[go: up one dir, main page]

WO2025015131A2 - Système de gestion de style de vie - Google Patents

Système de gestion de style de vie Download PDF

Info

Publication number
WO2025015131A2
WO2025015131A2 PCT/US2024/037525 US2024037525W WO2025015131A2 WO 2025015131 A2 WO2025015131 A2 WO 2025015131A2 US 2024037525 W US2024037525 W US 2024037525W WO 2025015131 A2 WO2025015131 A2 WO 2025015131A2
Authority
WO
WIPO (PCT)
Prior art keywords
patient
data
clinician
algorithm
user
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/US2024/037525
Other languages
English (en)
Other versions
WO2025015131A3 (fr
Inventor
R. Maxwell Flaherty
Carmine SILANO
Edward Roberts
D. Gregory FREY
J. Christopher Flaherty
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Salutaris Vitae Inc
Original Assignee
Salutaris Vitae Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Salutaris Vitae Inc filed Critical Salutaris Vitae Inc
Publication of WO2025015131A2 publication Critical patent/WO2025015131A2/fr
Publication of WO2025015131A3 publication Critical patent/WO2025015131A3/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance

Definitions

  • the present inventive concepts relate generally to systems, devices, and methods for managing a lifestyle of a patient.
  • a system for managing a lifestyle of a patient comprises a patient device comprising a user interface, the patient device configured to receive patient personalized data from the patient.
  • the system further comprises a processing unit configured to receive information from the patient device, and comprises: a memory module configured to store at least: patient information; and instructions used by the processing unit to perform an algorithm.
  • the algorithm is configured to analyze the patient information and provide feedback to the patient to tend the patient to achieve a healthy lifestyle based on the analysis.
  • the patient device comprises at least a portion of the processing unit.
  • the system is configured to provide a communication pathway between the patient and one or more: clinicians and/or suppliers.
  • the patient device is configured to receive a facial expression signal of the patient and/or a vocal expression signal of the patient and to generate from the facial and/or vocal expression signal two or more signal metrics, and the algorithm is configured to compute an output using a weighted combination of the two or more signal metrics and to provide the feedback based on the output.
  • the system algorithm comprises a model configured to provide at least a portion of the feedback, and the model is a machine-learning model that is trained using a plurality of training samples.
  • the user interface comprises an augmented reality user interface.
  • FIG. 1 illustrates a schematic view of a system for managing a lifestyle of a patient, consistent with the present inventive concepts.
  • first element when a first element is referred to as being “in”, “on” and/or “within” a second element, the first element can be positioned: within an internal space of the second element, within a portion of the second element (e.g. within a wall of the second element); positioned on an external and/or internal surface of the second element; and combinations of one or more of these.
  • proximate when used to describe proximity of a first component or location to a second component or location, is to be taken to include one or more locations near to the second component or location, as well as locations in, on and/or within the second component or location.
  • a component positioned proximate an anatomical site e.g. a target tissue location
  • spatially relative terms such as “beneath,” “below,” “lower,” “above,” “upper”, “under” and the like may be used to describe an element and/or feature's relationship to another element(s) and/or feature(s) as, for example, illustrated in the figures. It will be further understood that the spatially relative terms are intended to encompass different orientations of the device in use and/or operation in addition to the orientation depicted in the figures. For example, if the device in a figure is turned over, elements described as “below” and/or “beneath” other elements or features would then be oriented “above” the other elements or features. The device can be otherwise oriented (e.g. rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.
  • a component, process, and/or other item selected from the group consisting of A; B; C; and combinations thereof shall include a set of one or more components that comprise: one, two, three or more of item A; one, two, three or more of item B; and/or one, two, three, or more of item C.
  • a quantifiable parameter when described as having a value “between” a first value X and a second value Y, it shall include the parameter having a value of at least X, no more than Y, and/or at least X and no more than Y.
  • a length of between 1 and 10 shall include a length of at least 1 (including values greater than 10), a length of less than 10 (including values less than 1), and/or values greater than 1 and less than 10.
  • the expression “configured (or set) to” used in the present disclosure may be used interchangeably with, for example, the expressions “suitable for”, “having the capacity to”, “designed to”, “adapted to”, “made to” and “capable of’ according to a situation.
  • the expression “configured (or set) to” does not mean only “specifically designed to” in hardware.
  • the expression “a device configured to” may mean that the device “can” operate together with another device or component.
  • threshold refers to a maximum level, a minimum level, and/or range of values correlating to a desired or undesired state.
  • a system parameter is maintained above a minimum threshold, below a maximum threshold, within a threshold range of values, and/or outside a threshold range of values, such as to cause a desired effect (e.g. efficacious therapy) and/or to prevent or otherwise reduce (hereinafter “prevent”) an undesired event (e.g. a device and/or clinical adverse event).
  • a system parameter is maintained above a first threshold (e.g.
  • a threshold value is determined to include a safety margin, such as to account for patient/user variability, system variability, tolerances, and the like.
  • “exceeding a threshold” relates to a parameter going above a maximum threshold, below a minimum threshold, within a range of threshold values and/or outside of a range of threshold values.
  • the term “functional element” is to be taken to include one or more elements constructed and arranged to perform a function.
  • a functional element can comprise a sensor and/or a transducer.
  • a functional element is configured to deliver energy.
  • a functional element is configured to treat tissue (e.g. a functional element configured as a treatment element).
  • a functional element e.g. a functional element comprising a sensor
  • a sensor or other functional element is configured to perform a diagnostic function (e.g. to gather data used to perform a diagnosis).
  • a functional element is configured to perform a therapeutic function (e.g. to deliver therapeutic energy and/or a therapeutic agent).
  • a functional element comprises one or more elements constructed and arranged to perform a function selected from the group consisting of: deliver energy; extract energy (e.g. to cool a component); deliver a drug or other agent; manipulate a system component or patient/user tissue; record or otherwise sense a parameter such as a patient/user physiologic parameter or a system parameter; and combinations of one or more of these.
  • a functional element can comprise a fluid and/or a fluid delivery system.
  • a functional element can comprise a reservoir, such as an expandable balloon or other fluid-maintaining reservoir.
  • a “functional assembly” can comprise an assembly constructed and arranged to perform a function, such as a diagnostic and/or therapeutic function.
  • a functional assembly can comprise an expandable assembly.
  • a functional assembly can comprise one or more functional elements.
  • the term “transducer” where used herein is to be taken to include any component or combination of components that receives energy or any input, and produces an output.
  • a transducer can include an electrode that receives electrical energy, and distributes the electrical energy to tissue (e.g. based on the size of the electrode).
  • a transducer converts an electrical signal into any output, such as: light (e.g.
  • a transducer comprising a light emitting diode or light bulb), sound (e.g. a transducer comprising a piezo crystal configured to deliver ultrasound energy); pressure (e.g. an applied pressure or force); heat energy; cryogenic energy; chemical energy; mechanical energy (e.g. a transducer comprising a motor or a solenoid); magnetic energy; and/or a different electrical signal (e.g. different than the input signal to the transducer).
  • a transducer can convert a physical quantity (e.g. variations in a physical quantity) into an electrical signal.
  • a transducer can include any component that delivers energy and/or an agent to tissue, such as a transducer configured to deliver one or more of: electrical energy to tissue (e.g. a transducer comprising one or more electrodes); light energy to tissue (e.g. a transducer comprising a laser, light emitting diode and/or optical component such as a lens or prism); mechanical energy to tissue (e.g. a transducer comprising a tissue manipulating element); sound energy to tissue (e.g. a transducer comprising a piezo crystal); chemical energy; electromagnetic energy; magnetic energy; and combinations of one or more of these.
  • the term “material” can refer to a single material, or a combination of two, three, four, or more materials.
  • System 10 is configured to interface with one or more users, user U, such as one or more patients (patient P herein), clinicians (clinician C herein), and/or suppliers (supplier S herein), each as shown.
  • System 10 is configured to assist patient P toward living a healthy lifestyle, such as by eating in a healthy manner and/or performing other tasks that cause patient P to tend to be healthy.
  • Patient P can comprise one or more human beings that are relatively healthy (e.g., a patient that wants to remain healthy via use of system 10), and/or one or more human beings whose health is compromised (e.g., a patient that wants to become healthier due to use of system 10).
  • System 10 can comprise one or more patient devices, patient device 100 shown, which can be used by patient P to interface with system 10, such as to request health related information from system 10 and/or to obtain an item provided by system 10 (e.g., provided by a supplier S who also uses system 10).
  • System 10 can comprise one or more clinician devices, clinician device 200 shown, which can be used by clinician C to interface with system 10, such as to provide health related information to system 10 and/or directly to a patient P of system 10.
  • System 10 can comprise one or more supplier devices, supplier device 300 shown, which can be used by supplier S to interface with system 10, such as to receive an item request to be fulfilled by supplier S.
  • System 10 can be configured to provide (e.g., via same day delivery or otherwise) to patient P one or more items, item 20 shown, where item 20 can include one or more: food products, supplements, beauty or skin care products, instructions (e.g., cooking instructions and/or other instructions), devices, and/or other physical items, that have been determined by system 10 (e.g., by an algorithm of system 10 as described herein, or by a clinician of system 10) to be beneficial to the health (e.g., physical and/or mental health), demeanor, attitude, wellbeing, quality of life, and/or satisfaction of the patient (singly or collectively, “health” of the patient herein).
  • health e.g., physical and/or mental health
  • demeanor demeanor
  • attitude e.g., wellbeing, quality of life, and/or satisfaction of the patient (singly or collectively, “health” of the patient herein).
  • System 10 can be configured to provide patient P specific information, personalized data 99 shown, such as information determined by system 10 to be beneficial to the health of the patient.
  • personalized data 99 includes a recommendation of an item (e.g., an item 20 of system 10, or other food item, such as a meal prepared at a restaurant) for ingestion and/or other use by patient P, whether or not the item is provided to patient P by system 10.
  • system 10 is configured to determine personalized data 99, which may or may not include providing a determined item 20 to the patient.
  • System 10 can be configured to determine personalized data 99 based at least in part on data related specifically to patient P (e.g., patient data 101 described herein). For example, system 10 can base one or more decisions on: family history; DNA and/or other genetic data; medical history; likes and dislikes; allergies; dietary restrictions; fitness and/or other health goals; and combinations of these.
  • system 10 is configured to connect multiple patients P, clinicians C, and/or suppliers S via an interconnected network of patient devices 100//, clinician devices 200//, and supplier devices 300// (referred singularly or collectively to as devices 100, 200, and/or 300 herein).
  • system 10 comprises one or more networks, network 50 shown, such as a computer and/or other communications network for operably interconnecting devices 100, 200, and 300 to each other as well as other components of system 10.
  • Network 50 can comprise the Internet, a private network, a cellular network or other wireless network, a wired network, and/or other wired and/or wireless information sharing and/or data transmitting network.
  • system 10 comprises a centralized computer for data storage and/or data processing, server 400 shown.
  • Server 400 can be configured to host one or more services of system 10 to devices 100, 200, and/or 300.
  • server 400 comprises a cloud-based server.
  • server 400 comprises a decentralized server, such as when each device 100, 200, and/or 300 of system 10 contributes processing power and/or data storage space to server 400, forming an interconnected network of computing nodes functioning as a server for system 10.
  • System 10 can include one or more remote item storage locations, supplier warehouse 30 shown, for storing various items 20 (items 20s) prior to delivery to patient P.
  • system 10 comprises one or more local item storage locations, patient pantry 40 shown, for storing various items 20 (items 20p) that are already with the possession of patient P.
  • System 10 can comprise fulfillment network 60 shown, such as a network of delivery services, delivery trucks, delivery drivers, delivery drones, and/or other tools, vendors, or services required to provide patient P with item 20 from supplier warehouse 30.
  • system 10 is configured to determine an item 20 beneficial to the health of patient P, and via fulfillment network 60, have item 20 delivered to patient P.
  • system 10 can be configured to alert patient P that the determined item 20 is available to them (e.g., is already available and/or has become available).
  • System 10 can comprise one or more processing units, each comprising one or more processors. Each processor can be configured to execute one or more algorithms, such as one or more algorithms whereby the instructions for which are stored in memory operably coupled to the processor.
  • patient device 100 can comprise processing unit 110, that includes processor 111 which is operably coupled to a memory storage component, memory 112 shown.
  • Memory 112 can store instructions for one or more executable routines or other algorithms, algorithm 115 shown. Additionally or alternatively, memory 112 can store instructions for running an application (e.g., a software application) of system 10, application 116, or an application developed by a third-party, third-party app 116’, such as an application that has been downloaded and/or installed in memory 112 to “run” on device 100.
  • an application e.g., a software application
  • clinician device 200 comprises processing unit 210, that includes processor 211 which is operably coupled to memory 212, each as shown.
  • Memory 212 can store instructions for one or more executable routines and/or other algorithms, algorithm 215 shown. Additionally or alternatively, memory 212 can store instructions for running an application (e.g., a software application) of system 10, application 216, or an application developed by a third-party, third-party app 216’, that has been downloaded and/or installed onto memory 212 to run on device 200.
  • supplier device 300 comprises processing unit 310, that includes processor 311 which is operably coupled to memory 312, each as shown. Memory 312 can store instructions for one or more executable routines and/or other algorithms, algorithm 315 shown.
  • memory 312 can store instructions for running an application (e.g., a software application) of system 10, application 316, or an application developed by a third-party, third-party app 316’, that has been downloaded and/or installed in memory 312 to run on device 300.
  • server 400 comprises processing unit 410, that includes processor 411 which is operably coupled to memory 412, each as shown.
  • Memory 412 can store instructions for one or more executable routines, algorithm 415 shown.
  • memory 412 can store instructions for running an application (e.g., a software application) of system 10, application 416 (e.g., an application that can be downloaded into memory storage components of devices 100, 200, and/or 300, and/or an application configured to be performed by processing unit 410 of server 400).
  • application 416 e.g., an application that can be downloaded into memory storage components of devices 100, 200, and/or 300, and/or an application configured to be performed by processing unit 410 of server 400.
  • memory 412 comprises all or a portion of memory 112, 212, and/or 312, such as when data used by device 100, 200, and/or 300 is maintained in a cloud, network, or other remote storage location.
  • algorithm 415 can comprise and/or refer to one or more of algorithms 115, 215, and/or 315.
  • algorithm 415 can comprise an algorithm configured to be performed by processor 111 of patient device 100, such as when algorithm 415 comprises algorithm 115, the instructions for which are stored in memory 112.
  • application 416 can comprise and/or refer to one or more of applications 116, 116’, 216, 216’, 316, and/or 316’.
  • Algorithm 415 can comprise one or more routines, such as patient care algorithm 441, or comparison algorithm 443, each described herein.
  • Application 416 can comprise one or more applications, such as wellness hub 431, meal planner 432, or cart analyzer 433, each described herein.
  • processing unit 410 comprises algorithm 415AI shown, where algorithm 415AI comprises a machine learning, neural network, and/or other artificial intelligence algorithm (“Al algorithm” herein).
  • Algorithm 415AI can comprise one or more Al algorithms that have been trained by a first processing unit (e.g., processing unit 410) and is configured to process data (e.g., patient data, clinician data, system data, and/or supplier data, each described herein) on the first and/or on a second processing unit (e.g., processing unit 110, 210, and/or 310 described herein).
  • System 10 can comprise one or more databases configured to store data that has been collected by and/or input into system 10.
  • patient device 100 can comprise database 120, where database 120 is configured to store data related to patient P, patient data 101, each as shown.
  • Database 120 can be stored in memory 112.
  • Clinician device 200 can comprise database 220, where database 220 is configured to store data related to clinician C, clinician data 201, each as shown.
  • Database 220 can be stored in memory 212.
  • clinician database 220 can comprise a decentralized and/or distributed network.
  • Supplier device 300 can comprise database 320, where database 320 is configured to store data related to supplier S, supplier data 301, each as shown.
  • Database 320 can be stored in memory 312.
  • Server 400 can comprise system database 420, where database 420 is configured to store data related to the collective data of healthy living accumulated by system 10, system data 401, each as shown.
  • Database 420 can be stored in memory 412. Levels of security can be defined within each of the databases, such as security levels that correspond to access granted to each specific User U.
  • An algorithm of system 10 e.g., algorithm 115, 215, 315, and/or 415) can be configured to differentiate the level of access of a particular user U to a particular set of data, and either grant or block access accordingly.
  • algorithm 415 comprises a model configured to provide at least a portion of the feedback provided by system 10 to patient P.
  • the model comprises a machine-learning model that has been trained using a plurality of training samples.
  • an algorithm of system 10 is configured to perform a “product assessment” of one or more items 20.
  • algorithm 415 can analyze data selected from the group consisting of output of scientific studies; feedback from one or more patient’s P; feedback from one, two, or more clinician’s C; studies performed by and/or sponsored by the manufacturer of system 10; and combinations of these.
  • an algorithm of system 10 is configured to provide security (e.g., anonymity or other security measures) to various data uploaded into, downloaded from, stored in, and/or analyzed by, one or more components of system 10. For example, health and/or other personal data of a patient P and/or a clinician C can be “secured” by system 10.
  • security e.g., anonymity or other security measures
  • one or more portions of system 10 are configured as a blockchain system.
  • Patient device 100 can comprise one or more user interfaces, user interface 130 shown, such as for providing and/or receiving information to and/or from patient P.
  • User interface 130 can include one or more user input and/or output components.
  • user interface 130 can comprise a keyboard, mouse, touchscreen, and/or another human interface and/or other input component, user input component 131 shown.
  • user interface 130 can comprise a speaker, indicator light, haptic transducer, and/or another human and/or other interface output component, user output component 132 shown.
  • User interface 130 can include one or more visual outputs, display 133.
  • Patient device 100 can be configured to provide an interactive graphical interface, GUI 135, such as a graphical user interface provided by application 116.
  • GUI 135 is displayed to patient P on display 133.
  • user interface 130 comprises a graphical user interface (e.g., interface 130 comprises GUI 135).
  • user interface 130 comprises an interface for communicating with an artificial intelligence-based device.
  • user interface 130 comprises a virtual reality and/or an augmented reality interface.
  • Clinician device 200 can comprise an interface, user interface 230 shown, for providing and/or receiving information to and/or from clinician C.
  • User interface 230 can include one or more user input and/or output components.
  • user interface 230 can comprise a keyboard, mouse, touchscreen, and/or another human and/or other interface input component, user input component 231 shown.
  • user interface 230 can comprise a speaker, indicator light, haptic transducer, and/or another human and/or other interface output component, user output component 232 shown.
  • User interface 230 can include one or more visual outputs, display 233.
  • Clinician device 200 can be configured to provide an interactive graphical interface, GUI 235, such as a graphical user interface provided by application 216.
  • GUI 235 is displayed to clinician C on display 233.
  • user interface 230 comprises a graphical user interface (e.g., interface 230 comprises GUI 235).
  • user interface 230 comprises an interface for communicating with an artificial intelligence-based device.
  • Supplier device 300 can comprise an interface, user interface 330 shown, for providing and/or receiving information to and/or from supplier S.
  • User interface 330 can include one or more user input and/or output components.
  • user interface 330 can comprise a keyboard, mouse, touchscreen, and/or another human and/or other interface input component, user input component 331 shown.
  • user interface 330 can comprise a speaker, indicator light, haptic transducer, and/or another human and/or other interface output component, user output component 332 shown.
  • User interface 330 can include one or more visual outputs, display 333.
  • Supplier device 300 can be configured to provide an interactive graphical interface, GUI 335, such as a graphical user interface provided by application 316.
  • GUI 335 is displayed to supplier S on display 333.
  • user interface 330 comprises a graphical user interface (e.g., interface 330 comprises GUI 335).
  • user interface 330 comprises an interface for communicating with an artificial intelligence-based device.
  • system 10 comprises one or more accessory devices configured to interface with (e.g., provide data to) a primary device of system 10, such as patient device 100 and/or clinician device 200, for example patient peripheral 180 and clinician peripheral 280 shown.
  • Patient peripheral 180 and/or clinician peripheral 280 can include one or more devices configured to track (e.g., continuously or semi -continuously record) and/or measure (e.g., acutely and/or chronically measure) one or more patient parameters, such as: steps, weight, heart rate, heart rate and/or heart motion (e.g., ECG), temperature such as skin temperature, blood pressure, blood glucose, blood oxygen, pulse, calories burned, duration in an active state, food intake, caloric intake, muscle/training loads, recovery time, pace of an activity, hydration, pupil dilation, menstrual cycle dynamics, sleep such as sleep quality, and combinations of these.
  • patient peripheral 180 and/or clinician peripheral 280 comprise a third-party device, such as third-party patient peripheral 180’ and third-party clinician peripheral 280’ shown.
  • System 10 can be configured to interface with one or more third-party peripheral devices 180’ and/or 280’, such as devices selected from the group consisting of: Fitbit® device; Amazon Halo® device; KardiaMobile® device; Samsung® Galaxy Watch device; Samsung® Galaxy Ring device; Apple® Watch device; a Garmin® device; a Strave device; Mapmyrun® device; a product similar to any one or more of these; and combinations of these.
  • System 10 can include one or more functional elements, for example functional elements 199, 299, and 399 shown.
  • Functional elements 199, 299, and/or 399 can each comprise one, two, or more sensors, and/or one, two or more transducers.
  • Functional elements 199, 299, and/or 399 can each comprise a sensor configured to measure a physiologic parameter of a user U (e.g., patient P).
  • patient peripheral 180 comprises a device that is configured to be used intermittently by the patient, such as a wearable device (e.g., a fitness tracking type device), a rechargeable device (e.g., a device that is not used during recharging), and/or a disposable device that is configured to be frequently replaced by the patient (e.g., a disposable sensor device and/or a disposable pumping device).
  • a wearable device e.g., a fitness tracking type device
  • a rechargeable device e.g., a device that is not used during recharging
  • a disposable device that is configured to be frequently replaced by the patient
  • one or more algorithms of system 10 e.g., algorithm 115
  • algorithm 115 are configured to receive and process data (e.g., patient data 101) from patient peripheral 180, and to perform one or more processes or provide one or more outputs (as described herein) based on the received data, while patient peripheral 180 is being used.
  • the algorithm can be further configured to perform one or mor processes and/or provide one or more outputs without data received from patient peripheral 180 while patient peripheral 180 is not being used.
  • system 10 is configured to indicate to the patient (e.g., via a warning displayed on display 133) when an output of the system is not based on data received from patient peripheral 180 (e.g., “This output is not based on current heartrate because current heartrate is not being received from your heartrate monitor”).
  • an algorithm of system 10 is configured to generate “predicted patient data”, such as predicted data 101’, such as when data is received intermittently from patient peripheral 180. For example, if data from patient peripheral 180 is not being received by the system (e.g., as patient data 101), an algorithm can predict and/or otherwise “fill in” the missing data as predicted data 101’. As an example, if a patient averages 1000 steps per hour during the workday, as recorded from patient peripheral 180 comprising a fitness tracker, and for a period of time, data is no longer received from the fitness tracker, the algorithm can predict the patient maintains the average steps per hour.
  • system 10 comprises an Al algorithm (e.g., algorithm 115) that is configured to generate predicted data 101’ to fill in missing data from intermittent data sources.
  • system 10 comprises a confirmation routine, as described herein, where predicted data 101’ is presented to a user U (e.g., patient P and/or clinician C) prior to predicted data 101’ being used by an algorithm of system 10 to produce an output (e.g., predicted data 101’ requires confirmation before being used as patient data 101 is used herein).
  • system 10 can be configured alert the user (e.g., via a warning displayed on display 133) that the output is based on algorithmically predicted data.
  • system 10 provides a user input (e.g., a touch icon of GUI 135 displayed on display 133) for a user U (e.g., patient P and/or clinician C) to confirm predicted data 101’, and/or to dismiss a warning that the provided output is based on predicted data 101’.
  • patient data 101 is updated at regular intervals, such as results of a blood test being provided to system 10 in monthly, bimonthly, annual, etc. intervals.
  • system 10 is configured to provide a reminder (e.g., via a message displayed to the user on display 133) to a user (e.g., patient P and/or clinician C) to provide missing patient data, for example when an expected data update is missed (e.g., the monthly blood test data is not provided to system 10).
  • an algorithm e.g., algorithm 115
  • algorithm 115 can be configured to determine predicted data 101’ when regularly provided data is missing, and/or the algorithm can be configured to not determine predicted data 101’, for example, when two, three, four, or more or more regular intervals of data have been missed.
  • system 10 can be configured to predict, via an Al algorithm, the results of a missing monthly blood test, but not to predict the results of a second (e.g., second consecutive) missing blood test.
  • Database 420 of server 400 can store various data (e.g., various data sets) recorded by, provided to, and/or generated by (e.g., by processing recorded and/or provided data) system 10 (“recorded by” and/or “measured by” herein).
  • database 420 can store information relating to items 20 of system 10, item data 421.
  • Item data 421 can include nutritional information, ingredients, serving size, and/or other information used in the determination by system 10 of providing personalized data 99 (e.g., an item 20) to a patient P.
  • Database 420 can store health-related information, health data 422, relating to one or more patients P of system 10 and/or relating to groups of patients (e.g., patients grouped by sex, nationality, age, and/or other grouping), such as information gathered from medical journals and/or from one or more clinicians C of system 10 (e.g., such as gathered from and agreed upon by a panel of clinicians C of system 10, as described herein).
  • groups of patients e.g., patients grouped by sex, nationality, age, and/or other grouping
  • clinicians C of system 10 e.g., such as gathered from and agreed upon by a panel of clinicians C of system 10, as described herein.
  • database 420 stores information relating to a community of patients P, community data 423, such as data relating to trends within a community of patients P, for example a community of patients P linked via a commonality, such as: geographic location; common interest (e.g., jogging); patient demographic parameter; patient health parameter (e.g., cancer patients or other patients with similar medical conditions); and/or a patient physiologic parameter (e.g., age, race, sex, DNA or other genetic parameter, blood parameter, blood gas parameter, and/or other patient physiologic parameter).
  • database 420 stores information used to train and/or perform Al algorithm 415AI, such as learning data 424 and/or Al data 425.
  • Learning data 424 can comprise information recorded by system 10 used to train Al algorithm 415AI, such as data that has been reviewed by a team of clinicians C to identify trends which algorithm 415AI is trained to identify from patient data 101 recorded by system 10.
  • the data reviewed by the clinicians is sorted into groups of data used to train Al algorithm 415AI (e.g., data determined to be applicable and/or otherwise acceptable by the clinicians) and data not used to train algorithm 415AI (e.g., data determined to not be applicable or otherwise acceptable by the clinicians).
  • Al data 425 can include data generated by algorithm 415AI relating to one or more trends identified in patient data 101 and/or other data recorded by system 10.
  • System 10 can be configured to identify one, two, or more items 20 recommended for patient P.
  • system 10 is further configured to indicate the benefits (e.g., the likely benefits) and/or advantages item 20 can provide to patient P (e.g., as compared to a comparable item 20).
  • System 10 can be configured to identify two or more patients P that are experiencing at least one similar health related parameter (e.g., a similar positive parameter and/or a similar adverse parameter). In some embodiments, system 10 can compare the two or more patients and provide personalized data 99 to the patient based on the comparison of the data (e.g., anonymized data) of the two or more patients.
  • a similar health related parameter e.g., a similar positive parameter and/or a similar adverse parameter.
  • system 10 can compare the two or more patients and provide personalized data 99 to the patient based on the comparison of the data (e.g., anonymized data) of the two or more patients.
  • System 10 can be configured to perform the management of patient data 101 in such a way as to ensure compliance with national security, confidentiality, and/or other standards (e.g., US HIPAA, and/or EU Regulation on the Protection of Personal Data), such as to protect privacy of patients’ medical records and other individually identifiable health information (singly or collectively referred to as “protected health information” or simply “health information” or “health data” herein).
  • national security, confidentiality, and/or other standards e.g., US HIPAA, and/or EU Regulation on the Protection of Personal Data
  • protected health information or simply “health information” or “health data” herein.
  • System 10 can be configured to assist the clinician in providing advice (e.g., functional medicine advice) to patients.
  • system 10 is configured to gather and/or normalize patient data 101 (e.g., medical history, lab results, fitness and/or mood tracker data, and/or patient data) and such data can be stored in clinician database 220.
  • system 10 is configured to gather and/or normalize data available via publications (e.g., medical journals, clinical trials, and/or publicly available and/or confidential clinical data), and such data can be stored in clinician database 220.
  • System 10 can be configured to provide personalized data 99 to the patient (e.g., via the clinician) based on the gathered publications data.
  • system 10 comprises a “data update routine”, such as when an algorithm of system 10 (e.g., an Al algorithm and/or other algorithm as described herein) is configured to update one or more databases of data (e.g., as described herein), and/or other data stored in one or more memory components of system 10.
  • the data update routine is performed on a routine basis (e.g., once a day, once a week, and/or other time duration).
  • changes to stored data requires a confirmation by a user U (e.g., a patient P and/or a clinician C), such as when system 10 comprises a “confirmation routine” that requires a user U to accept any data or other changes prior to the change being made by system 10.
  • System 10 can be configured to notify one or more users (e.g., a family member of the patient and/or one or more clinicians C) if the patient has ingested an item 20 that is “non-approved” and/or “detrimental” to the health of the patient if ingested.
  • system 10 is configured to generate one or more projected outcomes if the patient ingests (e.g., continues to ingest) the non-approved and/or detrimental item 20.
  • System 10 can be configured to analyze and/or incorporate family history data into a memory storage component, such as when generating personalized data 99 for the patient.
  • Family history data can include health information of immediate and/or distant relatives of the patient.
  • family history data includes risk factors, successful medical treatments, unsuccessful medical treatments, hypersensitivities, genetic conditions, DNA profiling data, and/or other similar data.
  • System 10 can be configured to record one, two, or more environmental factors of the patient, such as via patient device 100. Additionally, system 10 can be configured to analyze and incorporate the environmental factors when generating personalized data 99 for the patient. In some embodiments, system 10 can be configured to provide personalized data 99 to the patient based on the recorded environmental data (e.g., data related to ambient temperature, barometric pressure, noise level, and/or other environment data, of the current, previous, and/or future environment of the patient).
  • the recorded environmental data e.g., data related to ambient temperature, barometric pressure, noise level, and/or other environment data, of the current, previous, and/or future environment of the patient.
  • System 10 can be configured to identify and/or notify one or more users (e.g., a clinician C and/or the patient P) if the patient’s mood and/or overall disposition is trending in a direction that historically results in an ingestion of a non-approved and/or detrimental item 20.
  • system 10 can identify the patient’s mood via pairing with a mood sensor, such as a sensor that tracks one, two, or more of breathing patterns, heart rate, brainwave patterns, eye movement patterns, sleep patterns, skin electrochemical activity and temperature, inter alia, and/or other parameter of patient P (e.g., recorded via a MUSETM headband, Empatica® wristband, and/or Emotiv® Insight Headgear).
  • System 10 can be further configured to recommend one, two, or more items 20 in response to the patient’s mood (e.g., recommend healthy comfort food to the patient P).
  • Patient data 101 can be stored in patient device 100 (as shown in Fig. 1), in clinician device 200, in supplier device 300, in system server 400, and/or in another component of system 10.
  • System 10 can be configured to identify an item 20, and/or perform another function of system 10 as described herein, based on an analysis of patient data 101 that includes data that has been entered and/or updated within the last one day, one week, and/or 1 month.
  • system 10 can include patient device 100 and/or clinician device 200, either or both, user device 100/200 herein.
  • System 10 can be configured to receive information related to facial, vocal, and/or behavioral expressions of a patient P and/or a clinician C, such as information received via user device 100/200 (e.g., a phone, tablet, or other device including a camera and/or microphone), and/or another component of system 10 configured to capture images of and/or sounds produced by patient P and/or clinician C.
  • System 10 e.g., via algorithm 115, 215, and/or 415) can be configured to generate a plurality of signal metrics from the received information, and to calculate a reaction score (e.g., an emotional reaction score that relates to an emotional response of a user) using the generated plurality of signal metrics.
  • a reaction score e.g., an emotional reaction score that relates to an emotional response of a user
  • System 10 can be further configured to provide a food product or other item 20 (e.g., provided to patient P) based at least in part on the calculated reaction score.
  • the reaction score relates to a desire, or lack thereof, that patient P or clinician C has related to a particular item 20 (e.g., a food product or other item 20 that patient P or clinician C likes or dislikes for ingestion or other use by patient P).
  • System 10 can comprise a user device 100/200 that is configured to measure facial temperature of patient P, such as a user device 100/200 that includes an infrared or other thermal camera. Facial temperature information captured by user device 100/200 can be stored as patient data 101, such as when system 10 is configured to recommend and/or otherwise provide an item 20 based on at least facial temperature information. System 10 (e.g., via an algorithm of system 10) can be configured to convert facial temperature information into patient health condition information and/or other facial temperature derived patient information (also patient data 101). In some embodiments, facial temperature information or facial temperature derived patient information and a second type of patient data 101 is used by system 10 to provide an item 20.
  • the second type of patient data 101 can comprise patient genetic information, patient allergy information, patient location information, and/or other patient information.
  • system 10 can be configured to enable communication (e.g., transfer of information) between a patient P using patient device 100 and a clinician C using clinician device 200, when patient P and clinician C are remotely located with respect to each other.
  • information is transferred between a patient P and a remotely located clinician C in real time, such as when sets of information transfers (e.g., back and forth information transfers) occur in time periods less than 10 minutes, or less than 5 minutes.
  • information transferred between patient P and clinician C includes at least audio information (e.g., the voice of patient P or clinician C), at least visual information (e.g., one or more images of patient P), or both.
  • System 10 can be configured to provide a list of available products (e.g., item 20), for example a list of food products made available to a patient based on patient data 101, such as when the list of food products is provided based on at least patient health information as well as the patient’s location (e.g., the patient’s current location).
  • a list of available products e.g., item 20
  • the list of food products is provided based on at least patient health information as well as the patient’s location (e.g., the patient’s current location).
  • the list is provided in response to a request that is made by the patient, for example a request for a food product, such as a sandwich.
  • System 10 can be configured to determine a first list of available products, and to apply a filter to the first list, such as a filter based at least on patient data 101 (e.g. a filter based on at least patient health information and patient location information).
  • System 10 can be configured to provide (e.g., display on a screen, present audibly, or both) the filtered list of available products to the patient, for example such that the patient can select an item 20 from the list for purchase (e.g., for purchase and delivery to the patient).
  • the filtered list of available products does not include items which the patient is trying to avoid (e.g., based on patient data 101), for example to limit temptation of the patient from selecting undesired products.
  • System 10 can be configured to identify a particular user of a device, such as to confirm the identity of patient P using patient device 100 and/or confirm the identity of clinician C using clinician device 200.
  • System 10 can identify a user via fingerprint, voiceprint, and/or facial recognition.
  • a functional element of a device for example functional element 199 of patient device 100, can comprise a microphone array and a vibration measurement assembly.
  • the microphone array can be configured to detect airborne acoustic waves corresponding to a vocalization of the user
  • the vibration measurement assembly can be configured to detect vibrations of tissue of the user caused by the vocalization.
  • System 10 can be configured to authenticate the user of the device based on an authentication dataset that is generated based on signals from the microphone array and vibration measurement assembly.
  • one or more functions of system 10 are disabled without affirmative confirmation of the identity of the user (e.g., patent P or clinician C), for example changing of patient data and/or clinician data (e.g., to prevent malicious tampering and/or other unauthorized changes to patient data 101 or other data of system 10).
  • system 10 can be configured to provide a food product or other item 20 to patient P based on an analysis of patient data 101.
  • a list of multiple items 20 is provided to patient P (e.g., provided on a display screen) in a prioritized arrangement.
  • System 10 can provide the list of multiple items 20 with a prioritization that is achieved via graphical differentiation of the different items 20. For example, items 20 that are of more significant benefit to patient P can be graphically different via font size (e.g., bigger font for more benefit), color, or other graphical property.
  • placement of icons or other graphical presentations of the various items 20 can be positioned on a screen in a differentiating manner, such as when the items 20 of more benefit are positioned “above” other items 20, or in a section of a display noted as signifying one or more items 20 of higher benefit than others.
  • one or more algorithms and/or applications of system 10, such as algorithm 415 and/or application 416 can comprise an Al algorithm and/or Al based application, such as an Al assistant (e.g., application 416 can comprise an Al assistant, such as an application that utilizes a large language model (LLM) that has been trained to perform a function of system 10).
  • An Al assistant of system 10 can be configured to assist and/or replace a user of system 10.
  • an Al assistant can be configured to perform one or more actions described herein of clinician C or other user of system 10.
  • an Al assistant is configured to perform all, or at least a majority, of the functions of clinician C (e.g., use of system 10 by patient P does not require a clinician C comprising a human, the Al assistant is clinician C described herein).
  • a confirmation routine or other verification process of system 10 can be performed by an Al assistant, with or without input from a user (e.g., without a human interaction) regarding the verification process.
  • application 216 comprises an Al assistant configured to assist clinician C with input, processing, review, and/or confirmation of data (e.g., clinician data 201).
  • application 216 comprising an Al assistant is configured to process and summarize data from a first set comprising a large set of users of system 10 (e.g., patients P, clinicians C, and/or suppliers S), such that a second set comprising a limited set of users (e.g., clinicians C) can review the summarized data.
  • a first set comprising a large set of users of system 10 (e.g., patients P, clinicians C, and/or suppliers S)
  • a second set comprising a limited set of users (e.g., clinicians C) can review the summarized data.
  • the large set of users can comprise at least 50,000 users, such as at least 1,000,000 users, 2,500,000 users, 5,000,000 users, or 10,000,000 users
  • the limited set of users can comprise no more than 5,000 users, such as no more than 2,500 users, 1,500 users, 1,000 users, or 500 users
  • a limited number of clinicians C can service a large set of patients P with the assistance of application 216 comprising a trained Al assistant
  • application 216 comprising a trained Al assistant can service a set of patients P without a clinician C (e.g., when the Al assistant is trained with a dataset comprising information collected from a set of clinicians C, patients P, and/or other medical and/or health related sources).
  • system 10 comprises and/or is configured as wellness hub 431 described herein.
  • Processing unit 410 can further comprise an application 416 comprising a wellness hub 431, where hub 431 can be configured to provide direct and/or instant communication between two or more users U, such as communication between patient P and a clinician C (e.g., a nutritionist or dietitian previously associated with the patient or otherwise).
  • communication between two or more users U is provided by and/or otherwise driven by an Al algorithm of system 10 (e.g., Al algorithm 415AI), as described herein.
  • Wellness hub 431 can enable basic messaging between predetermined users U, such as messaging between patient P and clinician C (e.g., a particular clinician C).
  • Wellness hub 431 can enable clinician C to identify office hours during which patient P can contact the clinician.
  • Wellness hub 431 can comprise a toggle on/off feature that enables clinician C and/or supplier S to allow and/or prevent incoming communications from patient P.
  • Wellness hub 431 can indicate whether clinician C and/or suppliers S is a member of a larger network of providers (e.g., medical practice, insurance group, broad -based product supplier, and/or other network), or a smaller group of users authorized by the patient P (e.g., individual and/or smaller group of clinicians and/or suppliers who have been granted access, such as to a designated security level of data).
  • providers e.g., medical practice, insurance group, broad -based product supplier, and/or other network
  • a smaller group of users authorized by the patient P e.g., individual and/or smaller group of clinicians and/or suppliers who have been granted access, such as to a designated security level of data.
  • Wellness hub 431 can be configured to comprise features based on the type of user U, for example, the features available to clinician C can be dissimilar to the features available to patient P.
  • wellness hub 431 comprises a messaging system (e.g., an Al -based messaging system and/or other messaging system) that includes one, two, or more features that are only available to one or more clinician C.
  • clinician C can be provided with tools that allow for the management of conversations (also referred to as “messaging” herein) with multiple patients P simultaneously, as well as the ability to view a historical overview of where previous conversations with a patient ended.
  • clinician C can be provided with contact cards (e.g., physical or electronic) for each patient P that displays their respective medical information, nutritional data (e.g., data collected in real-time and/or past data), while also allowing for the clinician C to obscure the patient P’s personal identifying information.
  • Wellness hub 431 can be configured to allow for one or more interactions (e.g., specific messaging or other interactions but not all interactions) between clinician C and patient P to be audited or otherwise monitored.
  • Wellness hub 431 can be configured to allow a clinician C to monitor the progress toward and/or performance of the nutritional, fitness, and/or other health goals of patient P via system 10, such as progress that is monitored by an algorithm (e.g., an Al algorithm) of system 10.
  • system 10 can be configured to adjust one or more algorithms of system 10, as described herein, such as based on feedback from the clinician C doing the monitoring.
  • Wellness hub 431 can include a patient care algorithm 441, where algorithm 441 can be configured to analyze data about the care of patient P and/or the performance of clinician C.
  • Patient care algorithm 441 can analyze the number and/or content of conversations (e.g., messaging) between patient P and clinician C.
  • Patient care algorithm 441 can analyze one or more recommendations and/or other information provided by clinician C to patient P, such as complete versus incomplete recommendations.
  • Patient care algorithm 441 can analyze patient feedback ratings received by system 10 (e.g., via patient device 100), such as ratings related to quality of care, quality of clinician C, and other care and/or clinician information.
  • Patient care algorithm 441 can analyze prescriptions and/or supplements prescribed by clinician C for patient P.
  • Patient care algorithm 441 can analyze and/or compare health and/or fitness data of patient P at discrete time points (e.g., period, routine time points, and or manually determined time points). Patient care algorithm 441 can detect and/or present warnings to clinician C based on the context of a conversation with patient P.
  • wellness hub 431 is configured to provide a platform through which clinicians C can identify and/or engage with potential clients (e.g., patients P). Wellness hub 431 can allow clinician C to identify patients based on one, two, or more criteria, such as health concerns of a patient P.
  • Wellness hub 431 can allow a patient P to find one, two or more clinicians (e.g., to function as Clinician C) based on one, two, or more criteria, such as a minimum review rating (e.g., 5-star reviews), recommendation from another patient P, applicability of the clinician’s skills, expertise, and/or background in an area desired by the patient and/or associated with a patient goal and/or medical condition.
  • a minimum review rating e.g., 5-star reviews
  • recommendation from another patient P e.g., applicability of the clinician’s skills, expertise, and/or background in an area desired by the patient and/or associated with a patient goal and/or medical condition.
  • an Al algorithm of system 10 identifies a list of recommended one or more clinicians based on various data of patient data 101 as described herein.
  • Wellness hub 431 can determine particular groups of one or more clinicians, such as a grouping based on one, two, or more criteria, such as clinicians with knowledge of a particular diet format (e.g., keto, gluten-free, and/or other diet format). Wellness hub 431 can allow clinicians to organize themselves into groups based on one, two, or more criteria. Wellness hub 431 can provide instant, direct-access, and/or on-demand consultation services with a clinician C.
  • a particular diet format e.g., keto, gluten-free, and/or other diet format.
  • wellness hub 431 can be configured to order an item 20 to be provided or otherwise delivered to patient P, such as instructed by clinician C.
  • System 10 can provide (e.g., display on user interface 130) available food stores and/or other food sources and/or available delivery services, singly or collectively supplier S herein, within a particular area of patient P (e.g., with a threshold distance of patient P, such as within 50 miles, 25 miles or 10 miles of patient P), such as when providing a searchable listing of what food-based items 20 are available from each supplier S.
  • System 10 can further identify “preferred” suppliers S (e.g., suppliers S identified by an Al algorithm or other algorithm 415 of system 10 as being desired) for patient P.
  • System 10 can provide an aggregated search to locate or order particular items from one or more suppliers S in the local area of patient P, and/or able to supply an item 20 within a particular time limit (e.g., no more than one week, one day, and/or 4 hours).
  • System 10 can display a food ordering menu for clinician C to complete on behalf of patient P.
  • System 10 can be configured to include in a food product display an “emphasis” on one or more nutritional and/or other potential health aspects of a food item, such as an emphasis based on nutritional, fitness, and/or other health guidelines, diets, and/or other food-based data (e.g., data specifically related to the particular patient P).
  • System 10 can display previously ordered and/or previously “favorited” items (e.g., one or more items 20 as favorited or otherwise preferred or recommended by either by clinician C or patient P), such as to provide for simplified reordering (e.g., rapid reordering).
  • System 10 can be configured to provide a “shopping cart” (also referred to as “cart” herein), including one or more specific items 20.
  • a cart as created and/or otherwise identified by clinician C for a particular patient P or group of patients P can be published or otherwise shared with the particular patient P, such as for review, confirmation, selection, and/or display (e.g., immutable display and/or at least long-lasting display).
  • the cart may be modified by patient P, and such modifications can be communicated back to clinician C for review, as well as acceptance (confirmation), rejection, and/or further modification.
  • wellness hub 431 is configured to create and/or otherwise define one, two, or more nutritional, fitness and/or other health milestones, such as milestones that can divide a principal health goal into two or more discrete goals (e.g., goals related to fitness and/or other health of patient P).
  • wellness hub 431 can be configured to modify one or more algorithms 415 of system 10, as described herein, such as to increase the likelihood of achieving one or more health goals of patient P (e.g., one or more discrete health goals of patient P).
  • wellness hub 431 is configured to present third-party products (e.g., one or more items 20 comprising food products provided by one or more suppliers S) to clinician C and/or patient P, such as food products and/or other products that align or support the nutritional, fitness, and/or other health goals of patient P.
  • System 10 can be configured to determine and/or filter (e.g., sub-select) a list of products (e.g., products proposed to be items 20) based on the context of a conversation (e.g., via keywords, patient selected input, profile, and/or other relevant conversation parameters) between clinician C and patient P.
  • System 10 can display and/or recommend the determined and/or filtered products to clinician C and/or patient P.
  • System 10 can directly recommend a determined and/or filtered product to patient P.
  • System 10 can notify clinician C of products that patient P has selected (e.g., from the determined and/or filtered list).
  • System 10 can display and/or hide cost data for a product (e.g., an item 20 comprising a determined and/or filtered food product or other product) to clinician C and/or patient P.
  • System 10 can allow for patient P to select products (e.g., only select products) that are presented to clinician C for review, such that clinician C can accept, reject, and/or modify the product (e.g., via a confirmation routine of system 10).
  • wellness hub 431 uploads, stores, and/or analyzes data from one, two, or more patient P wearable devices (e.g., products configured as wristbands, rings, headbands, glasses, and/or other patient-wearable devices that gather data related to health, fitness, mood, food intake, and/or environmental conditions), such as to analyze and/or share the data with clinician C.
  • System 10 can comprise an interface configured to upload and/or record data (e.g., singly or collectively “upload” or “record” herein) from one, two, or more wearable devices.
  • System 10 can utilize the uploaded data to determine which of a set of products (e.g., third-party food and/or other products) to display and/or recommend to clinician C and/or patient P.
  • a set of products e.g., third-party food and/or other products
  • wellness hub 431 is configured to arrange for the billing between patent P, clinician C, and/or supplier S.
  • supplier S can comprise an insurance provider of patient P, such that items reimbursed by the insurance provider can be recognized and/or reimbursement provided.
  • an algorithm of system 10 e.g., an algorithm 415 described herein
  • system 10 is configured to identify (e.g., recognize) a deviation of patient P from one or more nutritional, fitness, and/or other health goals, and wellness hub 431 is configured to implement one or more changes to patient P’s nutritional, fitness, and/or other health goals, such as to encourage or otherwise aid the patient in achieving their health goals.
  • wellness hub 431 can be configured to modify one or more algorithms of system 10, as described herein, such as to increase the likelihood of achieving one or more health goals of patient P.
  • System 10 can be configured to predict how patient P may react (e.g., physically, mentally, and/or otherwise react) to the revised health goals and/or the revised algorithms.
  • system 10 can measure, determine, and/or ask user U how accurately patient P has been following the revised health goals and/or assess the impact of one or more revised algorithms. Using this information, system 10 can be configured to make further adjustments to the revised health goals and/or the revised algorithms, such as to improve effectiveness of system 10 in causing patient P to achieve their goals. System 10 can be configured to adjust the recommended food products, quantities, consumption times, and/or supplements (e.g., an adjustment due to a revised algorithm).
  • system 10 can be configured to: request input from clinician C; suggest further changes in: food products, quantities, consumption times, and/or supplements; suggest patient exercise and/or other patient activities; and combinations of these.
  • the revised recommendations may come from other user U history or experience.
  • System 10 can create a gradient of change that can be implemented over a period of time. For example, if patient P switches from a high-carb to a low-carb diet, a gradual transition can help patient P avoid negative health impacts that may otherwise be experienced in response to such an aggressive transition.
  • System 10 can generate a “weaning” profile, such as to make gradual changes from one diet to another. For example, a weaning profile can follow a transition pattern that is arranged as at least one of a linear, s-curve, parabolic, logarithmic, and/or wavetable function.
  • wellness hub 431 is configured to match one or more patients P with one or more clinicians C based on one, two, or more preferences (e.g., care type, character, physical attributes, approach to medicine, specialty, locations, and/or other preferences of the one or more patients P or other preferences).
  • system 10 is configured to present user U with a variety of selectable and/or definable characteristics of various suppliers of products and/or services (item 20) that can be used by system 10 to find suppliers S that meet the indicated preferences.
  • System 10 can further allow user U to prioritize the various characteristics used, such as a priority of most important to least important.
  • System 10 can allow supplier S to select characteristics that best describe their products and/or services.
  • System 10 can determine its own set of characteristics for one or more suppliers S, such as characteristics determined based on user U feedback (e.g., patient P feedback), sensor data, and/or context and/or sentiment of a conversation.
  • wellness hub 431 connects available food delivery services and/or other item 20 suppliers to patient P and/or clinician C.
  • System 10 can identify food delivery services in a specified vicinity of patient P, and can display the results to patient P and/or clinician C.
  • System 10 can further locate and/or filter food delivery services based on distance to a current location (e.g., of patient P or clinician C) and/or distance to a specified location (which can comprise a future location or otherwise be different than the current location of patient P or clinician C).
  • System 10 can identify food delivery services based on a timetable of locations where patient P may be located.
  • system 10 can recognize patient P is likely to be located proximate a particular geographic location (e.g., near to Sarasota, Florida), such as when during a different time period (e.g., from 2pm-5pm) patient P is likely to be located proximate a different geographic location (e.g., Melbourne, Florida).
  • a particular geographic location e.g., near to Sarasota, Florida
  • a different time period e.g., from 2pm-5pm
  • wellness hub 431 is configured to generate a summary of the services provided by clinician C and/or supplier S.
  • wellness hub 431 calculates one or more performance scores for clinician C and/or supplier S, for example scores relating to one or more characteristics of clinician C and/or supplier S.
  • wellness hub 431 can provide a score of one or more characteristics of clinician C selected from the group consisting of: bedside manner; availability; affordability; response time; tone of communications; data-orientation; education; and combinations of these.
  • clinician C and/or supplier S can provide a “self-graded” score.
  • wellness hub 431 incorporates reviews from one or more other user U of system 10 (other than clinician C and/or supplier S as appropriate) to validate the clinician’s and/or supplier’s proclaimed strengths against reviewed (e.g., actual) performance.
  • wellness hub 431 can be configured to calculate one or more scores based solely on reviews provided by other users U of system 10.
  • the scores e.g., average scores
  • the score provided by clinician C and/or supplier S can be adjusted (e.g., slightly adjusted, or adjusted using an averaging technique) based on the calculated scores.
  • wellness hub 431 is configured to match a patient P with one or more clinicians C and/or suppliers S based on one or more preferences of the patient P and the scores of the one or more clinicians C and/or suppliers S. For example, if a patient P is interested in a clinician with a good bedside manner, wellness hub 431 can provide the patient P with a list of clinicians C with high bedside manner scores.
  • wellness hub 431 generates simulations of how the body, endurance, quality of life, and/or other health parameter of patient P may change in response to a change in one or more nutritional, fitness, and/or health goals, and/or a change in one or more algorithms 415 of system 10.
  • System 10 can receive input related to a food item (item 20), such as the associated caloric and/or other nutritional information of that item.
  • System 10 can further initiate an algorithm (e.g., algorithm 415), which considers the current state of the health of patient P, to perform one or more simulations on how the body, endurance, quality of life, and/or other health parameter of patient P may be impacted by the patient ingesting the particular food item (e.g., starting the ingestion of or increasing the ingestion of a particular food item), and/or avoiding or at least reducing the intake of the particular food item.
  • System 10 can notify patient P when a threshold quantity of a food item, or a threshold of a particular ingredient of a food item, is likely to cause adverse effects to patient P (e.g., a notification when the threshold has been reached and/or is about to be reached).
  • system 10 can be configured to review food-based items 20 in a shopping cart of user U, such as to review for (e.g., identify) food-based items 20 that are likely to have a negative effect on patient P.
  • system 10 can be configured to remove and/or replace the particular item 20, and/or prompt user U to remove or replace the item 20 with a healthier substitute.
  • System 10 can further identify food-based items 20 that should be consumed by patient P only in moderation, such as an identification based on their current health status.
  • wellness hub 431 is configured to generate a network and/or other connection between all clinicians C currently associated with a patient P, such as to aid in the communication and exchange of information between the various clinicians C and the patient P.
  • system 10 can be configured to assist in making choices (e.g., food-based items 20) that satisfy the recommendations of a single clinician C and/or satisfies the recommendations of a collective group of clinicians C (e.g., unanimously and/or via a majority) .
  • System 10 can aggregate the recommendations from each clinician C, address and/or otherwise point out contradicting recommendations, and assist in locating a supplier S of the food item for patient P.
  • System 10 (e.g., via an algorithm 415 of system 10 as described herein) can determine a resolution of contradicting clinician C recommendations, for example, such as when a dental professional instructs patient P to consume less acid-based food-based items 20 and a urologist instructions P to consume more acid-based food-based items 20.
  • system 10 can require an approval (e.g., via a confirmation routine of system 10), from either or both clinicians to the particular resolution determined by system 10.
  • wellness hub 431 allows patient P to manage individual clinician C’s access to documents, transcripts, communications, and/or other patient data (e.g., patient data 101).
  • System 10 can comprise a database that includes medical documents, clinician notes, scans, prescriptions, and/or other data of patient P (e.g., patient data 101).
  • System 10 can further allow user U to select one, two, or more subsets of data (e.g., one, two or more documents) on which system 10 is to perform an action.
  • wellness hub 431 generates, records, uploads, and/or identifies (singly or collectively “generates”, “records”, “uploads” or “identifies” herein) a “pool” of patient P data 101, such as to enable clinician C to perform research and/or one or more other analyses based on the particular pool of data generated.
  • System 10 can allow for patient P to anonymously share one, two, or more data documents and/or other data subsets for use in research and/or analysis.
  • System 10 can be configured to omit and/or otherwise redact patient-identifying information from the documents and/or other data subsets, generate a preview of the data with redactions, such as for approval, and then submit the redacted data to a database.
  • system 10 can be configured to submit unredacted documents and/or other data subsets to a database, where the sharable application programming interface (API) can include restricted access to fields of patient- identifying information.
  • System 10 can be configured to allow for clinician C to query data for research and analysis purposes across a narrow or broad filtered selection of patients.
  • System 10 can be configured to allow clinician C to re-hash or re-index the data into different database formats and/or types, such as for reasons of efficiency, speed, and/or patient-relation purposes.
  • wellness hub 431 is configured to identify one or more item 20 replacements, such as when an item 20 is unavailable, and/or such as when alternative items 20 may provide additional benefits (e.g., additional health, cost, and/or availability benefits) to patient P.
  • Wellness hub 431 can comprise an algorithm 415 configured to analyze one, two, or more items 20 and to determine an optimized alternative food product. For example, system 10 can recommend patient P replace standard bologna with turkey bologna. System 10 can also assign contextual data to identify item 20 replacements, such as to expand the relevancy of item 20 replacements.
  • system 10 can assign bologna as “lunch meat”, “sandwich ingredient”, and/or “processed sliced meat”, and thereby provide clarity to which replacement items 20 fulfill the contextual data of the item 20 to be replaced.
  • system 10 can identify yogurt as a relevant replacement for cereal.
  • system 10 can be configured to avoid recommending a meat product (e.g., chicken or beef) as a relevant replacement for a fruit or vegetable (e.g., avocado).
  • wellness hub 431 audibly and/or visually collects nutritional, fitness, and/or other health goals of patient P.
  • System 10 can be configured to identify health goals from commentary provided passively and/or actively by patient P, and/or through an Al device interface and/or another commercial device interface (e.g., Alexa, Siri).
  • System 10 can receive passive commentary from patient P via a microphone (e.g., a microphone within patient device 100 comprising a smartphone of patient P).
  • the microphone can record audio used by system 10 to recognize patient P orders a particular food item (e.g., a flatbread, gluten-free pizza) at a restaurant, and during consumption, patient P audibly indicates that food item (e.g., the flatbread, gluten-free pizza) is satisfactory (e.g., a recording similar to “this pizza is really good”).
  • System 10 can prompt patient P to add that food item to a “favorites database” (e.g., the information is stored as part of patient data 101).
  • wellness hub 431 is configured to allow system 10 and/or clinician C to recommend various “types” of items 20 for consumption by patient P.
  • Wellness hub 431 can further identify a source of the recommended food products.
  • System 10 can receive dietary input from clinician C and further display a list of available items 20 that meet the criteria (e.g., items that are also within a current or future geographical region of patient P).
  • System 10 can be configured to allow clinician C to select one, two, or more items 20 they recommend for patient P to consume.
  • System 10 can present the recommended items 20 by clinician C to patient P and provide one or more methods to order the recommended items 20.
  • system 10 can identify items 20 available via a wholesale distributor (e.g., Sysco, Costco, and the like) and/or via one or more food delivery services (e.g., Instacart, Uber Eats, Door Dash, and/or other similar delivery services).
  • a wholesale distributor e.g., Sysco, Costco, and the like
  • one or more food delivery services e.g., Instacart, Uber Eats, Door Dash, and/or other similar delivery services.
  • wellness hub 431 collaborates with a government-based program (e.g., SNAP) to provide healthy eating criteria to patient P.
  • Wellness hub 431 can be configured to distribute government-based funding, such as funding that is based on the healthy eating criteria.
  • Wellness hub 431 can interact with one, two, or more devices to review data (e.g., food intake, exercise, diet, sleep, and/or other patient data) to determine a reward for patient P.
  • wellness hub 431 incorporates a reward-based system that allows patient P to earn “points” based on an allowance of overall healthy versus unhealthy choices made by the patient P.
  • System 10 can assign points to items 20 based on a health scale (e.g., a scale of healthy vs unhealthy for the particular patient P).
  • System 10 can assign points to various items 20 based on a rating (e.g., a health rating for the particular patient P).
  • System 10 can assign points to items 20 based on their relative contribution to the nutritional, fitness, and/or other health goals of patient P, for example, if the item 20 is beneficial to a health goal, the item 20 is assigned positive points, and vice versa.
  • Nutritional, fitness, and/or other health goals can include target parameters for blood pressure, fat intake, cholesterol intake and/or cholesterol level, sodium intake, and/or other relevant parameters.
  • System 10 can assign a weight of importance to each health goal parameter, for example, the primary goal for patient P can be reducing their sodium intake, whereas a secondary goal can be reducing their cholesterol intake and/or their cholesterol level.
  • System 10 can be configured to predict the health impact on a set of parameters as a result of item 20 consumption by patient P.
  • system 10 can compare each parameter, such as the weights of each parameter, such as to compute a new weighted sum of change to determine if it is a positive or negative change.
  • the parameter can be also measured against a target window, such as to prevent or at least limit (“prevent” or “limit” herein) the rewarding of excessive behavior.
  • a particular substance e.g., potassium
  • eating a particular item 20 including the particular substance is rated as “Good” (e.g., patient P notified of the positive rating, and points can be awarded and/or other patient-motivating feedback can be provided if ingestion occurs)
  • eating the same particular substance might be rated as “BAD” (e.g., patient P notified of the negative rating, and points subtracted and/or other patient demotivation delivered if ingestion occurs)
  • the level of that substance in patient P is already above a desired level (e.g., to avoid increasing the level to a dangerous or otherwise undesired level).
  • system 10 can temporarily modify the health goals of patient P to encourage the increase in the particular vitamin, supplement, or food product, or medication (e.g., Vitamin D and Zinc).
  • System 10 can prioritize temporary health goals over other health goals (e.g., pre-defined and/or other previous health goals).
  • System 10 can include preset variables (e.g., ailments), such as Covid- 19 and Influenza, and such presets can further include target values for new target health goals (e.g., temporary health goals for the time period in which the adverse medical condition is present in the patient P).
  • target values for new target health goals e.g., temporary health goals for the time period in which the adverse medical condition is present in the patient P.
  • a user U can engage the particular adverse medical condition preset (e.g., Covid- 19 preset) and system 10 can be configured to automatically update the health goals accordingly.
  • wellness hub 431 is configured to provide one or more recommendations based on budget and/or other financial data of patient P (e.g., as provided by patient P), such as to provide item 20 recommendations that satisfy the nutritional, fitness, and/or other health goals, as well as financial constraints and/or other financial requirements or desires of patient P.
  • wellness hub 431 is configured to utilize patient data 101 comprising family-based data, such as to provide recommendations to patient P without exposing the health information of a particular family member from which the data was collected (i.e. to satisfy medical privacy guidelines, such as HIPAA).
  • wellness hub 431 is configured to utilize family-based data to provide recommendations for one or more items 20 that are provided to achieve the health goals of a patient P comprising multiple members of a family (e.g., items 20 that meet the collective requirements of multiple patients).
  • wellness hub 431 is configured to monitor a set of parameters that enable system 10 to automatically generate tentative meeting times available for clinician C.
  • system 10 can be configured to prompt a patient P, such as to identify a time of day that is convenient for both the clinician and patient to meet.
  • wellness hub 431 is configured to “illuminate” one or more items 20 that each satisfy one, two, or more health goals of patient P.
  • Wellness hub 431 can comprise a digital screen that scrolls along a line of items 20 and indicates, such as via highlighting, font change, background change, an audible signal, and/or other illumination, what patient P should or should not consider.
  • wellness hub 431 is configured to provide one or more recommendations of restaurants, food products (items 20), businesses (e.g., restaurants, grocery stores, and/or other suppliers S), and/or social connections to patient P, whereby the recommendations relate to items 20 whose ingestion tend toward patient P achieving one or more nutritional, fitness, and/or other health goals of that patient P.
  • System 10 can be configured to interface with one or more social media platforms (e.g., Facebook, Twitter, and the like) of patient P, such that system 10 can obtain further individualized information about their preferences, health history, interests, and/or another relevant parameter.
  • social media platforms e.g., Facebook, Twitter, and the like
  • system 10 comprises a confirmation routine such that the patient can “approve” any data obtained from a social media platform prior to its use by system 10 (e.g., prior to the data being used by an algorithm of system 10 or used otherwise by system 10).
  • system 10 is configured to cross-reference the individualized information with social media communities (e.g., Facebook groups), such as to provide patient P with relevant connections to businesses, brands, social circles, and people.
  • social media communities e.g., Facebook groups
  • wellness hub 431 is configured to convert the dietary needs and/or other dietary plans of patient P into one or more “motivational collages” of items 20 that are designed (e.g., aesthetically inclined) to encourage the patient to consume the food product.
  • System 10 can be configured to review one or more of dietary plans; nutritional, fitness, and/or other health goals; food preferences; and/or body composition preferences of patient P, and further source images related to those preferences (e.g., and provide those images to the patient, such as via user interface 130 of device 100).
  • system 10 can be configured to similarly identify and/or collect motivational phrases to be provided to the patient.
  • System 10 can be configured to generate a collage based on the identified images, motivational phrases, or both.
  • Processing unit 410 can further comprise an application 416 comprising a meal planner 432, where planner 432 is configured to provide multiple “meal templates” to user U.
  • Meal planner 432 can provide a preview of items 20 included in a meal template, such as a description, images, and nutritional information of each food product.
  • Meal planner 432 can provide a video explanation for the preparation of a meal template and the associated food products.
  • Meal planner 432 can be configured to allow user U to select one, two, or more items 20 within a database and assign each item 20 to a “calendar template”.
  • the calendar template can include cells associated with day and time.
  • Meal planner 432 can allow user U to search for a food product, and to drag and drop item 20 into the desired cell. For example, user U can drag and drop a particular food product (e.g., oatmeal) as breakfast for each weekday at a particular time (e.g., 7am).
  • Each cell within the calendar of meal planner 432 can indicate the total calories, total carbohydrates, total fat, and/or other parameter level, of the items 20 (individually and collectively).
  • Each day within the meal planner 432 calendar can be dynamically coded (e.g., color-coded and/or otherwise graphically coded) based on one or more parameters (e.g., level of one or more parameters).
  • each comer of each cell can be coded to represent the level of individual nutritional values in an item 20 and/or meal including one or more items 20, such as a representation of the level of sodium, fat, protein, and/or other food parameter for that item 20 and/or meal.
  • Meal planner 432 can be configured to analyze and/or provide a summary of items 20 identified by system 10 as “POOR” or “BAD”, that were and/or will be consumed by patient P.
  • meal planner 432 can summarize the amount of fat, sodium, cholesterol, and/or other food parameters that patient P consumed and can further indicate levels that exceed a threshold (e.g., a predetermined threshold associated with patient P).
  • Meal planner 432 can comprise one, two, or more input components, such as a right-click menu and/or other trigger, such as to generate replacement item 20 recommendations, such as described hereinabove.
  • Meal planner 432 can be configured to assign colors or other graphical properties (e.g., generate a color-code) to one, two, or more cells within the calendar, the graphical properties correlating to item 20 choice assessments (e.g., “GOOD” or “BAD”), such as to indicate and/or suggest (“indicate” or “suggest” herein) which items 20 may need to be and/or should be replaced by patient P.
  • graphical properties e.g., generate a color-code
  • item 20 choice assessments e.g., “GOOD” or “BAD”
  • Meal planner 432 can be configured to automatically generate one, two, or more meal templates for a patient P, based on one or more nutritional, fitness, and/or other health goals of patient P.
  • patient P and/or a clinician C can input a target daily caloric intake, target daily fat intake, target daily carbohydrate intake, target daily protein intake, number of meals per day, and/or other food and/or patient ingestion parameter, and meal planner 432 can generate a meal template comprising one, two, or more items 20 that collectively satisfy one or more of the health goals.
  • Patient P can indicate one or more days for which they desire meal planner 432 to generate meal templates.
  • patient P can highlight one or more days for meal planner 432 to generate meal templates.
  • Meal planner 432 can include a “zoom capability” to allow patient P and/or clinician C to view the items 20 included within a single meal template and further allow patient P and/or clinician C to request a replacement food product for one or more items 20.
  • Meal planner 432 can generate a “shopping list” that includes the items 20 contained within one or more meal templates, such as meal templates generated for a time period (e.g., a single week).
  • Meal planner 432 can further populate a shopping cart via one, two, or more suppliers S to allow patient P to purchase the items 20 (e.g., purchase the items 20 online).
  • SHOPPING CART ANALYZER 433 can include a “zoom capability” to allow patient P and/or clinician C to view the items 20 included within a single meal template and further allow patient P and/or clinician C to request a replacement food product for one or more items 20.
  • Meal planner 432 can generate a “shopping list” that includes the items 20 contained within one or more meal templates, such as
  • Processing unit 410 can further comprise an application 416 comprising a shopping cart analyzer 433 configured to identify and/or recommend replacement items 20 for items included within user U shopping cart.
  • Shopping cart analyzer 433 can identify items 20 representing replacement food products that can be deemed as healthier alternatives.
  • Shopping cart analyzer 433 can enable patient P and/or clinician C to improve items 20 within a shopping cart and/or further align with the nutritional, fitness, and/or other health goals for patient P.
  • Shopping cart analyzer 433 can identify and/or recommend similar and/or alternative items 20 based on nutritional information and/or preferences of patient P.
  • Shopping cart analyzer 433 can identify and/or recommend similar and/or alternative items 20 based on one or more dietary restrictions of patient P.
  • Shopping cart analyzer 433 can identify and/or recommend similar or alternative items 20 based on one or more diet formats (e.g., keto, gluten-free, and/or other diet types). Shopping cart analyzer 433 can identify and/or recommend similar and/or alternative items 20 based on price. Shopping cart analyzer 433 can be configured to provide a larger sale value to supplier S, such as by identifying and/or recommending items 20 that are more expensive (e.g., premium items 20).
  • diet formats e.g., keto, gluten-free, and/or other diet types.
  • Shopping cart analyzer 433 can identify and/or recommend similar and/or alternative items 20 based on price.
  • Shopping cart analyzer 433 can be configured to provide a larger sale value to supplier S, such as by identifying and/or recommending items 20 that are more expensive (e.g., premium items 20).
  • Shopping cart analyzer 433 can include a “one-step button” configured to automatically implement one, two, or more adjustments (e.g., replacements) to items 20 within a patient P or clinician C shopping cart.
  • Shopping cart analyzer 433 can automatically replace items 20 identified as “POOR” or “BAD” with healthier, comparable, alternative food products.
  • shopping cart analyzer 433 can automatically replace fried potato chips with baked potato chips, replace pork bacon with turkey bacon, replace full-sodium cold cuts with reduced-sodium cold-cuts, and/or replace any product deemed undesirable for patient P with a desired food product.
  • Shopping cart analyzer 433 can be configured to support replacements of one or more items 20 with products that satisfy one or more diet formats.
  • shopping cart analyzer 433 can automatically replace a high carbohydrate item 20 with a reduced-carbohydrate food product.
  • Shopping cart analyzer 433 can analyze and/or provide a summary of the nutritional benefits attributed to the replacement item 20 food products.
  • shopping cart analyzer 433 can indicate to patient P or clinician C a set of replacement items 20 that reduced total carbohydrates by a certain percentage (e.g., reduced 18%) and increased dietary fiber a certain percentage (e.g., increased by 11%) as compared to the originally selected items 20.
  • Shopping cart analyzer 433 can include an algorithm 443 configured to analyze an item 20, such as to analyze the differences between two or more item 20 food products, such as a comparison performed in multiple dimensions.
  • Algorithm 443 can utilize finite logic to compare the food products, for example, “item 20 A contains less fat than item 20 B”. Algorithm 443 can utilize linear algebra using dot-product matrix math to compare the food products. Algorithm 443 can be configured to recommend various items 20 for selection based on the health goals, financial goals, and/or other goals of patient P (e.g. at least the health goals of patient P).
  • Shopping cart analyzer 433 can be configured to interface directly with supplier S.
  • Shopping cart analyzer 433 can be configured to interface with supplier S via a browser plugin.
  • Patient P and/or clinician C can be shopping via a website hosted by supplier S, and system 10 can be configured such that shopping cart analyzer 433 is accessible from a “sidebar”.
  • Shopping cart analyzer 433 can parse the website of supplier S and can extract information to feed to the analysis portion of an algorithm of system 10.
  • Shopping cart analyzer 433 can be configured to identify and/or recommend replacement non-food-based items 20 for items included within user U shopping cart.
  • clinician C may recommend patient P avoid particular chemicals found in cleaning products (e.g., latex, propylene glycol, carcinogens, and/or other potentially undesired chemicals and/or undesired materials that can be found in cleaning products and/or other nonfood-based items 20).
  • System 10 can comprise a dynamically adaptable persuasive selling system, “DAPSS”.
  • DAPSS dynamically adaptable persuasive selling system
  • abstract containers for use on websites can hold text, images, video, and/or a call to action, and can have 0, 1, or more persuasive attributes.
  • System 10 can be configured to measure all user interaction, associating actions with each container’s persuasive configuration.
  • System 10 can be configured to arrange future containers to “push” the same persuasive configurations on the user.
  • Each user’s experience may be a unique configuration.
  • System 10 can be configured to arrange a particular percentage (e.g., 80%) of the containers in a method in which the user is most responsive to, and the remaining percentage (e.g., the other 20%) can be arranged to use different methods, for example as a test.
  • System 10 can be configured such that preferences can be set (e.g. by the manufacturer of system 10) to choose a set of persuasive rules to be applied to the user’s experience.
  • System 10 can be configured to bias the use of some persuasive rules more than others, and the bias can be a user-defined parameter.
  • System 10 can be configured to leave cookies and/or local-storage and save data to the global DAPSS, such that when a user makes an initial visit to a site they had never visited, they get the DAPSS data to configure the user’s first experience to implement all of the proven, historical DAPSS data.
  • the DAPSS instructions and/or data can be stored on server 400 (e.g. a server of the manufacturer of system 10), and can be implemented into a client (e.g., e-commerce store) website, such as via remote java scripts.
  • server 400 e.g. a server of the manufacturer of system 10
  • client e.g., e-commerce store
  • One or more user interfaces of system 10, as described herein, can have one or more interface parameters (e.g. graphical, audio, and/or tactile parameters, such as fonts, layout, upscale tactics, verbiage, button and/or background colors, audible tones, songs, and/or accents, and/or other user interface parameters) that are adjusted (e.g., dynamically adjusted) based on the way a user U responds to that particular parameter when presented to user U.
  • the user’s response can be analyzed based on: time (e.g., total time) viewing a particular screen (e.g. a particular webpage or other user-provided screen); checkout rate (e.g.
  • system 10 can adjust the location of one or more viewable components, such as the location of a sidebar between a location at the top of a screen and the side of a screen, based on an analysis performed by system 10 (e.g. via an included DAPSS), such as a location change that is determined based on use by a particular user (e.g. a particular patient P, clinician C, and/or suppler S).
  • system 10 e.g., an included DAPSS
  • graphical parameters e.g. background colors, sidebar locations, and/or other user interface parameter
  • Processing unit 410 can further comprise algorithm 415 configured to manipulate supplier S data to satisfy user U preferences.
  • Algorithm 415 can utilize data related to supplier S (e.g., data supplied by supplier S, data related to supplier S logistics and/or products, and/or other supplier S data).
  • Algorithm 415 can utilize user U preferences (e.g. patient P and/or clinician C preferences), such as preferences stored as a “cookie”.
  • Algorithm 415 can be configured to manipulate data of supplier S without the supplier providing business logic to affect the manipulation.
  • the United States Department of Agriculture (USDA) website provides a large quantity of data about food and nutrition, but such data is generally subjected to limited features for organization according to user preferences.
  • Algorithm 415 can enable a user U to define which data within the USDA website is of particular personal importance, such that algorithm 415 can automatically manipulate the data to satisfy the preferences of the particular user U.
  • user U can indicate an allergy (e.g. a peanut allergy) in their preferences.
  • Algorithm 415 can automatically manipulate (e.g., omit) any items 20 that contain that particular allergic material from being displayed on the website of supplier S.
  • system 10 comprises an algorithm that is configured to monitor one or more ailments and/or other adverse medical conditions of patient P over time.
  • system 10 comprises an algorithm that is configured to control access and/or personal distribution of medicine or other products to patient P, such as when system 10 includes a patient peripheral 180 that comprises a pill lockbox whose lock status is controlled by system 10.
  • System 10 via one or more algorithms of system 10 described herein, can be configured to change the lock status of the pillbox based on an analysis of patient data 101 (e.g., patient data 101 that includes data that has been entered and/or updated within the last one day, one week, and/or 1 month).
  • system 10 includes a patient peripheral 180 that comprises a vitamin dispenser.
  • the vitamin dispenser can comprise an assembly configured to grind solid material (e.g., solid vitamins), such as to add it into a beverage for patient P to ingest.
  • the assembly can be configured to add one or more liquids (e.g., liquid vitamins) into a beverage for patient P to ingest.
  • System 10 via one or more algorithms of system 10 described herein, can be configured to operate a patient peripheral 180 (e.g., a patient peripheral 180 comprising a vitamin dispenser) based on an analysis of patient data 101 (e.g., patient data 101 that includes data that has been entered and/or updated within the last one day, one week, and/or 1 month).
  • system 10 includes a patient peripheral 180 that comprises a vitamin and/or drink separator.
  • the separator can comprise an assembly that is configured to prevent oxidation of a material (e.g., vitamins) that are contained within a beverage.
  • the assembly can be configured such that when a beverage bottle is opened (e.g., first opened), liquid contents and/or vitamins contents are introduced (e.g., by the assembly).
  • a twist of the beverage bottle’s cap can be configured to release the vitamins into the liquid content.
  • System 10 via one or more algorithms of system 10 described herein, can be configured to operate a patient peripheral 180 (e.g., a patient peripheral 180 comprising a vitamin and drink separator) based on an analysis of patient data 101 (e.g., patient data 101 that includes data that has been entered and/or updated within the last one day, one week, and/or 1 month).
  • a patient peripheral 180 e.g., a patient peripheral 180 comprising a vitamin and drink separator
  • patient data 101 e.g., patient data 101 that includes data that has been entered and/or updated within the last one day, one week, and/or 1 month.
  • system 10 comprises an algorithm that is configured to produce recommendations based on a patient P parameter (e.g., and stored as patient data 101), such as current health profile, health goals, financial goals and/or other goals, current medications, previously ingested food products (e.g. recently ingested food products), and/or other personal information or configurable items.
  • System 10 can be configured to monetize a transaction or other event, such as by providing alternative brand suggestions that “satisfy” (e.g., are in line with achieving) the same, or better, nutritional, fitness, and/or other health goals of patient P.
  • system 10 comprises a patient peripheral 180, a functional element 199, and/or a user interface (e.g., user interface 130) comprising a display (e.g. a projector and/or a screen) and/or a camera configured to visualize a plate onto which a meal could be placed, and to utilize data to overlay how much volume of each item 20 should take up on the plate.
  • a green overlay for vegetables can comprise about a third of the plate
  • a red overlay for fruits can comprise about another third of the plate
  • a blue overlay for meats can comprise about another third of the plate.
  • the overlays can change proportions based on individual nutrition goals.
  • System 10 can comprise an algorithm (e.g., algorithm 415) that is configured to utilize image recognition to map what items 20 are on the plate, and the algorithm can further determine the recommended volume of each item 20 based on information from a camera (e.g. multi -camera information).
  • patient device 100 comprises an augmented reality device (e.g., glasses or a headset configured to present an augmented reality to the patient) that presents the overlay as a visual augmentation to the patient.
  • system 10 is configured such that certain items 20 are “pre- loaded items 20” in a patient peripheral 180 comprising a food storage device, and system 10 can be configured to provide instructions as to which item 20 to consume, and/or how to consume them (e.g. when and/or at what quantity). For example, if patient P is experiencing low blood sugar, system 10 (e.g., when determined by algorithm 415 of system 10) can be configured to instruct patient P to eat the “granola bar in compartment C3”.
  • system 10 comprises a “heartbeat” communication protocol that timecodes and/or encodes (e.g. encodes using a security protocol) messages about the physical performance of patient P and can attach other health and/or other patient P information to the message. These messages can be performed on a routine basis, such as to mimic a heartbeat.
  • a “heartbeat” communication protocol that timecodes and/or encodes (e.g. encodes using a security protocol) messages about the physical performance of patient P and can attach other health and/or other patient P information to the message. These messages can be performed on a routine basis, such as to mimic a heartbeat.
  • system 10 comprises an algorithm (e.g., algorithm 415) configured to provide a “cafeteria tracker”.
  • system 10 can be used in a cafeteria, where subjects eating in the cafeteria (e.g. patients P comprising students, company workers, and/or other subjects that eat in a cafeteria), each have a patient device 100 that allows system 10 to track which food product items 20 are selected by each subject (e.g. each patient P, such as via a functional element comprising a camera, a food tray comprising a tracking device, or other arrangement to link a patient P with one or more food products selected for ingestion).
  • subjects eating in the cafeteria e.g. patients P comprising students, company workers, and/or other subjects that eat in a cafeteria
  • each patient device 100 that allows system 10 to track which food product items 20 are selected by each subject (e.g. each patient P, such as via a functional element comprising a camera, a food tray comprising a tracking device, or other arrangement to link a
  • the patients P comprise students, and a parent or other guardian of each patient P is provided the food product item selections made by that patient P.
  • system 10 and/or its components are configured, constructed, and arranged similar to the similar components in co-pending United States Patent Application Serial Number 17/299,433, entitled “Health Management System”, filed on June 3, 2021.
  • GANs GENERATIVE ADVERSARIAL NETWORKS
  • processing unit 410 can further comprise one or more Generative Adversarial Networks, GANs, which can be configured to receive training data, reduce the training data down to abstract concepts, and then generate and/or validate new solutions in the same multidimensional space.
  • GANs Generative Adversarial Networks
  • a GANs of system 10 can be configured to identify one, two, or more items 20 currently available to patient P (e.g., items 20 within patient pantry 40) and can further suggest one, two, or more “recipes” that incorporate the identified items 20.
  • a GANs of system 10 can be configured to identify an item 20 and can further suggest one, two, or more alternatives for the identified item 20, such as a healthier alternative item 20.
  • a GANs of system 10 can suggest one, two, or more medicinal items 20 combinations to assist with patients having one or more comprehensive lists of medicines and interactions.
  • systemlO comprises patient peripheral 180’ comprising smart glasses (e.g. Ray -Ban stories and/or other smart glasses) that can be configured to generate and/or implement augmented reality to provide visual guidance to patient P during the use of system 10.
  • Patient peripheral 180’ comprising smart glasses can be configured to provide visual guidance based on the nutritional requirements and/or other requirements and/or desires of patient P.
  • Patient peripheral 180’ comprising smart glasses can be configured to highlight (e.g. in images provided by peripheral 180’) items 20 that should, or should not, be consumed by patient P.
  • peripheral 180’ can overlay an “X” or other indicator over items 20 that should not be consumed by patient P.
  • patient peripheral 180’ can comprise smart glasses that are configured to estimate the nutritional information (e.g., calorie content), such as to display the nutritional information of items 20 when viewed by user U.
  • a peripheral 180’ comprising smart glasses can be configured to indicate personalized allergy warnings for patient P.
  • a peripheral 180’ comprising smart glasses can be configured to identify an item 20 being viewed by patient P and can further display any notes (e.g. as received from clinician C) with regard to that particular item 20. For example, if patient P is viewing an item 20 comprising a medication, peripheral 180’ can display a contraindicating message similar to “you’ve already taken that medication today; it is only prescribed once a day”.
  • peripheral 180’ can display a contraindicating message similar to “put the whiskey down, it will negatively interact with your temozolomide”.
  • a peripheral 180’ can comprise smart glasses that are configured to identify and log one or more items 20 (e.g. all or at least a majority) consumed by patient P (e.g. over a time period).
  • system 10 are configured as a blockchain system.
  • system 10 data can be shared across the chain, such as to provide superior security features when compared to any centralized data store.
  • one or more devices of system 10 described herein are configured to monitor the activity level of patient P, for example, if patient P is awake or asleep, and/or active or sedentary.
  • one or more algorithms of system 10 consider the activity level of patient P when determining information related to patient P, such as personalized data 99.
  • a user U such as patient P
  • one or more devices of system 10 described herein are configured to monitor the location and/or environment of patient P, for example the geographic location of patient P and/or the physical environment surrounding patient P, such as when patient P is on a plane.
  • one or more algorithms of system 10 consider the location of patient P when determining information related to patient P, such as personalized data 99.
  • a user U such as patient P
  • can input future location data such as a planned trip where patient P will be on a plane, and/or patient P will be visiting a location at a different altitude than the usual environment of patient P, such as when patient P plans to visit Denver (e.g., the mile high city).
  • System 10 can determine personalized data 99 based on the current location and/or future location data, such as personalized data 99 including recommendations for altitude preparations (e.g., breathing exercises prior to the trip, and/or a reminder to bring asthma medication).
  • one or more algorithms of system 10 is configured to analyze vendor information (e.g., information of supplier S) that is input by patient P.
  • vendor information e.g., information of supplier S
  • patient P can take a picture (e.g., with patient device 100) of a menu at a restaurant, and system 10 can analyze the menu data, and determine one or more recommendations for patient P (e.g., one or more recommendations based on personalized data 99, as described herein).
  • system 10 monitors one or more items that are ingested by patient P (e.g., items 20 that are recommended by system 10 to patient P, or other items ingested by patient P), such as food, medications, and/or vitamins ingested by patient P throughout a time period, such as throughout a day.
  • System 10 can provide a visual indicator (e.g., such as via GUI 135 of patient device 100) of the levels of ingested items, such as the amount of nutrients, calories, number of items, dietary “points” such as Weight Watchers points, or other metrics, such as metrics related to a recommended value (e.g., a recommended daily value) for patient P, such as a recommended value determined by system 10 based on personalized data 99.
  • a recommended value e.g., a recommended daily value
  • system 10 is configured to alert patient P (e.g., via patient device 100) if a recommended value of an item is exceeded, and/or would be exceeded if an item were ingested. For example, if system 10 identified patient P is planning to eat a cupcake (e.g., when a camera of system 10 records a video of patient P removing the paper from a cupcake, and algorithm 415 of system 10 predicts the intent of patient P based on the recorded video), an alert can be presented if the cupcake will exceed a daily allotment of sugar for patient P.
  • one or more algorithms of system 10 are configured to process conflicting medical information or other health information.
  • system 10 can process information from various sources (e.g., various medical journals), and generate an analysis of conflicting information.
  • a user U e.g., a clinician C and/or patient P
  • which information is to be “rejected” by system 10 e.g., which information is to be referenced in one or more decision making processes of system 10).
  • one or more algorithms of system 10 comprise one or more biases, such as biases that produce a weighting metric for information based on various factors, such as the quantity of supporting information previously analyzed by system 10, the credibility of the source of the information, and/or one or more preferences of a user U of system 10.
  • system 10 is biased toward the suggestion of avoiding particular items 20, and/or system 10 is biased away from the suggestion of ingesting a particular item 20. For example, if the medical community is undecided (e.g., as determined by system 10 based on the available information processed by system 10) on the benefits of a supplement (e.g., turmeric), system 10 can be biased towards not suggesting that item.
  • a supplement e.g., turmeric
  • system 10 can be biased toward avoiding positive or negative suggestions of an item 20 if there is insufficient information available to system 10 to generate a suggestion.
  • system 10 is configured to combine the protocols of two or more diet plans, such as to create a diet plan specific for a patient P (e.g., when patient P is interested in two or more methodologies, such as the carnivore diet and a keto diet).
  • a first diet excludes particular foods (e.g. items 20)
  • system 10 can select foods from a second diet that are not excluded by the first diet to suggest various items 20 to patient P.
  • system 10 is configured to identify one or more ingredient interactions and/or redundancies in the diet of patient P. For example, when ordering food (e.g., one or more items 20) and/or a meal (e.g., when patient P orders an item 20 via system 10), system 10 can identify if the food may have a negative reaction to something recently ingested by patient P. As another example, system 10 can identify that a supplement is not needed (e.g., iron supplements) if other items 20 in a planned diet for patient P (e.g., a meal plan determined and provided by system 10) are rich in that supplement (e.g., if the meal plan calls for spinach which is rich in iron).
  • a supplement e.g., iron supplements
  • a user U such as patient P
  • System 10 can be configured to provide an analysis of the information (e.g., based on other information previously analyzed by system 10), and/or can request an analysis of the information from another user, such as a clinician C.
  • system 10 is configured to generate a menu for an event based on the personalized data of two or more attendees (e.g., two or more patients P) of the event. For example, for a child’s birthday party, a user U can send digital invitations (e.g., via patient device 100) to the invitees of the party to link the personalized data 99 of the invitees, and/or for the invitees to fill out information, such as allergy information.
  • System 10 can analyze the personalized data of each of the invitees and prepare a menu for the event that meets the health needs of each (e.g., the menu can avoid allergens such as peanuts).
  • System 10 can also be configured to warn a user (e.g., patient P) if one or more of the items on the menu for an event contain an undesired ingredient for the patient P, such as an allergen.
  • system 10 can warn a user to avoid the cookies that are being served which contain peanuts.
  • an application e.g., application 116 of system 10 comprises an invite service and/or a hosting service configured to allow a first user U to invite guests (e.g., other users U and/or individuals who are not users of system 10) to an event, and to assist in the planning of the event based on the personalized data of the guests.
  • system 10 comprises a “sick mode” in which one or more of the functions of system 10 is altered based on a temporary health condition of patient P. For example, if patient P is diagnosed with the flu (and patient P and/or clinician C of patient P report the diagnosis to system 10), system 10 can be configured to temporarily suggest items 20 to user P based on the diagnosis. For example, system 10 can suggest soup for a sick patient. In some embodiments, system 10 is configured to base one or more item 20 suggestions on a calendar (e.g., a calendar of events provided by user U) such as to suggest items 20 to treat and/or mitigate allergies during allergy season.
  • a calendar e.g., a calendar of events provided by user U
  • an application of system 10 is configured as a “group ordering” tool.
  • system 10 can allow a group of users to place an order of items 20 (e.g., a lunch order at a conference from a local restaurant, such as a restaurant that is a supplier S of system 10 that has provided a menu to system 10).
  • each user U can indicate the items 20 they wish to order from that user’s device (e.g., patient device 100).
  • System 10 can be configured to aggregate the order for the group.
  • the order can then be provided to a single user (e.g., a user who will order the group’s lunch), and/or system 10 can provide the order to supplier S (e.g., the restaurant from which the users selected their meals based on the menu provided to system 10).
  • supplier S e.g., the restaurant from which the users selected their meals based on the menu provided to system 10.
  • one or more algorithms of system 10 are configured to monitor user activity while user U (e.g., patient P) uses various third-party applications (e.g., third-party app 116’).
  • System 10 can perform one or more actions and/or initiate one or more processes based on activity performed using various third-party applications. For example, system 10 can monitor food purchased via third-party applications, and incorporate the purchased food (e.g., items 20) in a meal plan for the user.
  • System 10 can add reminders to a calendar of user U, such as reminders of expiration dates or predicted dates that various items 20 (e.g., fresh fruit) should be consumed by (e.g., various items purchased via system 10 and/or via a third-party application).
  • system 10 is configured to monitor user activity on third-party applications and to provide a warning configured to dissuade user U from purchasing various items, such as unhealthy food or frivolous items (e.g., to help user U save money).
  • system 10 is configured to place a phone call on behalf of user U.
  • user U can place a food order from a supplier (e.g., a supplier not digitally connected to system 10, where system 10 can automatically place the food order), and system 10 can place a call to the supplier (e.g., via voice synthesizer, such as an Al voice synthesizer) to place the order for user U.
  • a supplier e.g., a supplier not digitally connected to system 10, where system 10 can automatically place the food order
  • system 10 can place a call to the supplier (e.g., via voice synthesizer, such as an Al voice synthesizer) to place the order for user U.
  • voice synthesizer such as an Al voice synthesizer
  • system 10 is configured to provide a graphical overlay on one or more third-party applications, such as online grocery ordering applications.
  • System 10 can display information to user U, without impeding the functionality of the third-party application.
  • system 10 provides information via an overlay relating to the health of the user, and/or information regarding how an item presented by the third-party application relates to the health of the user.
  • system 10 can overlay a “grade” (e.g., A-F) based on how healthy the displayed product is for the user based on the user’s personalized data 99.
  • system 10 is configured to alter how the information of a third-party application is displayed to the user.
  • system 10 can sort information (e.g., a list of products) based on the user’s personalized data.
  • system 10 is configured to provide an overlay on a digital menu, such as a menu accessed via a QR code at a restaurant (e.g., a restaurant that is not a supplier S of system 10).
  • one or more algorithms of system 10 are biased to assume a standard value, such as when more accurate information is not available.
  • system 10 can be biased to assume a standard calorie intake or a standard amount of daily exercise when analyzing user data (e.g., analyzing patient data 101 to determine a meal plan).
  • system 10 is configured to update a plan (e.g., a meal plan) based on real time feedback from the user. For example, if the user forgets to take a multivitamin and/or misses breakfast, system 10 can update the meals for the remainder of the day, such as to include more vitamin rich foods, or to increase the macro nutrient intake levels to reach a particular goal.
  • a plan e.g., a meal plan
  • system 10 is configured to group various items 20, such as to order a group of items, and/or to record a group of items as ingested.
  • system 10 can store a group of ingredients as a meal, such that the user can report to system 10 that they ingested a meal (e.g., a chicken Caesar salad), and system 10 can record that meal as the items 20 included in that meal (such as lettuce, chicken, and Caesar dressing).
  • system 10 is configured to generate one or more outputs that are based on local events (e.g., based on “breaking news”). For example, in the event of an outbreak of nuclear war, system 10 can recommend iodine or other supplements. In the event of forest fires or other natural or unnatural pollutants that may temporarily affect the user’s environment, system 10 can make recommendations to minimize the effect of the pollutants on the healthy lifestyle of the patient (e.g., system 10 can suggest a treadmill exercise to replace a planned outdoor run if the outdoor air quality is expected to be poor).
  • system 10 is configured to analyze user activity to determine one or more patterns, and/or to predict future needs (e.g., what items 20 user U may need).
  • An algorithm of system 10 can comprise an artificial intelligence algorithm (e.g., Al algorithm 415AI described herein) configured to analyze data collected by system 10 to determine one or more user patterns.
  • system 10 is configured to facilitate a study, such as a clinical study.
  • Patients P and/or clinicians C can provide data to system 10, such that system 10 can automatically analyze and/or be used to help an investigator analyze the effect of an item or activity (e.g., a medication, a food, a supplement, or an activity such as meditation or exercise), such as to perform a double-blind, controlled study.
  • system 10 is configured to implement a study protocol, such that the patients P and clinicians C are “blinded”, while system 10 is configured as an “unblinded” entity in the study.
  • system 10 is configured to “nudge” a user U, for example, when system 10 sends a message or other notification to user U encouraging the user to eat a suggested meal and/or to exercise.
  • System 10 can provide positive reinforcement to a user U when a positive action (e.g., performing an exercise routine or reaching a goal) is taken by the user.
  • system 10 is configured to interface with an artificial intelligence, such as a general artificial intelligence (e.g., an artificial intelligence trained and/or operated by a third-party, such as OpenAI, Google, or Microsoft).
  • an artificial intelligence such as ChatGPT
  • Algorithm 415 of system 10 can be configured to query an artificial intelligence, such as ChatGPT, by providing a query, patient information, and/or nutritional information.
  • Algorithm 415 can be configured to intake one or more responses from the artificial intelligence, such as to process the response, and provide information to a user U, such as patient P.
  • Algorithm 415 can be configured as a “wrapper” for an artificial intelligence, such as when algorithm 415 is configured to format, pre-process, combine, structure, and/or aggregate one or more pieces of information into a format that can be input to the artificial intelligence (e.g., input as a query such that the artificial intelligence provides a desired output).
  • algorithm 415 is configured to format, pre-process, combine, structure, and/or aggregate one or more pieces of information into a format that can be input to the artificial intelligence (e.g., input as a query such that the artificial intelligence provides a desired output).
  • patient device 100 is configured to record an expression of patient P, such as a facial expression, a verbal expression, an expression of body language, and/or another verbal or non-verbal expression.
  • System 10 can be configured, via algorithm 415, to generate one or more signal metrics based on the recorded expression.
  • algorithm 415 is configured to determine an output based on a weighted combination of two or more of the signal metrics, and to provide feedback to a user U (e.g., patient P and/or clinician C) based on the output.
  • patient device 100 is configured as a virtual reality and/or an augmented reality device, such as a wearable device configured to present images to the patient, such as images representing a virtual world and/or images representing augmentations to the physical world.
  • patient device 100 is configured to display images to the patient without otherwise obstructing the view of the patient (e.g., via a transparent display).
  • patient device 100 can be configured to record the view of the patient (e.g., with a video recording element) and display an augmented view of the environment to the patient (e.g., when patient device 100 otherwise blocks the view of the patient’s surroundings).
  • Patient device 100 can be configured to continuously or semi -continuously (e.g., while patient device 100 is in use and/or being worn by the patient) record visual, audio, and/or other information relating to the environment surrounding patient P.
  • System 10 can be configured to analyze the recorded information, such as via algorithm 415, such as to determine which items 20 are ingested by patient P.
  • patient device 100 is configured to display nutritional or other information relating to an item 20 in an augmented reality manner (e.g., as a virtual overlay presented to patient P).
  • Patient device 100 can be configured to block or otherwise censor information from a user, such as to help a patient make healthy decisions (e.g., healthy eating decisions), for example by “hiding” unhealthy items 20 (e.g., cookies) with an opaque augmented reality overlay, such as when the user (e.g., patient P) is browsing for food in a pantry and/or reviewing a menu.
  • healthy decisions e.g., healthy eating decisions
  • opaque augmented reality overlay e.g., such as when the user (e.g., patient P) is browsing for food in a pantry and/or reviewing a menu.

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • Biomedical Technology (AREA)
  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
  • Pathology (AREA)
  • Epidemiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)

Abstract

L'invention concerne un système de gestion de style de vie d'un patient. Le système comprend un dispositif patient ayant une interface utilisateur, et le dispositif patient reçoit des données personnalisées de patient provenant du patient. Le système peut en outre comprendre une unité de traitement qui reçoit des informations provenant du dispositif de patient et comprend : un module de mémoire destiné à stocker au moins des informations de patient et des instructions utilisées par l'unité de traitement pour exécuter un algorithme. L'algorithme peut analyser les informations de patient et fournir une rétroaction au patient pour pousser le patient à adopter un mode de vie sain sur la base de l'analyse.
PCT/US2024/037525 2023-07-11 2024-07-11 Système de gestion de style de vie Pending WO2025015131A2 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US202363526062P 2023-07-11 2023-07-11
US63/526,062 2023-07-11

Publications (2)

Publication Number Publication Date
WO2025015131A2 true WO2025015131A2 (fr) 2025-01-16
WO2025015131A3 WO2025015131A3 (fr) 2025-04-10

Family

ID=94216359

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2024/037525 Pending WO2025015131A2 (fr) 2023-07-11 2024-07-11 Système de gestion de style de vie

Country Status (1)

Country Link
WO (1) WO2025015131A2 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20240086469A1 (en) * 2022-09-12 2024-03-14 ASG Technologies Group, Inc. dba ASG Technologies Systems for Redaction of Documents in a Web-Based Collaborative Platform

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12131661B2 (en) * 2019-10-03 2024-10-29 Willow Laboratories, Inc. Personalized health coaching system

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20240086469A1 (en) * 2022-09-12 2024-03-14 ASG Technologies Group, Inc. dba ASG Technologies Systems for Redaction of Documents in a Web-Based Collaborative Platform
US12437009B2 (en) * 2022-09-12 2025-10-07 Rocket Software Technologies, Inc. Systems for redaction of documents in a web-based collaborative platform

Also Published As

Publication number Publication date
WO2025015131A3 (fr) 2025-04-10

Similar Documents

Publication Publication Date Title
Hadi et al. Good vibrations: Consumer responses to technology-mediated haptic feedback
Watson et al. Digital healthcare in COPD management: a narrative review on the advantages, pitfalls, and need for further research
US10231622B2 (en) Systems, devices, and methods for analyzing and enhancing patient health
US20250378967A1 (en) Performing mapping operations to perform an intervention
US10170016B2 (en) Comprehensive management of human health
US11211156B2 (en) Digital therapeutic systems and methods
CN104471597B (zh) 用于患者保健计划管理的系统和方法
US20180004914A1 (en) Personal Health Advisor System
WO2020229705A1 (fr) Système et procédé de surveillance de santé à distance pour hôpitaux et villes
US20120129139A1 (en) Disease management system using personalized education, patient support community and telemonitoring
US20190006040A1 (en) Cognitive diabetic regulator
JP6360998B2 (ja) 健康情報処理装置
CN104704526A (zh) 健康信息处理装置、健康信息显示装置以及方法
CN106716425A (zh) 健康和保健管理方法及用于其实践的系统
Chen et al. A bitter pill to swallow? The consequences of patient evaluation in online health question-and-answer platforms
Patterson Contextual expectations of privacy in self-generated health information flows
US10628047B2 (en) System and method for minimizing computational resources when copying data for a well-being assessment and scoring
US20220392596A1 (en) System and Method for Treating Migraine and Headache Through a Digital Therapeutic
JP2015079466A (ja) 食事型センサ、センシング方法及び食品
KR20230168184A (ko) 처방된 장치 또는 서비스의 평가방법 및 평가장치
WO2025015131A2 (fr) Système de gestion de style de vie
Freedman Personalized Health Care and Artificial Intelligence Could Improve Your Life--at the Cost of Your Privacy; If you think Facebook and Google invade your privacy, imagine what hackers could do with a minute-to-minute log of your disease symptoms, behaviors, locations and even your appearance and conversations
Khan et al. Investigating health-aware smart-nudging with machine learning to help people pursue healthier eating-habits
Patterson et al. Context-dependent expectations of privacy in self-generated mobile health data
Portius Wish or Truth: Can Digital Interventions Stop the Obesity Crisis?