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WO2025068014A1 - Dispositif médical implantable et procédé de fonctionnement d'un dispositif médical implantable - Google Patents

Dispositif médical implantable et procédé de fonctionnement d'un dispositif médical implantable Download PDF

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Publication number
WO2025068014A1
WO2025068014A1 PCT/EP2024/076205 EP2024076205W WO2025068014A1 WO 2025068014 A1 WO2025068014 A1 WO 2025068014A1 EP 2024076205 W EP2024076205 W EP 2024076205W WO 2025068014 A1 WO2025068014 A1 WO 2025068014A1
Authority
WO
WIPO (PCT)
Prior art keywords
patient
medical device
implantable medical
respiratory activity
activity data
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/EP2024/076205
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English (en)
Inventor
R. Hollis Whittington
Dirk Muessig
Christopher S. De Voir
Xinlong Wang
Ravi Kiran Kondama Reddy
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.)
Biotronik SE and Co KG
Original Assignee
Biotronik SE and Co KG
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 Biotronik SE and Co KG filed Critical Biotronik SE and Co KG
Publication of WO2025068014A1 publication Critical patent/WO2025068014A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0031—Implanted circuitry
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
    • A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
    • A61B5/053—Measuring electrical impedance or conductance of a portion of the body
    • A61B5/0538—Measuring electrical impedance or conductance of a portion of the body invasively, e.g. using a catheter
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/08—Measuring devices for evaluating the respiratory organs
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/18—Applying electric currents by contact electrodes
    • A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/3605—Implantable neurostimulators for stimulating central or peripheral nerve system
    • A61N1/36128—Control systems
    • A61N1/36135—Control systems using physiological parameters
    • A61N1/3614—Control systems using physiological parameters based on impedance measurement
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/18—Applying electric currents by contact electrodes
    • A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/362—Heart stimulators
    • A61N1/365—Heart stimulators controlled by a physiological parameter, e.g. heart potential
    • A61N1/36514—Heart stimulators controlled by a physiological parameter, e.g. heart potential controlled by a physiological quantity other than heart potential, e.g. blood pressure
    • A61N1/36521—Heart stimulators controlled by a physiological parameter, e.g. heart potential controlled by a physiological quantity other than heart potential, e.g. blood pressure the parameter being derived from measurement of an electrical impedance

Definitions

  • Implantable medical device and method of operating an implantable medical device
  • the invention relates to an implantable medical device and to a computer-implemented method for operating an implantable medical device.
  • Implantable cardiac monitors have traditionally been utilized for syncope, detection of atrial fibrillation, and for diagnosis of palpitations.
  • the future of ICMs includes the assessment, monitoring, and management of heart failure, and other chronic conditions that benefit from long-term monitoring.
  • respiration is a key vital parameter, as lung function can be impacted by a failing heart and poor pulmonary function can also cause the failure of the heart, impact autonomic function or exacerbate existing HF.
  • Respiration rate throughout the day is also recognized as a predictive variable for HF and is utilized in worsening HF prediction algorithms in ICDs.
  • Such a device uses daily trends in respiration rate as one variable to define an HF index value. When the HF index exceeds a programmed threshold, the likelihood of an HF decompensation event is declared.
  • ICMs can in principle measure respiration in multiple ways, and the method for measuring respiration is secondary to this concept.
  • Methods include ECG amplitude modulation, heart rate modulation, impedance modulation, chest wall motion, and others.
  • respiration rate is recognized as valuable, interpretation of the parameter is complicated by the measurement conditions and the unpredictable nature of respiration. Respiration behavior is impacted by exercise, talking, concentration, posture, and other factors, making the determination of a single respiration rate difficult or of limited clinical value. It is therefore an object of the present invention to provide an improved implantable medical device capable of effectively monitoring a respiration activity of a patient.
  • the object is solved by a computer program having the features of claim 13 and by a computer-readable data carrier having the features of claim 14 and a method for treating a patient with the implantable medical device having the features of claim 15.
  • the present invention provides an implantable medical device, in particular a cardiac monitor and/or a neurostimulation device (e.g. a spinal cord stimulation device), comprising means for capturing respiratory activity data of a patient and/or calculating the respiratory activity data of the patient based on at least one medical parameter captured by the implantable medical device.
  • a cardiac monitor and/or a neurostimulation device e.g. a spinal cord stimulation device
  • the implantable medical device comprises means for triggering a storage of the captured and/or calculated respiratory activity data of the patient in response to fulfillment of a predetermined triggering event, wherein the respiratory activity data comprises a time series of the respiratory activity of the patient.
  • the present invention further provides a computer-implemented method for operating an implantable medical device, comprising capturing respiratory activity data of a patient and/or calculating the respiratory activity data of the patient based on at least one medical parameter captured by the implantable medical device.
  • the method furthermore comprises triggering a storage of the captured and/or calculated respiratory activity data of the patient in response to fulfillment of a predetermined triggering event, wherein the respiratory activity data comprises a time series of the respiratory activity of the patient.
  • the present invention provides a computer program with program code to perform the method according to the present invention when the computer program is executed on a computer.
  • the present invention provides data carrier containing program code of a computer program for performing the method according to the present invention when the computer program is executed on a computer.
  • the present invention provides a method for treating a patient with the implantable medical device of the present invention, wherein the implantable medical device is operated by the computer- implemented method of the present invention.
  • An idea of the present invention is to provide an implantable medical device capable of taking a snapshot of a respiratory activity of the patient. Having a time series or snapshot of the respiration activity enables a deeper assessment of the respiratory activity and also allows validation of the respiration activity via confirmation of the waveform, as well as allows offline analysis outside of the implant by a clinician, a more complicated processor/computer, or an Al system that can analyze the data for more meaningful physiologic parameters and indicators.
  • respiration snapshot The advantages of the respiration snapshot are that significant diagnostic information is conveyed in the time series data of respiration or a surrogate respiration measure. Simple statistics such as mean minimum and maximum are not sufficient to convey the complexity of respiration.
  • time series data can be used for post-processing within the implant to determine critical features of the patient's health or current respiratory state in a manner that is compatible with a low power implant.
  • the time series data may also be transmitted to a server or a cloud-based application for detailed analysis and extraction of features, classification of respiratory waveform, determination of respiratory disorder, or diagnosis of health condition in an offline server, connected peripheral, or cloud computer.
  • the time series of the respiratory activity of the patient comprises a continuous waveform of a predetermined duration
  • the respiratory activity data is stored in the implantable medical device to be later transmitted for analysis offline or analyzed in real-time and stored on the implantable medical device.
  • the at least one medical parameter captured by the implantable medical device used for calculating the respiratory activity data of the patient comprises a thoracic impedance, an amplitude variation of an ECG and/or timevarying properties of the ECG.
  • implantable medical devices not fitted with an accelerometer are configured to produce respiratory activity data of the patient.
  • the means for capturing the respiratory activity data of the patient is an accelerometer or means for communicating with an accelerometer, wherein the captured respiratory activity data, in particular for an implantable cardiac monitor, is a chest wall motion.
  • the chest wall motion data advantageously provides accurate respiration data of the patient, which then may be subject to further analysis.
  • the means for capturing the respiratory activity data of the patient is configured to capture an impedance (e.g. of a chest cavity) measured between two electrodes of the implantable medical device or two electrodes on the surface of the patient body. This alternative measuring method also provides accurate respiration data of the patient that can then be used in downstream evaluation.
  • the means for capturing the respiratory activity data of the patient is configured to measure the time series of the respiratory activity of the patient with a sample rate between 0.5 Hz and 1 kHz, in particular with a sample rate between 1 Hz and 32 Hz. Said sample rate yields sufficient data points to identify relevant events in the respiratory signal of the patient.
  • the sample rate may further be chosen to adequately sample the data with respect to the slew rate of the signal. Further, the sample rate be oversampled initially as the device provides data to more than one feature, and subsequently resampled to the chosen respiration sample rate.
  • the means for capturing the respiratory activity data of the patient is configured to record the time series of the respiratory activity of the patient on a periodic basis based on an amount of time elapsed, a time of day or due to a predefined triggering event.
  • the periodic measurement thus provides typical patient medical data in which normal and/or abnormal respiration patterns may be observed.
  • the predefined triggering event is a change in body position or posture and/or establishing a resting posture such as no significant body motion or physical activity for at least a predetermined time period. This indicates the patient is at rest and in a steady state.
  • the predefined triggering event comprises motion sensor inputs, ECG inputs, impedance inputs, sleep status indicators, or triggers from peripheral or external devices, in particular a wearable sensor and/or an outside server or cloud-based system, wherein the ECG inputs comprise ECG amplitude modulation, ECG frequency modulation and/or autonomic nervous system indicators.
  • the event can thus be triggered by a wide range of sensors thus providing flexibility in data sources for event triggering.
  • the predefined triggering event occurs based on a geolocation of the patient, an incline angle of the patient, a status of the patient as determined by additional user data based on the patient's lifestyle and habits, or risk factors.
  • An example would be triggering a respiration measurement when a patient is in a region with low air quality index or a location where cigarette smoking or environmental smoke is common, conditions which might trigger asthma or exacerbation of COPD.
  • Another example would be triggering a respiration measurement on patients taking CNS depressants/opioids for chronic pain management, because such medications can dampen human respiratory function, they cause significant health consequences.
  • the predefined triggering event occurs based on a measurement of a connected altimeter, depth sensor or pressure sensor.
  • Fig. 1 shows a diagram of an implantable medical device according to a preferred embodiment of the invention
  • Fig. 3 - 7 show graphs of respiratory activity data of a patient according to the preferred embodiment of the invention.
  • Fig. 8 shows various implantation locations of the implantable medical device according to the preferred embodiment of the invention.
  • the implantable medical device 1 shown in Fig. 1 comprises means 10 for capturing respiratory activity data D of a patient and/or calculating the respiratory activity data D of the patient based on at least one medical parameter 12 captured by the implantable medical device 1.
  • the implantable medical device 1 may be a cardiac monitor (e.g. a loop recorder) and/or a neurostimulation device (e.g. a spinal cord stimulation device).
  • the implantable medical device 1 comprises means 14 for triggering a storage of the captured and/or calculated respiratory activity data D of the patient in response to fulfillment of a predetermined triggering event E, wherein the respiratory activity data D comprises a time series of the respiratory activity of the patient.
  • the time series of the respiratory activity of the patient comprises a continuous waveform of a predetermined duration.
  • the respiratory activity data D is preferably stored in the implantable medical device 1 to be later transmitted for analysis offline or alternatively analyzed in real-time and stored on the implantable medical device 1.
  • the at least one medical parameter 12 captured by the implantable medical device 1 used for calculating the respiratory activity data D of the patient comprises a thoracic impedance, an amplitude variation of an ECG and/or time-varying properties of the ECG.
  • the means 10 for capturing the respiratory activity data D of the patient is an accelerometer 18 or alternatively a means for communicating with an accelerometer 18, wherein the captured respiratory activity data D, in particular for an implantable cardiac monitor, is a chest wall motion.
  • the means 10 for capturing the respiratory activity data D of the patient may be configured to capture an impedance (e.g. of a chest cavity) measured between two electrodes of the implantable medical device 1 or two electrodes on the surface of the patient body.
  • an impedance e.g. of a chest cavity
  • the means 10 for capturing the respiratory activity data D of the patient is further configured to measure the time series of the respiratory activity of the patient with a sample rate between 0.5 Hz and 1 kHz, in particular with a sample rate between 1 Hz and 32 Hz.
  • the means 10 for capturing the respiratory activity data D of the patient is configured to record the time series of the respiratory activity of the patient on a periodic basis based on an amount of time elapsed, a time of day or due to a predefined triggering event E.
  • the predefined triggering event E is a change in body position or posture and/or establishing a resting posture such as no motion and/or no physical activity for at least a predetermined time period.
  • the predefined triggering event E comprises motion sensor inputs, ECG inputs, impedance inputs, sleep status indicators, or triggers from peripheral or external devices, in particular a wearable sensor and/or an outside server or cloud-based system, wherein the ECG inputs comprise ECG amplitude modulation, ECG frequency modulation and/or autonomic nervous system indicators.
  • the predefined triggering event E may occur based on a geolocation of the patient, an incline angle of the patient, a status of the patient as determined by additional user data based on the patient's lifestyle and habits, or risk factors.
  • the predefined triggering event E may also occur based on a measurement of a connected altimeter, depth sensor or pressure sensor.
  • Fig. 2 shows a flowchart of a computer-implemented method for operating an implantable medical device 1 according to the preferred embodiment of the invention.
  • the method comprises capturing Sla respiratory activity data D of a patient and/or calculating Sib the respiratory activity data D of the patient based on at least one medical parameter 12 captured by the implantable medical device 1.
  • the method comprises triggering S2 a storage of the captured and/or calculated respiratory activity data D of the patient in response to fulfillment of a predetermined triggering event E, wherein the respiratory activity data D comprises a time series of the respiratory activity of the patient.
  • Fig. 3 to 7 show graphs of respiratory activity data D of a patient according to the preferred embodiment of the invention.
  • a threshold value is shown in 120, where the peaks 105, 110, and 115 are appropriately detected.
  • a mean respiration rate can be determined and are representative of the patient’s respiratory state.
  • the respiratory peaks have different amplitudes and change over time, and there are also pauses between the respiratory peaks which are diagnostically important.
  • a simple threshold as shown in 230 would be insufficient and not representative of the breathing status as peaks 205, 215 and 220 would be detected while peak 210 would not.
  • the pause is only detected as the lack of a peak and could not be discriminated from the peak 210 which is simply below the threshold 230.
  • Graph 300 of Fig. 5 Another example of this is shown in Graph 300 of Fig. 5 where a general higher threshold shown as 340 is able to detect certain types of respiration activity, i.e. peaks 305, 330 but a more aggressive threshold shown as 350 is necessary to detect additional lower amplitude respiratory activity, i.e. peaks 310, 315, 320. While simple implants may be able to implement a single-tier threshold system for detection of respiratory peaks multiple levels may be required or a more complex analysis may be required to fully determine inhalation and exhalation and therefore measure and report a proper statistic for respiration rate, number of pauses, inhalation to expiration ratio, relative tidal volume, regularity, depth, and other relevant parameters.
  • a general higher threshold shown as 340 is able to detect certain types of respiration activity, i.e. peaks 305, 330 but a more aggressive threshold shown as 350 is necessary to detect additional lower amplitude respiratory activity, i.e. peaks 310, 315
  • the time series data may be used as a confirmatory measure to validate statistics such as minimum, maximum, and mean.
  • mean and ranges of respiration data per day can be provided over time and these are provided by existing solutions.
  • a time series would resolve exactly what led to the mean respiration rate or range of respirations visible in the data and provide much greater diagnostic power to determine the health of the patient.
  • the daily index shown in graph 400 indicates normal or abnormal breathing.
  • a plurality of indices are plotted over time such as several days.
  • the index in this case denotes amplitude of the respiration rate pattern but it could also stand for variability depending on what is considered the most important indicator of normal and abnormal breathing rate patterns.
  • the area 405 shows a normal respiratory function
  • the area 410 shows abnormal respiratory function.
  • the line 420 indicates a threshold of a breathing rate of e.g. 18 breaths per minute.
  • a reason for the increased breathing rate in the area 410 could be some fluid in the lungs which was later drained off be taking a specific drug to this effect, which then resulted in a more normal breathing rate.
  • determining signal minima and maxima in order to determine peak and trough points of a waveform might be complicated by waveform morphology as shown in graph 500 of Fig. 7.
  • a false peak 505, 510 compared to an actual peak 515 or false trough 520 compared to an actual trough 525 can be detected due to the shape, and signal thresholding determines erroneous results.
  • offline analysis using more sophisticated morphology matching algorithms and those assessing flat line portions or low slope portions of the waveform are used to accurately identify respiration parameters. In these cases, a respiration snapshot is critical to enable accurate analysis.
  • Fig. 8 shows various implantation locations of the implantable medical device 1 according to the preferred embodiment of the invention.
  • the implantable medical device 1 measures respiration as a continuous quantity. Respiration could be measured using thoracic impedance, amplitude variation of ECG, time-varying properties of ECG such as rate, or other methods. In particular, for an implantable cardiac monitor, chest wall motion as measured via an accelerometer 18 is particularly apt.
  • a device placed under the skin and above the sternum or rib cage as shown in Fig. 8 with device locations shown as 10, 20, or 30 is preferable. These locations also provide the ability to detect cardiac activity. If no cardiac activity is desired contralateral locations on the right side of the chest are also appropriate. Lateral locations under the arm or on the side of the rib cage would in this case also be appropriate.

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  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Medical Informatics (AREA)
  • Surgery (AREA)
  • Biophysics (AREA)
  • Pathology (AREA)
  • Veterinary Medicine (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Public Health (AREA)
  • Molecular Biology (AREA)
  • Physics & Mathematics (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Physiology (AREA)
  • Pulmonology (AREA)
  • Cardiology (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

L'invention concerne un dispositif médical implantable (1), comprenant des moyens (10) pour capturer des données d'activité respiratoire (D) d'un patient et/ou calculer les données d'activité respiratoire (D) du patient sur la base d'au moins un paramètre médical (12) capturé par le dispositif médical implantable (1), et des moyens (14) pour déclencher un stockage des données d'activité respiratoire capturées et/ou calculées (D) du patient en réponse à la satisfaction d'un événement de déclenchement prédéterminé (E), les données d'activité respiratoire (D) comprenant une série chronologique de l'activité respiratoire du patient. L'invention concerne en outre un procédé mis en œuvre par ordinateur pour faire fonctionner un dispositif médical implantable (1).
PCT/EP2024/076205 2023-09-29 2024-09-19 Dispositif médical implantable et procédé de fonctionnement d'un dispositif médical implantable Pending WO2025068014A1 (fr)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US202363541388P 2023-09-29 2023-09-29
US63/541,388 2023-09-29
EP23205251 2023-10-23
EP23205251.4 2023-10-23

Publications (1)

Publication Number Publication Date
WO2025068014A1 true WO2025068014A1 (fr) 2025-04-03

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Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040254501A1 (en) * 2000-08-11 2004-12-16 Mault James R. Achieving a relaxed state
US20050043652A1 (en) * 2003-08-18 2005-02-24 Lovett Eric G. Sleep state classification
US20050080348A1 (en) * 2003-09-18 2005-04-14 Stahmann Jeffrey E. Medical event logbook system and method
US20050142070A1 (en) * 2003-09-18 2005-06-30 Hartley Jesse W. Methods and systems for assessing pulmonary disease with drug therapy control
US20060036294A1 (en) * 2003-10-15 2006-02-16 Tehrani Amir J Patient compliance management device and method
US20110061647A1 (en) * 2003-08-18 2011-03-17 Stahmann Jeffrey E Patient Monitoring, Diagnosis, And/Or Therapy Systems and Methods
US20130197385A1 (en) * 2012-01-31 2013-08-01 Medtronic, Inc. Respiratory function detection
CN105286823A (zh) * 2015-10-13 2016-02-03 吉林大学 穿戴式自供电多生理参数监测装置及监测方法
WO2017018506A1 (fr) * 2015-07-30 2017-02-02 ミネベア株式会社 Dispositif de détection de condition physique, procédé de détection de condition physique et système de lit
US20190029601A1 (en) * 2017-07-26 2019-01-31 Cardiac Pacemakers, Inc. Worsening heart failure stratification
CN208709857U (zh) * 2017-11-17 2019-04-09 深圳和而泰智能控制股份有限公司 一种呼吸暂停检测系统
JP2019208876A (ja) * 2018-06-05 2019-12-12 株式会社東芝 呼吸センサ、呼吸検出装置、生体情報処理装置、生体情報処理方法、コンピュータプログラム及びマインドフルネス支援装置
US20230071214A1 (en) * 2021-09-03 2023-03-09 West Affum Holdings Corp Multi-function wearable monitoring system with sleep disorder warning
US20230077507A1 (en) * 2020-01-29 2023-03-16 Amir Landesberg Treatment of cardiac decompensation, pulmonary congestion and dyspnea

Patent Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040254501A1 (en) * 2000-08-11 2004-12-16 Mault James R. Achieving a relaxed state
US20050043652A1 (en) * 2003-08-18 2005-02-24 Lovett Eric G. Sleep state classification
US20110061647A1 (en) * 2003-08-18 2011-03-17 Stahmann Jeffrey E Patient Monitoring, Diagnosis, And/Or Therapy Systems and Methods
US20050080348A1 (en) * 2003-09-18 2005-04-14 Stahmann Jeffrey E. Medical event logbook system and method
US20050142070A1 (en) * 2003-09-18 2005-06-30 Hartley Jesse W. Methods and systems for assessing pulmonary disease with drug therapy control
US20060036294A1 (en) * 2003-10-15 2006-02-16 Tehrani Amir J Patient compliance management device and method
US20130197385A1 (en) * 2012-01-31 2013-08-01 Medtronic, Inc. Respiratory function detection
WO2017018506A1 (fr) * 2015-07-30 2017-02-02 ミネベア株式会社 Dispositif de détection de condition physique, procédé de détection de condition physique et système de lit
CN105286823A (zh) * 2015-10-13 2016-02-03 吉林大学 穿戴式自供电多生理参数监测装置及监测方法
US20190029601A1 (en) * 2017-07-26 2019-01-31 Cardiac Pacemakers, Inc. Worsening heart failure stratification
CN208709857U (zh) * 2017-11-17 2019-04-09 深圳和而泰智能控制股份有限公司 一种呼吸暂停检测系统
JP2019208876A (ja) * 2018-06-05 2019-12-12 株式会社東芝 呼吸センサ、呼吸検出装置、生体情報処理装置、生体情報処理方法、コンピュータプログラム及びマインドフルネス支援装置
US20230077507A1 (en) * 2020-01-29 2023-03-16 Amir Landesberg Treatment of cardiac decompensation, pulmonary congestion and dyspnea
US20230071214A1 (en) * 2021-09-03 2023-03-09 West Affum Holdings Corp Multi-function wearable monitoring system with sleep disorder warning

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