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WO2020003954A1 - Programme exécuté par ordinateur, dispositif de traitement d'informations et procédé exécuté par ordinateur - Google Patents

Programme exécuté par ordinateur, dispositif de traitement d'informations et procédé exécuté par ordinateur Download PDF

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Publication number
WO2020003954A1
WO2020003954A1 PCT/JP2019/022470 JP2019022470W WO2020003954A1 WO 2020003954 A1 WO2020003954 A1 WO 2020003954A1 JP 2019022470 W JP2019022470 W JP 2019022470W WO 2020003954 A1 WO2020003954 A1 WO 2020003954A1
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WIPO (PCT)
Prior art keywords
resident
walking
walking speed
trajectory data
computer
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.)
Ceased
Application number
PCT/JP2019/022470
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English (en)
Japanese (ja)
Inventor
寛 古川
武士 阪口
海里 姫野
恵美子 寄▲崎▼
遠山　修
藤原　浩一
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Konica Minolta Inc
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Konica Minolta Inc
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Priority to JP2020527345A priority Critical patent/JP7342863B2/ja
Publication of WO2020003954A1 publication Critical patent/WO2020003954A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • 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
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/22—Social work or social welfare, e.g. community support activities or counselling services
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/02—Alarms for ensuring the safety of persons
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
    • G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
    • G08B25/04—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using a single signalling line, e.g. in a closed loop

Definitions

  • the present disclosure relates to data processing, and more specifically, to data processing based on walking trajectories.
  • Patent Literature 1 Japanese Patent Application Laid-Open No. 2015-215711 states, "In order to watch the relative changes in behavior and ecology of residents in a manner close to the lives of residents, the progress of" aging "in which individual differences are remarkable.
  • a monitoring system that can relatively evaluate the resident according to the abilities and environment of the resident and present a watching specification that matches the evaluation ”(see [Problem] in [Summary]).
  • Patent Document 2 JP-A-2017-117423 discloses a “watching system capable of grasping daily activities including a walking speed of a watching target person”.
  • the watching system includes “a plurality of slave units 2 (2A to 2G) installed in a house H and a master unit 3”.
  • each child device 2 senses the target person, it sends a notification signal to the parent device 3.
  • master device 3 Based on the time data of the notification signal from child device 2D and the time data of the notification signal from child device 2E, master device 3 calculates the travel time of the watching target from bedroom PD to toilet PD, and The walking speed of the watching target is calculated based on the time. ] (Refer to [Summary]).
  • the degree of care is determined based on, for example, interviews with the target person and caregiver and the opinion of the attending physician. May take some time.
  • the measured value may change according to the period in which the user is moving.
  • the degree of change in the measured value (for example, walking speed or the like) differs depending on the physique, age, gender, and the like of the resident. Therefore, there is a case where a change in a resident's state cannot be properly grasped by simply comparing only the measured values. Therefore, there is a need for a technique that can properly grasp changes in the state of a resident.
  • the present disclosure has been made in view of the above-described background, and an object in a certain aspect is to provide a technique capable of appropriately grasping a change in a resident's state.
  • a program to be executed by a computer causes the computer to acquire walking trajectory data representing the trajectory of the resident, calculate the walking speed of the resident based on the plurality of trajectory data, and And normalizing the walking speed based on the determined coefficient.
  • the occupant attributes include any of age, gender, height, or weight.
  • the program causes the computer to compare the values of the walking speeds calculated based on the walking trajectory data acquired on a plurality of different days with the normalized values of the respective walking speeds.
  • the step of determining the degree is further executed.
  • an information processing apparatus includes a memory and a processor coupled to the memory.
  • the processor obtains walking trajectory data representing the walking trajectory of the resident, calculates the walking speed of the resident based on the plurality of walking trajectory data, and determines the walking speed in advance based on the attribute of the resident. It is configured to normalize the walking speed based on the calculated coefficient.
  • the attribute of the resident includes any of age, gender, height, and weight.
  • the processor is configured to compare the respective walking speeds calculated based on the walking trajectory data acquired on a plurality of different days with each normalized value of the walking speed. Is further configured to determine
  • a computer-implemented method includes the steps of acquiring walking trajectory data representing a trajectory of a resident, calculating a walking speed of the resident based on a plurality of trajectory data, and determining in advance based on attributes of the resident. Normalizing the walking speed based on the obtained coefficient.
  • the resident's attributes include any of age, gender, height, or weight.
  • the method includes the step of providing a care request for the resident based on a comparison of each value obtained by normalizing each walking speed calculated based on the walking trajectory data acquired on a plurality of different days.
  • the method further includes the step of determining a degree.
  • the program executed by the computer, the information processing apparatus, and the method executed by the computer according to the present disclosure can appropriately grasp a change in the state of the resident.
  • FIG. 1 is a diagram illustrating an example of a configuration of a watching system.
  • FIG. 1 is a block diagram illustrating an outline of a configuration of a watching system.
  • FIG. 3 is a block diagram illustrating a hardware configuration of a computer system 300 functioning as a cloud server 150. It is a figure showing an example of the outline of the device composition of watching system 100 using sensor box 119.
  • FIG. 3 is a diagram illustrating one mode of data storage in a hard disk 5 included in the cloud server 150. It is a figure showing change of a walking locus of a resident in a certain situation.
  • FIG. 3 is a diagram illustrating one mode of data storage in a hard disk 5.
  • FIG. 3 is a diagram illustrating an example of a display on a monitor 8. It is a figure showing an example of a diagnosis report of a walking speed.
  • ⁇ ⁇ ⁇ ⁇ In certain situations, normalize the observation values (walking speed, etc.) of the target person such as the resident of the facility. Using normalized observations, all subjects can be evaluated on the same basis.
  • the degree of care required of the resident is determined based on a comparison of values obtained by normalizing each walking speed calculated based on walking trajectory data acquired on a plurality of different days.
  • the walking speed is calculated using the walking locus data of each resident selected by the user, and the normalized walking speed is calculated by multiplying by the attribute coefficient.
  • FIG. 1 is a diagram illustrating an example of the configuration of the watching system 100.
  • the watching target is, for example, a resident in each living room provided in the living room area 180 of the facility.
  • living rooms 110 and 120 are provided in a living room area 180.
  • the living room 110 is assigned to the resident 111.
  • the living room 120 is assigned to the resident 121.
  • the number of living rooms included in the watching system 100 is two, but the number is not limited to this.
  • Network 190 may include both an intranet and the Internet.
  • the mobile terminal 143 carried by the caregiver 141 and the mobile terminal 144 carried by the caregiver 142 can be connected to the network 190 via the access point 140. Further, the sensor box 119, the management server 200, and the access point 140 can communicate with the cloud server 150 via the network 190.
  • Each of the living rooms 110 and 120 includes a closet 112, a bed 113, and a toilet 114 as facilities.
  • the door of the living room 110 is provided with a door sensor 118 that detects opening and closing of the door.
  • a toilet sensor 116 for detecting the opening and closing of the toilet 114 is installed on the door of the toilet 114.
  • the bed 113 is provided with an odor sensor 117 for detecting the odor of each of the residents 111 and 121.
  • Each resident 111, 121 is equipped with a vital sensor 290 for detecting vital information of the resident 111, 121.
  • the detected vital information includes the resident's body temperature, respiration, heart rate, and the like.
  • the residents 111 and 121 can operate the care call slave 115, respectively.
  • the sensor box 119 has a built-in sensor for detecting the behavior of an object in the living rooms 110 and 120.
  • a sensor is a Doppler sensor for detecting the movement of an object.
  • a camera is another example.
  • the sensor box 119 may include both a Doppler sensor and a camera as sensors.
  • FIG. 2 is a block diagram showing an outline of the configuration of the watching system 100.
  • the sensor box 119 includes a control device 101, a read only memory (ROM) 102, a random access memory (RAM) 103, a communication interface 104, a camera 105, a Doppler sensor 106, a wireless communication device 107, and a storage device. 108.
  • the control device 101 controls the sensor box 119.
  • the control device 101 is composed of, for example, at least one integrated circuit.
  • the integrated circuit is, for example, at least one CPU (Central Processing Unit), MPU (Micro Processing Unit) or other processor, at least one ASIC (Application Specific Integrated Circuit), at least one FPGA (Field Programmable Gate Array), or these. And the like.
  • An antenna (not shown) and the like are connected to the communication interface 104.
  • the sensor box 119 exchanges data with an external communication device via the antenna.
  • External communication devices include, for example, management server 200, mobile terminals 143, 144 and other terminals, access point 140, cloud server 150, and other communication terminals.
  • the camera 105 is a near-infrared camera in one implementation.
  • the near-infrared camera includes an IR (Infrared) projector that emits near-infrared light.
  • IR Infrared
  • camera 105 is a surveillance camera that receives only visible light.
  • a 3D sensor or a thermographic camera may be used as camera 105.
  • the sensor box 119 and the camera 105 may be configured integrally or may be configured separately.
  • the Doppler sensor 106 is, for example, a microwave Doppler sensor, and emits and receives radio waves to detect the behavior (movement) of objects in the living rooms 110 and 120. Thereby, the biological information of the resident 111, 121 of the living room 110, 120 can be detected.
  • the Doppler sensor 106 emits microwaves in the 24 GHz band toward the beds 113 of the rooms 110 and 120, and receives reflected waves reflected by the residents 111 and 121. The reflected waves are Doppler shifted by the actions of the residents 111 and 121.
  • the Doppler sensor 106 can detect the respiratory state and heart rate of the residents 111 and 121 from the reflected waves.
  • the wireless communication device 107 receives signals from the care call slave device 240, the door sensor 118, the toilet sensor 116, the odor sensor 117, and the vital sensor 290, and transmits the signals to the control device 101.
  • the care call slave unit 240 includes a care call button 241. When the button is operated, care call slave device 240 transmits a signal indicating that the operation has been performed to wireless communication device 107.
  • the door sensor 118, the toilet sensor 116, the odor sensor 117, and the vital sensor 290 transmit respective detection results to the wireless communication device 107.
  • the storage device 108 is, for example, a fixed storage device such as a flash memory or a hard disk, or a recording medium such as an external storage device.
  • the storage device 108 stores a program executed by the control device 101 and various data used for executing the program.
  • the various data may include behavior information of the residents 111 and 121. The details of the action information will be described later.
  • At least one of the above-mentioned programs and data is a storage device other than the storage device 108 (for example, a storage area (for example, a cache memory) of the control device 101, a ROM 102, The RAM 103 and external devices (for example, the management server 200 and the portable terminals 143 and 144) may be stored.
  • a storage device other than the storage device 108 for example, a storage area (for example, a cache memory) of the control device 101, a ROM 102,
  • the RAM 103 and external devices for example, the management server 200 and the portable terminals 143 and 144) may be stored.
  • the action information is, for example, information indicating that the residents 111 and 121 have performed a predetermined action.
  • the predetermined action is “wake up” indicating that the resident 111, 121 has occurred, “getting out” indicating that the resident 111, 121 has left the bedding, and the resident 111, 121 has fallen from the bedding. This includes four actions of “fall” indicating that the resident has fallen, and “falling” indicating that the resident 111 or 121 has fallen.
  • the control device 101 generates each piece of behavior information of the resident 111, 121 associated with each room 110, 120 based on an image captured by the camera 105 installed in each room 110, 120. I do.
  • the control device 101 detects, for example, the heads of the residents 111 and 121 from the image, and based on the detected temporal changes in the sizes of the heads of the residents 111 and 121, “ “Wake up”, “get out of bed”, “fall” and “fall” are detected.
  • “Wake up”, “get out of bed”, “fall” and “fall” are detected.
  • the storage area of the beds 113 in the living rooms 110 and 120, the first threshold Th1, the second threshold Th2, and the third threshold Th3 are stored in the storage device.
  • the first threshold Th1 identifies the size of the resident's head between the lying position and the sitting position in the area where the bed 113 is located.
  • the second threshold value Th2 identifies whether or not the resident is in the standing posture, based on the size of the resident's head in the living rooms 110 and 120 excluding the area where the bed 113 is located.
  • the third threshold value Th3 identifies whether or not the resident is in the recumbent posture in the living rooms 110 and 120 excluding the area where the bed 113 is located, based on the size of the resident's head.
  • the control device 101 extracts a moving object region from the target image as a region of the occupants 111 and 121 by, for example, the background difference method or the frame difference method.
  • the control device 101 further derives from the extracted moving body region by, for example, a circular or elliptical Hough transform, by pattern matching using a prepared head model, or by a neural network learned for head detection.
  • the head areas of the residents 111 and 121 are extracted using the thresholds thus set.
  • the control device 101 detects “wake up”, “get out of bed”, “fall” and “fall” from the extracted position and size of the head.
  • the control device 101 determines that the position of the head extracted as described above is within the area where the bed 113 is located, and that the size of the head extracted as described above uses the first threshold Th1 to lie down. When it is detected that the size of the posture has changed to the size of the sitting posture, it may be determined that the action “wake up” has occurred.
  • the control device 101 controls the size of the head extracted as described above.
  • the control device 101 controls the size of the head extracted as described above.
  • the control device 101 determines that the position of the head extracted as described above is located in the living rooms 110 and 120 excluding the area where the bed 113 is located, and the size of the extracted head uses the third threshold Th3. If it is detected that the size has changed from a certain size to the size of the recumbent posture, it may be determined that the action “fall” has occurred.
  • the control device 101 of the sensor box 119 generates the behavior information of the residents 111 and 121.
  • an element other than the control device 101 for example, the cloud server 150
  • the cloud server 150 generates the behavior information of the residents 111 and 121 using the images in the living rooms 110 and 120. Is also good.
  • the mobile terminals 143 and 144 include a control device 221, a ROM 222, a RAM 223, a communication interface 224, a display 226, a storage device 228, and an input device 229.
  • the mobile terminals 143 and 144 are realized as, for example, a smartphone, a tablet terminal, a wristwatch-type terminal, or other wearable devices.
  • the control device 221 controls the mobile terminals 143 and 144.
  • the control device 221 is configured by, for example, at least one integrated circuit.
  • the integrated circuit includes, for example, at least one CPU, at least one ASIC, at least one FPGA, or a combination thereof.
  • An antenna (not shown) and the like are connected to the communication interface 224.
  • the mobile terminals 143 and 144 exchange data with an external communication device via the antenna and the access point 140.
  • External communication devices include, for example, the sensor box 119, the management server 200, and the like.
  • the display 226 is realized by, for example, a liquid crystal display, an organic EL (Electro Luminescence) display, or the like.
  • the input device 229 is realized by, for example, a touch sensor provided on the display 226. The touch sensor receives a touch operation on the mobile terminals 143 and 144, and outputs a signal corresponding to the touch operation to the control device 221.
  • the storage device 228 is realized by, for example, a flash memory, a hard disk or another fixed storage device, or a removable data recording medium.
  • FIG. 3 is a block diagram illustrating a hardware configuration of computer system 300 functioning as cloud server 150.
  • the computer system 300 includes, as main components, a CPU 1 that executes a program, a mouse 2 and a keyboard 3 that receive an instruction input by a user of the computer system 300, and data generated by executing the program by the CPU 1 or a mouse 2.
  • a RAM 4 for volatilely storing data input via the keyboard 3
  • a hard disk 5 for nonvolatilely storing data
  • an optical disk drive 6 a communication interface (I / F) 7, and a monitor 8 Including.
  • Each component is mutually connected by a data bus.
  • the optical disk drive 6 is loaded with a CD-ROM 9 and other optical disks.
  • the processing in the computer system 300 is realized by each hardware and software executed by the CPU 1.
  • Such software may be stored in the hard disk 5 in advance.
  • the software may be stored on the CD-ROM 9 or another recording medium and distributed as a computer program.
  • the software may be provided as a downloadable application program by an information provider connected to the so-called Internet.
  • Such software is temporarily stored in the hard disk 5 after being read from the recording medium by the optical disk drive 6 or another reading device, or downloaded via the communication interface 7.
  • the software is read from the hard disk 5 by the CPU 1 and stored in the RAM 4 in the form of an executable program.
  • CPU 1 executes the program.
  • Each component of the computer system 300 shown in FIG. 3 is a general component. Therefore, it can be said that one of the essential parts of the technical idea according to the present disclosure is software stored in the RAM 4, the hard disk 5, the CD-ROM 9, or other recording media, or software downloadable via a network.
  • the storage medium may include a non-transitory, computer-readable data storage medium. Since the operation of each piece of hardware of computer system 300 is well known, detailed description will not be repeated.
  • the recording medium is not limited to a CD-ROM, FD (Flexible Disk), or hard disk, but may be a magnetic tape, cassette tape, optical disk (MO (Magnetic Optical Disc) / MD (Mini Disc) / DVD (Digital Versatile Disc)). , IC (Integrated Circuit) card (including memory card), optical card, mask ROM, EPROM (Electronically Programmable Read-Only Memory), EEPROM (Electronically Erasable Programmable Read-Only Memory), and fixed memory such as flash ROM It may be a medium that carries the program.
  • IC Integrated Circuit
  • the program here includes not only a program directly executable by the CPU but also a program in a source program format, a compressed program, an encrypted program, and the like.
  • FIG. 4 is a diagram illustrating an example of a schematic device configuration of the watching system 100 using the sensor box 119.
  • the watching system 100 is used for watching the residents 111 and 121 who are the monitoring target (monitoring target) and other residents. As shown in FIG. 4, a sensor box 119 is attached to the ceiling of the living room 110. Sensor boxes 119 are similarly attached to other rooms.
  • a range 410 represents a detection range of the sensor box 119.
  • the Doppler sensor detects a person's behavior that has occurred within the range 410.
  • the sensor box 119 has a camera as a sensor, the camera captures an image in the range 410.
  • the sensor box 119 is installed in, for example, a nursing care facility, a medical facility, or a home.
  • the sensor box 119 is attached to the ceiling, and the resident 111 and the bed 113 are imaged from the ceiling.
  • the place where the sensor box 119 is mounted is not limited to the ceiling, and may be mounted on the side wall of the living room 110.
  • the watching system 100 detects a danger occurring to the resident 111 based on a series of images (that is, videos) obtained from the camera 105.
  • the detectable danger includes a fall of the resident 111 and a state where the resident 111 is at a danger location (for example, a bed fence).
  • the monitoring system 100 When the monitoring system 100 detects that the resident 111 is in danger, the monitoring system 100 notifies the caregivers 141, 143, etc. of that fact. As an example of the notification method, the watching system 100 notifies the danger of the resident 111 to the portable terminals 143 and 144 of the caregivers 141 and 142. Upon receiving the notification, the mobile terminals 143 and 144 notify the caregivers 141 and 142 of the danger of the resident 111 by a message, voice, vibration, or the like. Accordingly, the caregivers 141 and 142 can immediately recognize that the danger has occurred in the resident 111 and can rush to the resident 111 quickly.
  • FIG. 4 illustrates an example in which the watching system 100 includes one sensor box 119, but the watching system 100 may include a plurality of sensor boxes 119.
  • FIG. 4 shows an example in which the watching system 100 includes a plurality of mobile terminals 143 and 144. However, the watching system 100 can be realized by one mobile terminal.
  • FIG. 5 is a diagram illustrating one mode of data storage in the hard disk 5 included in the cloud server 150.
  • the hard disk 5 holds the table 60.
  • the table 60 sequentially stores data transmitted from each sensor provided in each living room as walking locus data. More specifically, the table 60 includes a room ID 61, a date and time 62, an X coordinate value 63, and a Y coordinate value 64.
  • the room ID 61 identifies the room of the resident.
  • the date and time 62 identifies the date and time when the signal sent from the sensor was acquired.
  • the X coordinate value 63 indicates the point detected at the date and time, that is, the X coordinate value of the position of the resident.
  • the Y coordinate value 64 represents the point detected at the date and time, that is, the Y coordinate value of the position of the resident.
  • the coordinate axes that are the basis of the X coordinate value and the Y coordinate value are defined, for example, with reference to the end point of the living room (for example, one corner of the room).
  • the coordinate axis may be defined based on a certain point in the facility where each living room is provided.
  • the hard disk 5 holds the image data sent from the sensor box 119.
  • Image data is acquired at predetermined time intervals.
  • the CPU 1 can identify the state of the resident by performing image analysis using each image data. For example, the CPU 1 can extract a head from each image data and extract a time when the resident is lying down, a time when the resident is sitting on the bed 113, and a time when the resident is walking.
  • the person who walks in the room may be a caregiver or a family other than the resident. Therefore, the CPU 1 can exclude a walking locus of a person other than the resident.
  • the CPU 1 may calculate a walking speed for each walking locus, and exclude a walking locus whose speed is equal to or higher than a certain speed estimated to be a walking speed of a healthy person other than a resident from image analysis targets.
  • a walking speed measured in advance or a walking speed measured at the time of image analysis can be used as a walking speed of a healthy person.
  • the CPU 1 calculates, for each point detected at a plurality of times, an x-coordinate value and a y-coordinate value, and a next point from a certain point in each point. Can be calculated based on the time required to reach.
  • the CPU 1 indicates a walking locus of a resident and reads a plurality of walking locus data acquired on different days from the hard disk 5.
  • the CPU 1 calculates a walking speed of the resident based on a plurality of walking trajectory data. For example, for each walking locus, the CPU 1 calculates the difference between the x coordinate value and the y coordinate value of the two observed points, and divides the time required for movement between the two points by the difference. Calculate the walking speed.
  • the walking locus data to be calculated is not particularly limited.
  • the walking locus data acquired the day before the day on which the calculation was instructed the walking locus data acquired three months before the previous day, and the walking locus data acquired six months before the previous day are used. May be done.
  • the period for seeing the change in walking speed is not limited to three months and six months ago. Walking trajectory data one month ago and two months ago may be used. Alternatively, walking locus data one year ago may be used.
  • the CPU 1 normalizes the walking speed by multiplying the walking speed by a predetermined coefficient based on the attribute of the resident.
  • Normalized value calculated walking speed ⁇ coefficient according to first attribute ⁇ ... ⁇ coefficient according to n-th attribute (2)
  • the attributes of the resident are age, gender, height, Or include either weight.
  • the normalized walking speed is calculated as follows as an example.
  • Normalized walking speed measured walking speed ⁇ age coefficient ⁇ sex coefficient ⁇ height coefficient ⁇ weight coefficient (3)
  • the CPU 1 is calculated based on walking locus data acquired on a plurality of different days. Based on the comparison of the respective values obtained by normalizing the respective walking speeds, the degree of care required of the resident is determined.
  • the CPU 1 calculates a walking speed using the walking locus data of each resident selected by the user, and calculates a normalized walking speed by multiplying by a coefficient according to the attribute. By comparing the normalized values, the CPU 1 can detect the presence or absence of a change in the state of each resident and the degree of the change.
  • FIG. 6 is a diagram illustrating a change in a walking locus of a resident in a certain situation.
  • each walking locus 610, 611 shows a reciprocating locus from the bed 113 to the toilet 114. Therefore, it is presumed that the resident went straight from bed 113 to toilet 114. For example, when the resident does not have difficulty walking or does not develop dementia or the like, even at night, the path from the bed 113 to the toilet 114 takes the walking locus 610 so as to take the shortest course. , 611.
  • the resident may walk without purpose (wandering).
  • walking trajectories 622 and 623 that are not directed to a specific destination (for example, the wash basin 51, the closet 112, the desk 52, etc.) can be observed. Therefore, by observing the change in the walking locus of each resident, it is possible to objectively grasp the change in the state of the resident. For example, if it is detected that the walking trajectory, which has been almost straight from the bed 113 to the destination in the past, fluctuates or goes around the same place, it is estimated that the state of the resident has changed. .
  • FIG. 7 is a diagram illustrating one mode of data storage in hard disk 5.
  • the data structure shown in FIG. 7 is generated on the hard disk 5 of the cloud server 150 or the management server 200.
  • the hard disk 5 has tables 710, 720, and 730.
  • the table 710 includes an age 711 and an age coefficient 712.
  • the age 711 is classified every several years.
  • the width of the age 711 is not limited to that illustrated in FIG. For example, it may be in units of two or three years or ten years.
  • Table 720 includes gender 721 and gender coefficient 722.
  • the gender 721 is applied to the gender of the resident.
  • the gender coefficient 722 is applied according to the gender of the resident.
  • Table 730 includes height 731 and height coefficient 732.
  • the height 731 indicates the height of the resident.
  • the width of the height is not limited to the example (10 cm) shown in FIG. 7 and may be another width, for example, 2 cm, 5 cm, or the like.
  • Height coefficient 732 represents a coefficient applied to each height.
  • FIG. 8 is a diagram showing the correspondence between the walking speed and the level of the need for nursing care or support required according to the walking speed.
  • the hard disk 5 includes the table 800.
  • the table 800 includes the normalized walking speed 810 and the degree of care / support required 820.
  • the normalized walking speed 810 is a walking speed calculated by multiplying by a weight coefficient corresponding to each attribute shown in FIG.
  • the degree of need for nursing / support required 820 indicates the degree of need for nursing or support required according to the walking speed.
  • FIG. 9 is a flowchart showing a part of the process executed by CPU 1 of cloud server 150.
  • step S910 the CPU 1 acquires a plurality of walking trajectory data from the hard disk 5 based on the instruction of the data processing being given to the cloud server 150. For example, when a user (administrator, nursing staff, etc.) of the management server 200 accessing the cloud server 150 instructs data processing, the cloud server 150 stores the stored walking trajectory data (see FIG. 5). The data is read from the hard disk 5 to the RAM 4.
  • step S920 CPU 1 calculates the walking speed of the resident based on the plurality of walking trajectory data.
  • the CPU 1 uses the walking locus data observed at a designated time such as morning, afternoon, before going to bed, etc., and moves in using the time required for the movement of two points and the coordinate values of the two points.
  • the walking speed of the person is calculated.
  • Data serving as a basis for calculating the walking speed may be any of image data acquired by the camera 105 and data output from the Doppler sensor 106.
  • CPU 1 reads out a coefficient (FIG. 7) predetermined based on the attribute of the resident.
  • each coefficient may be input by the user each time during the normalization process.
  • step S940 the CPU 1 normalizes the walking speed by multiplying the walking speed by the coefficient.
  • the CPU 1 normalizes the walking speed using the formula “calculated walking speed ⁇ age coefficient ⁇ sex coefficient ⁇ height coefficient”. Note that all the coefficients shown in FIG. 7 need not be used as the coefficients used for normalization, and other coefficients than those shown in FIG. 7 may be used.
  • step S950 CPU 1 stores the normalized value in hard disk 5.
  • step S960 CPU 1 reads the normalized values calculated based on the walking trajectory data acquired on a plurality of different days. At this time, the CPU 1 may read the values of each of the plurality of residents selected by the user.
  • CPU 1 compares each value. For example, the CPU 1 compares the normalized values of one resident three days before and six months before the tenant's day. In a case where a plurality of residents are selected in another aspect, similarly, for each of the residents, the values after the normalization on the day before, three months before, and six months before the residents are compared. Further, the CPU 1 can display each value on the monitor 8 as a graph.
  • CPU 1 determines the state of the resident based on the result of the comparison. For example, if the CPU 1 detects a resident whose walking speed is significantly reduced, the CPU 1 displays on the monitor 8 a determination result such as “check of nursing care required” or “requirement of detailed inspection”. Alternatively, it may be output to a form as a diagnosis result.
  • FIG. 10 is a diagram illustrating an example of a display on the monitor 8.
  • the monitor 8 displays a graph 1010 of Mr. A and a graph 1020 of Mr. B based on the data before the normalization.
  • the monitor 8 displays a graph 1011 of Mr. A and a graph 1021 of Mr. B based on the normalized data.
  • the walking speed of Mr. B is higher than the walking speed of Mr. A
  • the degree of decrease in the walking ability of Mr. A is larger than the degree of the walking ability of Mr. B. It is understood.
  • FIG. 11 is a diagram showing an example of a walking speed diagnosis report.
  • the monitor 8 displays a diagnostic report based on FIG.
  • the monitor 8 displays the attributes of the selected resident, the diagnosis result, and the like. Is displayed.
  • the monitor 8 may display a notice such as "check of degree of nursing care required", "requirement of detailed inspection” or the like for a resident requiring special attention. Thereby, the user can take necessary measures according to the degree of change of the resident.
  • a measured value for example, walking speed
  • a coefficient defined in accordance with the attribute of a resident a state in which an influence due to a difference in attribute is excluded.
  • the state and ability eg, walking ability
  • the status of each resident can be objectively grasped, and the status of each resident can be compared without being affected by the attribute, so that the status of each resident can be grasped more accurately.
  • This technology is applicable to information processing using data obtained in hospitals, nursing homes, nursing homes and other facilities.

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Abstract

L'invention concerne un procédé exécuté par une unité centrale (CPU) d'un système informatique, comprenant : une étape (S910) à laquelle des données de trajectoire de marche sont acquises à partir d'un disque dur ; une étape (S920) à laquelle la vitesse de marche d'un occupant pertinent est calculée sur la base d'une pluralité d'éléments de données de trajectoire de marche ; une étape (S930) à laquelle un coefficient prédéterminé est lu sur la base d'un attribut d'un occupant ; une étape (S940) à laquelle la vitesse de marche est normalisée par multiplication de la vitesse de marche par le coefficient ; une étape (S950) à laquelle la valeur normalisée est sauvegardée ; une étape (S960) à laquelle une valeur normalisée calculée sur la base de données de trajectoire de marche acquises sur une pluralité de jours différents est lue ; une étape (S970) à laquelle les valeurs sont comparées ; et une étape (S980) à laquelle l'état de la personne pertinente est déterminé sur la base des résultats de comparaison.
PCT/JP2019/022470 2018-06-26 2019-06-06 Programme exécuté par ordinateur, dispositif de traitement d'informations et procédé exécuté par ordinateur Ceased WO2020003954A1 (fr)

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JP2023012291A (ja) * 2021-07-13 2023-01-25 コニカミノルタ株式会社 介護を支援する情報を提供するためにコンピューターによって実行される方法、当該方法をコンピューターに実行させるプログラム、および、介護支援情報提供装置

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JP2014140604A (ja) * 2013-01-23 2014-08-07 Kazuhiro Shiina 歩行速度および歩幅測定システム
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JP2023012291A (ja) * 2021-07-13 2023-01-25 コニカミノルタ株式会社 介護を支援する情報を提供するためにコンピューターによって実行される方法、当該方法をコンピューターに実行させるプログラム、および、介護支援情報提供装置
JP7753699B2 (ja) 2021-07-13 2025-10-15 コニカミノルタ株式会社 介護を支援する情報を提供するためにコンピューターによって実行される方法、当該方法をコンピューターに実行させるプログラム、および、介護支援情報提供装置

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