WO2019244647A1

WO2019244647A1 - Computer-executable program, information processing device, and computer-executable method

Info

Publication number: WO2019244647A1
Application number: PCT/JP2019/022466
Authority: WO
Inventors: 寛古川; 武士阪口; 海里姫野; 恵美子寄▲崎▼; 遠山　修; 藤原　浩一
Original assignee: コニカミノルタ株式会社
Priority date: 2018-06-20
Filing date: 2019-06-06
Publication date: 2019-12-26
Also published as: JPWO2019244647A1; JP7215481B2

Abstract

In this invention, the process to be executed by a CPU of a computer system comprises: a step (S820) for reading out a plurality of instances of trajectory data acquired on different days and representing walking trajectories of a person in a room; a step (S830) for using either walking characteristics of an inhabitant of the room or walking characteristics of a person in the room other than the inhabitant to identify trajectory data relating to the inhabitant and trajectory data relating the other person in the room among the acquired plurality of instances of trajectory data; a step (S840) for computing the walking speed of the inhabitant of the room using the identified trajectory data relating to the inhabitant; and a step (S850) for outputting identification information relating to the inhabitant and the walking speed of the inhabitant.

Description

Computer-executed program, information processing apparatus, and computer-executed method

The present disclosure relates to data processing, and more specifically, to data processing based on walking trajectories.

技術 Techniques for watching residents are known. For example, Japanese Patent Application Laid-Open No. 2015-215711 (Patent Literature 1) 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]).

JP-A-2017-117423 (Patent Document 2) 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”. When each child device 2 senses the target person, it sends a notification signal to the parent 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]).

Japanese Patent Application Laid-Open No. 2017-151676 (Patent Document 3) discloses "a monitored person monitoring device, a method, and a system capable of further improving work efficiency". The monitored person monitoring device is configured such that an event notification communication signal for notifying the event, containing event information indicating the content of a predetermined event related to the monitored person to be monitored, is communicably connected. The management server SV as an example is a device that notifies the terminal device.The self-sustained determination processing unit 223 that determines whether the monitored person Ob can be independent based on an image acquired from the sensor device via the network. And a warning notification processing unit 224 that transmits a warning notification communication signal containing warning information indicating a warning to a predetermined terminal device when the monitored person Ob is determined to be unable to become independent by the independence determination processing unit 223. (See [Summary]).

JP-A-2015-215711 JP-A-2017-117423 JP 2017-151676 A

For those who need watching or nursing care, nursing care certification is based on, for example, interviews with the target person and caregiver and the opinions of the attending physician. May take a while. Therefore, there is a need for a technique that enables quantitative measurement and does not require much time for determination.

The present disclosure has been made in view of the above-described background, and an object in one aspect is to provide a technique for deriving quantitative information that can be used for recognition of a caregiving degree.

According to one embodiment, a program to be executed on a computer is provided. This program is a computer which represents a walking locus of a person in a room, acquires a plurality of locus data acquired on different days, and acquires the locus data based on a walking characteristic of a resident of the room or a walking characteristic of a non-resident. Determining the trajectory data other than the resident in the room from the plurality of trajectory data obtained, and the trajectory data of the resident, and using the trajectory data of the resident after the determination, the walking speed of the resident in the room Is calculated.

According to an embodiment, the determining step includes determining, as the resident's trajectory data, the trajectory data in which the starting point and the ending point of the trajectory are in the vicinity of the bed arranged in the living room among the plurality of trajectory data. Including.

According to one embodiment, the determining step includes excluding, from the obtained plurality of track data, track data corresponding to a walking speed defined as a walking speed other than the resident from the plurality of track data. Including.

According to an embodiment, the determining step includes determining, as the trajectory data of the resident, the trajectory data of a predetermined time as a time zone in which only the resident is in the room among the plurality of obtained trajectory data. Including doing.

According to one embodiment, the program causes the computer to further execute a step of outputting a proposal for reconsidering the degree of care of the resident based on the calculation result of the walking speed.

According to another embodiment, an information processing apparatus including a memory and a processor coupled to the memory is provided. The processor represents a walking trajectory of a person in the room, acquires a plurality of trajectory data acquired on different days, and acquires a plurality of trajectories acquired based on walking characteristics of the resident of the room or walking characteristics other than the resident. It is configured to discriminate trajectory data other than the resident in the room from the data and the trajectory data of the resident, and calculate the walking speed of the resident in the room using the trajectory data of the resident after the discrimination. ing.

According to one embodiment, the processor determines, as the resident's trajectory data, the trajectory data in which the starting point and the ending point of the trajectory are near the bed arranged in the living room among the plurality of trajectory data.

According to one embodiment, the processor excludes, from the plurality of track data, the track data corresponding to the walking speed measured in advance as the walking speed other than the resident, from the obtained plurality of track data.

According to an embodiment, the processor determines, as the trajectory data of the resident, the trajectory data of a predetermined time as a time zone in which only the resident is in the room, among the plurality of obtained trajectory data.

According to one embodiment, the processor is further configured to output a suggestion that prompts a review of the resident's care level based on the result of the walking speed calculation.

According to yet another embodiment, a computer-implemented method is provided. This method represents a walking trajectory of a person in a living room, and acquiring a plurality of trajectory data obtained on different days, and is obtained based on walking characteristics of a resident of the living room or walking characteristics other than the resident. A step of discriminating the trajectory data other than the resident in the room from the plurality of trajectory data and the trajectory data of the resident, and calculating the walking speed of the resident in the room using the trajectory data of the resident after the discrimination Performing the steps.

According to an embodiment, the determining step includes, among the plurality of acquired track data, excluding the track data corresponding to the walking speed defined as the walking speed other than the resident from the plurality of track data. including.

According to one embodiment, the method further includes the step of outputting a suggestion prompting a review of the degree of care of the resident based on the result of the calculation of the walking speed.

In one aspect, quantitative information that can be used for the recognition of the degree of need for nursing care can be derived.
The above and other objects, features, aspects and advantages of the present invention will become apparent from the following detailed description of the invention that is understood in connection with the accompanying drawings.

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. It is a figure showing the difference between the walking locus of the resident of the living room 110 according to a certain situation, and the locus of a resident. 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 distribution of the moving speed of the person calculated for every locus. 9 is a flowchart illustrating a part of a process executed by CPU 1 of cloud server 150. It is a figure showing transition of the walking speed of five residents in a certain nursing home for six months. It is a figure showing the relationship between a tenant's average moving speed and a care degree.

Hereinafter, embodiments of the technical concept according to the present disclosure will be described with reference to the drawings. In the following description, the same components are denoted by the same reference numerals. Their names and functions are the same. Therefore, detailed description thereof will not be repeated.

[Technical Thought]
First, an outline of the technical idea disclosed in the present specification will be described. In a certain situation, the moving speed of the target person such as a resident of the facility is measured, and the daily state of the target person can be accurately grasped. The measurement is performed in a state where the subject is not conscious of the measurement. For example, there may be a case where the subject stops while moving or the speed becomes slow. Therefore, of the trajectory information (for example, a walking trajectory) obtained by the movement of the subject, only a trajectory having a distance equal to or more than a certain value can be an observation target. In a certain situation, a continuous trajectory is observed, and a trajectory whose start point and end point are near the bed or the bed is set as an observation target.

In another aspect, in order to exclude the trajectory information of a person other than the resident (for example, a caregiver, a nurse, other staff, a family member, etc.), a person other than the resident who may enter each room of the facility is excluded. The walking speed is measured in advance, and trajectory information in which walking at a certain speed or more is observed can be excluded from the observation target.

In yet another aspect, when a person other than the resident (for example, a staff member, a family member, etc.) enters the room, the person can wear the signal transmitter. The signal transmitter may emit a predefined identification number. The signal may be associated with the person's walking trajectory at that time. By doing so, the walking locus assigned the identification number can be excluded from the walking locus of the resident, so that the walking locus of the resident can be extracted. The information associated with the walking locus is not limited to the identification number, and may be data that is predetermined as a flag indicating entry.

[Configuration of watching system]
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. In the watching system 100 in FIG. 1,

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. In the example of FIG. 1, the number of living rooms included in the watching system 100 is two, but the number is not limited to this.

In the watching system 100, the sensor boxes 119 installed in the

living rooms

110 and 120, the management server 200 installed in the management center 130, and the access point 140 are connected via the network 190. Network 190 may include both an intranet and the Internet.

In the watching system 100, 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. In the

living rooms

110 and 120, 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. One example of a sensor is a Doppler sensor for detecting the movement of an object. Another example is a camera. The sensor box 119 may include both a Doppler sensor and a camera as sensors.

With reference to FIG. 2, the components of the watching system 100 will be described. FIG. 2 is a block diagram showing an outline of the configuration of the watching system 100.

[Sensor box 119]
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.

(4) 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.

アンテナ 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. By using the near-infrared camera, an image representing the inside of the

living room

110 or 120 can be captured even at night. In another implementation, camera 105 is a surveillance camera that receives only visible light. In still other implementations, 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. In one example, 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. For example, 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.

[Behavior information]
The above behavior information will be described. The action information is, for example, information indicating that the

residents

111 and 121 have performed a predetermined action. In one example, the predetermined action is “wake up” indicating that the

resident

111, 121 has occurred, “leaving” indicating that the

resident

111, 121 has left the bed (bedding) 113, and the

resident

111, 121 It includes four actions of “fall” indicating that the resident has fallen from the bed (bedding) 113 and “fall” indicating that the

resident

111 or 121 has fallen.

In one embodiment, 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. Hereinafter, a specific example of the generation of the behavior information will be described in more detail.

First, 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.

When the position of the head extracted as described above moves from within the area where the bed 113 is located to outside the area where the bed 113 is located, the control device 101 controls the size of the head extracted as described above. When it is detected that the head has changed from a certain size to a standing posture size by applying the second threshold value Th2, it may be determined that the action “getting out of bed” has occurred.

When the position of the head extracted as described above moves from within the area where the bed 113 is located to outside the area where the bed 113 is located, the control device 101 controls the size of the head extracted as described above. When it is detected that the head has changed from a certain size to a recumbent posture by applying the third threshold value Th3, it may be determined that the action “fall” has occurred.

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.

As described above, in one specific example, the control device 101 of the sensor box 119 generates the behavior information of the

residents

111 and 121. In the watching system 100 according to another aspect, an element other than the control device 101 (for example, 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.

[Mobile terminals 143 and 144]
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. In one aspect, the

mobile terminals

143 and 144 are realized as, for example, a smartphone, a tablet terminal, a wristwatch-type terminal, or another wearable device.

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.

アンテナ 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.

[Cloud Server Configuration]
The configuration of the cloud server 150 will be described with reference to FIG. 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 for executing a program, a mouse 2 and a keyboard 3 for receiving 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 Alternatively, 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. Alternatively, 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.

各 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.

プログラム 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.

[Device Configuration of Watching System 100]
With reference to FIG. 4, watching using the watching system 100 will be described. 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. When the sensor box 119 has the above-mentioned Doppler sensor, the Doppler sensor detects a person's behavior that has occurred within the range 410. When 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. In the example of FIG. 4, 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. As an example, 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).

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.

Note that 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.

[Classification of locus]
With reference to FIG. 5, the types of trajectories in the living room will be described. FIG. 5 is a diagram illustrating a difference between a walking locus of a resident of the room 110 according to a certain situation and a walking locus of a non-resident. In the living room 110, a closet 112, a bed 113, a toilet 114, a sink 51, and a desk 52 are arranged.

(5) As shown in the scene (A) of FIG. 5, two walking

trajectories

510 and 520 are detected from the result of the image processing observed during a certain period of a certain day. The walking locus 510 starts from the bed 113, reaches the toilet 114, and returns to the bed 113 again. The walking locus 520 starts from the door 109, heads toward the bed 113, and returns to the door 109 again.

Therefore, in a certain situation, it is possible to classify the person who has performed the walk indicated by the walking locus according to the starting point, destination (or turning point) or end point of the walking locus. For example, as shown in the scene (B), a person who has walked starting from the bed 113, arriving at the toilet 114 and returning to the bed 113 is estimated to be a resident. As shown in the scene (C), a person who starts walking from the door 109, reaches the bed 113, and walks as a trajectory returning to the door 109 is estimated to be a person other than the resident, such as a care staff. You.

[data structure]
The data structure of the cloud server 150 will be described with reference to FIG. FIG. 6 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. More specifically, the table 60 includes a room ID (Identification) 61, a date and time 62, an X coordinate value 63, and a Y coordinate value 64. The room ID 61 identifies the resident's room. The date and time 62 identifies the date and time when the signal sent from the sensor was obtained. The X coordinate value 63 indicates the X coordinate value of the point detected at the date and time. The Y coordinate value 64 indicates the Y coordinate value of the point detected at the date and time. In one aspect, the coordinate axes from which the X coordinate value and the Y coordinate value are based are defined, for example, with reference to the end point of the living room (for example, one corner of the room). In another aspect, the coordinate axis may be defined based on a certain point in the facility where each living room is provided.

For example, the XY coordinate values acquired based on the output from the Doppler sensor 106 or the camera 105 in the sensor box 119 and the date and time of the acquisition are periodically transmitted to the cloud server 150. In another aspect, data transmitted from the sensor box 119 may be stored in the management server 200 as well.

[Operation Overview of CPU 1]
In a certain situation, the CPU 1 represents a walking locus of a person in a living room, and acquires a plurality of locus data acquired on different days. Based on the walking characteristics of the resident of the room or the walking characteristics of the occupants other than the resident, the CPU 1 includes trajectory data of the occupants other than the resident in the room from among the plurality of acquired trajectory data, and trajectory data of the resident. Is determined. The CPU 1 calculates the walking speed of the resident in the room using the trajectory data of the resident after the determination.

In a certain situation, when the starting point and the ending point of the trajectory are near the bed, the CPU 1 may determine the trajectory as the trajectory of the resident. More specifically, the CPU 1 determines, as the resident's trajectory data, trajectory data in which the starting point and the ending point of the trajectory are in the vicinity of the bed 113 arranged in the room from among the plurality of trajectory data.

In a certain situation, the CPU 1 excludes, from the plurality of acquired track data, the track data corresponding to the walking speed measured in advance as the walking speed other than the resident from the plurality of track data. Thus, the CU 1 can extract the walking locus of the resident.

In a certain situation, the CPU 1 determines, as the trajectory data of the resident, the trajectory data of a predetermined time as a time zone in which only the resident is in the room among the plurality of acquired trajectory data.

局面 In a certain situation, the CPU 1 outputs a proposal to urge the review of the degree of care of the resident based on the result of the calculation of the walking speed. For example, for each resident, the CPU 1 can present a numerical value or a graph indicating a change in a walking locus on the monitor 8 or output the numerical value or a graph to a printer (not shown). This allows the caregiver, the care manager, and other managers, for example, to review the care determination for each resident based on objective data, thereby ensuring fairness and consent in the content of the determination. obtain.

[Movement speed of residents and staff]
With reference to FIG. 7, the difference between the moving speed of the resident and the moving speed of the staff will be described. FIG. 7 is a diagram illustrating a distribution of a moving speed of a person calculated for each trajectory. In FIG. 7, walking trajectories of 20 people are specified, and an average moving speed is calculated from data of each walking trajectory. Of these, the moving speeds specified by the

trajectory numbers

5, 7, 11, 14, 16 and 19 are respectively faster than 800 mm / sec, and the other trajectory numbers 1 to 4, 6, 8 to 10, 12, and The movement speeds identified at 13, 15, 17, 18 and 20 are each less than 600 millimeters / second. Therefore, it is clear that there is a difference between the distribution of the moving speed of non-residents such as nursing staff and the distribution of the moving speed of the resident, and the speed separating each distribution is defined as a threshold. obtain. For example, in the example of FIG. 7, 700 mm / sec may be a candidate for the threshold.

In some aspects, the management server 200 may display a distribution map as shown in FIG. 7 based on the average walking speed data calculated by the cloud server 150. The user of the management server 200 (for example, a care facility manager or a care manager) can objectively check the transition of the walking ability of each resident while looking at the distribution map.

[Data processing]
With reference to FIG. 8, data processing in the cloud server 150 will be described. FIG. 8 is a flowchart showing a part of the process executed by CPU 1 of cloud server 150.

In step S810, CPU 1 detects an input of the data processing mode. For example, when the staff operates the management server 200 and selects the data processing mode, the result of the selection is sent to the cloud server 150, and the cloud server 150 switches the operation mode to the data processing mode.

In step S820, the CPU 1 indicates a walking locus of a person in the living room and reads a plurality of locus data acquired on different days. For example, when the staff designates a date and time and instructs to extract a walking locus, the CPU 1 extracts data of a walking locus detected at the designated date and time from the table 60 of the hard disk 5.

In step S830, the CPU 1 determines, based on the walking characteristics of the resident of the room or the walking characteristics of the occupants other than the resident, the trajectory data of the occupants other than the resident in the obtained plurality of trajectory data, Determine the data. More specifically, the CPU 1 determines the walking locus of the resident and the walking locus of the staff from the walking locus of each resident and each staff based on the starting point of the walking locus (for example, see FIG. 5).

In step S840, CPU 1 calculates the walking speed of the resident in the room using the locus data of the resident after the determination. For example, the CPU 1 calculates an average walking speed based on the coordinate values of each point constituting the walking locus and the date and time when the point was extracted.

In step S850, CPU 1 outputs the resident identification information and the walking speed. For example, upon calculating each walking speed, the CPU 1 transmits the identification information of the resident and the calculation result to the management server-200. Upon receiving the identification information and the calculation result, the management server 200 displays these data on the monitor 8 (for example, FIG. 7). Alternatively, the management server-200 can output a form including these data to a printer or a file. The staff and other caregivers can objectively judge the transition of the walking ability of each resident by looking at the output data.

[Decrease in walking speed]
With reference to FIG. 9, transition of the walking speed according to a certain situation will be described. FIG. 9 is a diagram showing transition of the walking speed of five residents at a certain nursing home for six months. In one aspect, the monitor 8 of the management server 200 or the display 226 of the

mobile terminals

143, 144 may display the graph shown in FIG.

For example, for the resident 910, it can be seen that the degree of the decrease has been moderate after the walking speed has rapidly decreased from June 2017 to August 2017. As for the

residents

920, 930, and 940, it can be seen that the walking speed decreases at a constant rate, but the rate of decrease differs depending on the resident. For the resident 950, the walking speed once increased from June to July 2017, decreased until October 2017, and then increased again. Therefore, for example, it is presumed that the speed of decrease in walking is suppressed by walking training or the like. Therefore, the staff may use another example such as the resident 950 to recommend rehabilitation to other resident, for example.

[Walking speed and care level]
With reference to FIG. 10, the relationship between the average moving speed and the care degree will be described. FIG. 10 is a diagram illustrating a relationship between the average moving speed of the resident and the degree of care. In a certain situation, it is estimated that there is some correlation between the care degree and the average moving speed. For example, when the degree of care increases, walking tends to be inconvenient and the average moving speed is considered to decrease. Therefore, for each resident, by plotting the average moving speed of the resident for each care level that has already been certified, caregivers can objectively determine whether or not the current recognition of the care level is appropriate. Can be determined. For example, the average speed of the residents included in the group 1010 is lower than the threshold 1020, and it is estimated that the walking speed has decreased. Accordingly, the management server 200 may display on the monitor 8 that the recognition of the degree of care of the resident included in the group 1010 is to be changed, as one proposal.

As described above, according to the present embodiment, the walking locus observed in the living room of the facility is divided into the walking locus of the resident and the walking locus of a person other than the resident. By using the walking locus of the resident, it is possible to objectively grasp the change in walking speed. Since information required for nursing care is objectively provided, a fair and highly conclusive judgment can be made. Further, since the walking trajectory is derived using the data collected daily, quick data processing is possible, and information necessary for the determination can be provided in a short time.

The embodiments disclosed this time are to be considered in all respects as illustrative and not restrictive. The scope of the present invention is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

技術 This technology is applicable to information obtained in hospitals, nursing homes, nursing homes and other facilities.

100 system, 101,221 control device, 106 Doppler sensor, 107 wireless communication device, 108 storage device, 109 door, 110,120 living room, 111, 121, 910, 920, 930, 950 resident, 112 closet, 113 bed, 114 toilet, 115 care call handset, 116 toilet sensor, 117 sensor, 118 door sensor, 119 sensor box, 130 management center, 140 access point, 141, 142 caregiver, 143, 144 mobile terminal, 150 cloud server, 190 network, 200 management server, 226 display, 229 input device, 241 care call button, 290 vital sensor, 300 computer system, 4 0 range,

basin

51, 52 desks, 60 tables, 510 and 520 walk locus.

Claims

A program executed on a computer, wherein the program is stored in the computer,
Representing a walking locus of a person in the living room, and acquiring a plurality of locus data acquired on different days;
Based on the walking characteristics of the resident of the living room or the walking characteristics of the other than the resident, the trajectory data other than the resident in the living room and the trajectory data of the resident are determined from the plurality of acquired trajectory data. Steps to
Calculating the walking speed of the resident in the room using the trajectory data of the resident after the determination.
The determining step includes, among the plurality of trajectory data, determining trajectory data in which a start point and an end point of the trajectory are near a bed arranged in the living room, as trajectory data of the resident. The program according to claim 1.
The step of determining includes excluding, from the plurality of acquired trajectory data, trajectory data corresponding to a walking speed defined as a walking speed other than the resident from the plurality of trajectory data. Item 2. The program according to Item 1.
The determining step includes, among the plurality of acquired trajectory data, determining trajectory data of a predetermined time as a time zone in which only the resident is in the living room, as trajectory data of the resident. The program according to claim 1, comprising:
4. The program according to claim 1, wherein the program further causes the computer to execute a step of outputting a proposal for prompting a review of a resident's care degree based on a result of the calculation of the walking speed. 5.
Memory and
A processor coupled to the memory,
The processor is
Representing the walking trajectory of a person in a living room, acquiring a plurality of trajectory data acquired on different days,
Based on the walking characteristics of the resident of the living room or the walking characteristics of the other than the resident, the trajectory data other than the resident in the living room and the trajectory data of the resident are determined from the plurality of acquired trajectory data. And
An information processing apparatus configured to calculate a walking speed of a resident in the room using trajectory data of the resident after the determination.
The processor according to claim 6, wherein the processor determines, as the resident's trajectory data, trajectory data in which the starting point and the ending point of the trajectory are near the bed arranged in the living room among the plurality of trajectory data. Information processing device.
The processor according to claim 6, wherein the processor excludes, from the plurality of pieces of track data, track data corresponding to a walking speed measured in advance as a walking speed other than the resident from the plurality of track data. Information processing device.
7. The processor according to claim 6, wherein, among the plurality of acquired trajectory data, the trajectory data of a predetermined time as a time zone in which only the resident is in the room is determined as the occupant's trajectory data. An information processing apparatus according to claim 1.
7. The information processing device according to claim 6, wherein the processor is further configured to output a proposal for prompting a review of a resident's care degree based on a result of the calculation of the walking speed.
A method executed on a computer, the method comprising:
Representing a walking locus of a person in the living room, and acquiring a plurality of locus data acquired on different days;
Based on the walking characteristics of the resident of the living room or the walking characteristics of the other than the resident, the trajectory data other than the resident in the living room and the trajectory data of the resident are determined from the plurality of acquired trajectory data. Steps to
Calculating the walking speed of the resident in the room using the occupant trajectory data after the determination.
The determining step includes, among the plurality of trajectory data, determining trajectory data in which a start point and an end point of the trajectory are near a bed arranged in the living room, as trajectory data of the resident. The method according to claim 11.
The step of determining includes excluding, from the plurality of acquired trajectory data, trajectory data corresponding to a walking speed defined as a walking speed other than the resident from the plurality of trajectory data. Item 12. The method according to Item 11.
The determining step includes, among the plurality of acquired trajectory data, determining trajectory data of a predetermined time as a time zone in which only the resident is in the living room, as trajectory data of the resident. The method of claim 11, comprising:
The method according to claim 11, further comprising: outputting a proposal for prompting a review of the degree of care of the resident based on a result of the calculation of the walking speed.