JP4185846B2 - Activity state determination device, watching support system, and activity state determination method - Google Patents

Description

  The present invention relates to an activity state determination device and an activity state determination method for determining an activity state of an elderly person or an inpatient, and a watch support system for watching the activity state of an elderly person or an inpatient.

It has become important for bedridden prevention and physical condition management to understand the amount of activity and sleep state of elderly people in elderly facilities, hospitals, and living alone elderly homes. At this time, it is effective to measure an individual's activity amount, and conventionally, an individual's activity amount was determined by visual observation by a person. On the other hand, in recent years, the amount of activity of an individual is measured using an acceleration sensor that measures the amount of exercise, a pyroelectric sensor that detects the movement of a person without contact, or the like.
Patent Document 1 proposes an example of a device that measures momentum. This equipment measures the speed of movement, the magnitude of vibration, and the time due to exercise, and combines the measurement results with personal data such as the age and weight of the subject to calculate the exercise intensity by using the exercise intensity coefficient. ing. The calculation result is displayed as a graph or the like on the display means, and prompts the subject to perform health management.

On the other hand, Patent Documents 2 and 3 propose systems for grasping human activity patterns. In these systems, pyroelectric sensors are installed in each room of the subject's house, and when this sensor detects the subject's movement and determines that some abnormality has occurred in the behavior, it is remotely connected via a telephone line. Report to nurses and specialists. In these Patent Documents 2 and 3, it is described that the number of operations and the operation time are output from a sensor for detecting movement to grasp the daily pattern and athletic ability of the subject.
Furthermore, Patent Document 4 proposes an example of an apparatus that determines sleep. This determination apparatus extracts a heartbeat signal with an air mat sensor placed on the bedding, and uses the disturbance of the heartbeat signal waveform or a change in respiration.
JP-A-7-289540 JP-A-10-91879 JP 2002-197571 A JP 2001-258855 A

Such a conventional system for grasping the activity pattern of a person was able to calculate the amount of exercise and the number of movements and display it on a graph etc. with a display means, but only with the absolute value of the amount of movement and the number of movements of the sensor, Even if the degree of increase / decrease in the amount of exercise could be grasped, the behavior of the subject, particularly the difference between sleep and awakening, could not be estimated.
In addition, it is difficult for the staff of the elderly facilities without medical knowledge and the specialists of the call center to be notified to analyze the graph itself. Therefore, it was necessary to arrange specialized staff with experience enough to understand the meaning of the waveform of the graph and visually analyze the data of each subject. Therefore, there has been a problem that it is not possible to cope with an increase in the number of subjects who provide services at the call center, and there are individual differences among the persons who analyze the analysis results.

  Moreover, in the mat | matte sensor disclosed by patent document 4, it is necessary for a subject to be in the bedding which installed the sensor. For this reason, there is a problem that the amount of activity during the day cannot be taken and a minute signal such as a heartbeat signal is extracted, so that it is vulnerable to noise and accurate sensor information cannot be collected.

  The present invention has been made to solve such problems, and provides an activity state determination device, a watch support system, and an activity state determination method that can easily determine a sleep state and a wake state. With the goal.

  An activity state determination device according to the present invention is an activity state determination device that collects body motion data indicating body motion of a subject and grasps the activity state of the subject, and is an absolute body motion amount indicating the body motion data. Data accumulation means for accumulating values, and a difference value calculation means for obtaining a body movement amount absolute value accumulated in the data accumulation means and calculating a body movement amount difference value for each predetermined time from the obtained body movement amount absolute value; The activity state analyzing means for analyzing the activity state of the subject based on the transition of the body motion amount absolute value stored in the data storage means and the transition of the body motion amount difference value calculated by the difference value calculating means It is equipped with.

Further, the activity state analyzing means may determine whether the subject is based on a duration in which the body movement amount absolute value is less than or equal to a first threshold value and a duration in which the body movement amount difference value is less than or equal to a second threshold value. It is possible to determine whether or not the patient is in a sleep state.
In such a configuration, the activity state analysis means can accurately determine the sleep state using the first and second threshold values, and therefore, the sleep state can be easily determined based on the determination result. .

Further, the activity state analyzing means is configured to determine whether the body movement amount absolute value exceeds the first threshold value and the body movement amount difference value exceeds the second threshold value. It can be determined whether or not is in an awake state.
In such a configuration, the activity state analyzing means can accurately determine the wakefulness state using the first and second threshold values, so that the wakefulness state can be easily determined based on the determination result. .

  The activity state determination apparatus according to the present invention further includes an integral value calculating unit that acquires the body movement amount data stored from the data storage unit and calculates an integral value within a predetermined time from the acquired body movement amount data. It is a thing. In such a configuration, since the sleep state and the awake state can be reliably determined as described above, the activity amount of the subject in the awake state can be easily calculated. Thereby, it is possible to easily grasp the change of the target person in the active state.

Furthermore, the activity state determination apparatus according to the present invention may further include an output unit that outputs an analysis result by the activity state analysis unit, and a storage unit that stores an output result output by the output unit. As a result, it is possible to output the subject person in an easily understandable state of activity or changes in the activity state.
Further, in such a configuration, the absolute value of body movement at different time points such as yesterday and today can be output at the same time, so that the activity state of the subject can be output in a more understandable manner in parallel with the comparison target. .

The watching support system according to the present invention includes a sensor device that detects a subject's body movement and outputs the body movement amount data, and an activity state determination device as described above that collects the body movement amount data from the sensor device. The sensor device has communication means connectable to a public line network, and the activity state determination device obtains the body movement data by connecting to the public line connection means at a preset time. The data is stored in the data storage means.
In such a configuration, since the activity state determination device is used, the sleep state and the awake state can be accurately determined, and the sleep state and the awake state can be easily determined based on the determination result.

  The activity state determination method according to the present invention is an activity state determination method for collecting body movement amount data indicating the body movement of a subject and grasping the activity state of the subject person, wherein the body movement amount indicating the body movement amount data A step of accumulating an absolute value in a storage means, a step of acquiring the accumulated body motion amount absolute value, calculating a body motion amount difference value for each predetermined time from the acquired body motion amount absolute value, and the accumulated Analyzing the activity state of the subject based on the transition of the body movement amount absolute value and the transition of the calculated body movement amount difference value.

Further, the step of analyzing the activity state of the subject is based on a duration in which the absolute amount of body movement is less than a first threshold and a duration in which the difference in body movement is less than a second threshold. Determine whether the subject is in a sleep state.
In such a configuration, since the sleep state can be accurately determined using the first and second threshold values, the sleep state can be easily determined based on the determination result.

Furthermore, the step of analyzing the activity state of the subject includes a duration in which the absolute value of the body movement exceeds the first threshold and a duration in which the difference in the body movement exceeds the second threshold. Based on this, it is determined whether or not the subject is awake.
In such a configuration, the activity state analyzing means can accurately determine the wakefulness state using the first and second threshold values, so that the wakefulness state can be easily determined based on the determination result. .

  In addition, the activity state determination method according to the present invention includes a step of acquiring the accumulated body movement amount data and calculating an integrated value within a predetermined time from the acquired body movement amount data. In such a configuration, since the sleep state and the awake state can be reliably determined as described above, the activity amount of the subject in the awake state can be easily calculated. Thereby, it is possible to easily grasp the change of the target person in the active state.

  Furthermore, the activity state determination method according to the present invention includes a step of outputting a result analyzed by the step of analyzing the activity state of the target person and a step of storing the output result to be output. Thereby, since the absolute value of the amount of body movement at different time points such as yesterday and today can be output at the same time, the activity state of the subject can be output more easily while being parallel to the comparison target.

  ADVANTAGE OF THE INVENTION According to this invention, the active state determination apparatus, watching support system, and active state determination method which can determine a sleep state and a wakeful state easily can be provided.

The monitoring support system according to the present invention collects biological information such as the amount of activity of the human body, and determines the health state of the elderly and hospitalized patients by judging the sleep state and activity state of the human body based on the collected biological information. It is something to watch.
The best mode for carrying out the present invention will be described below with reference to the drawings.

Embodiment 1 of the Invention
First, the overall configuration of the watching support system according to the present invention will be described. FIG. 1 shows a configuration example of this watching support system. In FIG. 1, the watching support system according to the present invention is generally indicated by reference numeral 10. As shown in FIG. 1, the watching support system 10 includes a sensor device 1 and a determination device 2.

The sensor device 1 is a human-mounted sensor device that is worn on the arm of a patient who is a subject like a wristwatch, and measures and transmits the amount of activity of the subject wirelessly. In addition, if the sensor device 1 is a wristwatch type capable of wireless communication and wearable, body motion data can be collected throughout the day without disturbing the behavior of the subject.
As shown in FIG. 1, the determination device 2 includes a personal computer 3 (hereinafter referred to as a personal computer 3) and a reception device 4. The receiving device 4 receives the measurement result of the sensor device 1 transmitted wirelessly and outputs it to the personal computer 3. The personal computer 3 receives the signal from the receiving device 4 and manages the data. For example, the determination device 2 is installed in a call center or the like. The receiving device 4 and the personal computer 3 may perform data transmission by wire, and the personal computer 3 inputs data from the receiving device 4 from a serial port.

Next, the sensor device 1 and the determination device 2 of the watching support system 10 according to the present invention will be described in detail. Here, first, the internal configurations of the sensor device 1 and the determination device 2 will be described in order, and then the operation of the determination device 2 will be described.
An example of the internal configuration of the sensor device 1 is shown in the block diagram of FIG. In FIG. 2, 11 is a power supply unit, 12 is a body motion sensor, 13 is a sensor signal processing means, 14 is an analysis means, and 15 is a wireless transmission means.
The power source unit 11 is a power source such as a battery, and drives the sensor device 1 by this.
The body motion sensor 12 is a sensor that detects the amount of movement of the arm, such as an acceleration sensor, and preferably detects motion in three axial directions. The output of the body motion sensor 12 is input to the sensor signal processing means 13.
Based on the output signal of the body motion sensor 12, the sensor signal processing means 13 calculates the amount of movement in which direction by integration or the like, and transmits the calculation result to the analysis means 14.

Based on the calculation result of the sensor signal processing means 13, the analysis means 14 analyzes the total amount of movement every predetermined time, converts this analysis result into digital data, and transmits the digital data to the wireless transmission means 15. For example, the analysis unit 14 sets the total amount of movement to five levels, and classifies it as “0” when there is no movement, “100” when movement is severe, and the like. In addition, since the output from the analysis means 14 is transmitted at predetermined time intervals, it is not necessary to transmit the sensor signal at all times, and no interference occurs even when a plurality of sensor devices 1 are used.
The wireless transmission unit 15 adds the ID number that identifies the sensor device 1 to the result of the body movement amount data of the analysis unit 14 and transmits the result wirelessly. The ID number unique to the sensor device 1 is stored in a nonvolatile memory (not shown).

An example of the internal configuration of the determination device 2 is shown in the block diagram of FIG.
The reception device 4 of the determination device 2 receives the data transmitted from the wireless transmission means 15 of the sensor device 1. The receiving device 4 demodulates the received signal received from the wireless transmission means 15, converts it to a data format to be transmitted to the personal computer 3, and transmits the converted data to the personal computer 3.
In addition, the receiving device 4 may be installed in each hospital room and connected by a wired line, or the wireless transmission unit 15 of the sensor device 1 may be selected to have a large transmission output and receive a radio signal from each hospital room. Thus, it may be installed only near the personal computer 3 and connected by a transmission line such as RS-232C.

  In FIG. 3, 21 is a registration means, 22 is a data storage means, 23 is a difference value calculation means, 24 is an activity state analysis means, 25 is an output means, and 26 is a threshold setting means. The determination device 2 has such various means, and these various means are physically realized using hardware such as a CPU, ROM, RAM, hard disk drive, mouse, and keyboard. Further, various application programs are installed in the determination device 2, and the calculation processing and analysis processing described below are realized on the various hardware by the programs.

  The registration means 21 is input by the staff or the like from the screen of the personal computer 3 with a mouse or a keyboard. The data storage unit 22 is connected to the receiving device 4 and is connected to the difference value calculation unit 23 and the activity state analysis unit 24. The activity state analyzing unit 24 is connected to the data accumulating unit 22 and the difference value calculating unit 23, receives various data related to body movement, and outputs the analysis result to the output unit 25. The threshold value setting means 26 is input from the registration means 21 and connected to the activity state analysis means 24 to output various threshold values.

Next, the operation of the determination device 2 will be described with reference to FIG. FIG. 4 is a flowchart showing a processing flow of the determination device 2. Here, the operation of the determination apparatus 2 will be described using FIGS. 5 to 9 as appropriate.
As shown in FIG. 4, the staff of the facility that manages the health of the subject first registers various data in advance in the registration means 21 using a keyboard or the like (S101). The registered data can be a unique ID number of the sensor device 1 used by the subject, or personal information such as the name and age of the subject. Furthermore, various threshold values required for analysis by the activity state analysis means 24 and time for analysis are set as registration information.

The registered ID number of the sensor device 1 is transmitted to the data storage means 22, and the data storage means 22 receives only the body movement amount data of the sensor device 1 related to the ID number registered in advance. The data storage means 22 is always in a standby state for reception (S102), and is waiting for body movement amount data from the receiving device 4 to the sensor device 1.
When the data storage unit 22 receives data from the receiving device 4, the data storage unit 22 extracts the ID number of the sensor device 1 added to the body movement amount data and confirms whether it is registered in the registration unit 21 in advance. If an unregistered ID number or ID number itself is not added, the data storage means 22 determines that the data is garbled due to noise or the like, or is data of another device, and the data is stored. Discard. If the ID number is registered, the data storage means 22 receives the data (S103) and stores data for each ID number (S104).

  FIG. 5 shows an example of the absolute value data of the body movement amount stored in the data storage means 22. The absolute value data of the amount of body movement shown in FIG. 5 is a form of data output to the output means 25 in which data indicating a certain amount of body movement is arranged in time series. In FIG. 5, the vertical axis represents the value of the digital data converted by the analysis means 14 of the sensor device 1, and the horizontal axis represents the collected time. The absolute value data of the body movement amount can be read from the data storage unit 22 for each subject. Furthermore, it is possible to specify the period of the absolute value data of the body movement amount to be displayed. Here, the absolute value of the body movement amount data indicates the body movement amount data itself indicating the body movement.

  When the analysis time registered in the registration unit 21 is reached (S105), the activity state analysis unit 24 and the difference value calculation unit 23 automatically read data from the data storage unit 22 and start analyzing the data (S106). ). The difference value calculation means 23 that has read the data uses the time series data of the data storage means 22 to calculate a difference value for each predetermined time (S107). For example, when the analysis unit 14 of the sensor device 1 analyzes the total amount of body movement and wirelessly transmits it for one minute, the data accumulation unit 22 stores body movement amount data every minute. The difference value calculation means 23 also calculates the same difference in body movement data every minute.

FIG. 6 shows an example of the body motion amount difference value calculated from the time, the body motion amount absolute value, and the body motion amount absolute value. The body movement amount difference value shown in FIG. 6 is a value of + (plus) and − (minus) because it takes a difference from the previous data. In FIG. 6, the difference is taken every minute, but may be calculated every two minutes, and further, by dividing by two, differentiation every minute can be obtained.
The difference value of the amount of body movement indicates a change in the movement of the subject for each predetermined time. For example, when shifting to sleep or losing consciousness due to falling or the like, the difference value of the amount of body movement appears as a large value on the minus side because the body movement suddenly disappears. On the other hand, at the start of exercise such as transition from sleep to awakening, turning over, or rehabilitation, the difference value of the amount of body movement appears as a large value on the plus side because body movement suddenly appears. That is, it is possible to read the tendency of the subject's movement from the difference value of the amount of body movement, and when it is combined with information such as the time of occurrence, it is possible to estimate even the behavior of the subject.

FIG. 7 is a graph showing body movement amount absolute value data (FIG. 7 (a)) and body movement amount difference value data (FIG. 7 (b)) generated by the difference value calculation means 23 and the activity state analysis means 24 as time series data. An example is shown. In FIG. 7, the absence of data after 10:00 means that the analysis time is set to 10:00 in the registration means 21, and the data accumulation means 22 accumulates before 10:00. Analyzing data.
In the case of this subject, the absolute value of the body movement amount decreases around 21:00 on the previous day, the body movement amount difference value suddenly appears on the negative side, and thereafter the body movement amount difference value becomes a small value. Yes. From this, it is presumed that the subject has shifted to the sleep state around 21:00 on the previous day.
However, it is difficult for a nursing staff who does not have medical knowledge such as sleep to determine whether or not it is sleep only by looking at the graph shown in FIG. Moreover, even if sleep is estimated, it is laborious to analyze the graphs of all subjects every day. Therefore, in the present invention, in order to solve such a problem, it is possible to provide support for staff and the like so as to watch over the target person by automating the determination of sleep and awakening.

Various threshold values are input from the registration means 21 to the threshold setting means 26. FIG. 8 shows an example of a threshold setting screen for automating the determination of sleep and arousal states. In FIG. 8, four threshold values S1, S2, T1, and T2 can be set.
S1 is a threshold value of the body movement amount absolute value, and is a guideline for determining a sleep state when the body movement absolute value is lower than S1.
S2 is a threshold value of the body movement amount difference value, and is a guideline for determining the sleep state when the body movement difference value is lower than S2. Conventionally, whether the sleep or awakening is determined only by the threshold value S1 of the absolute value of the body movement amount, but it is difficult to set the threshold value for a subject who has a small amount of body movement from the daily life. The difference value of the amount of body movement indicates the amount of movement of body movement, and also serves as a guideline for measuring the calmness and rest of the subject. From this, it is possible to determine sleep more accurately by providing the threshold value S2 of the body movement amount difference value. In addition, the fact that the difference value of the body motion appears greatly negative can be added to the sleep determination criterion, and can be determined to be sleep when the subsequent difference value is S2 or less.

T1 is a time threshold value. When judging the sleep state from the awake state, T1 sleeps when the state where the absolute value of the body motion amount is S1 or less and the body motion amount difference value is S2 or less continues for T1 or more. It is to be judged. Therefore, when either the absolute value of the body motion amount or the difference value of the body motion amount exceeds the threshold value within T1, the sleep is not determined. This takes into account that the amount of body movement is reduced even when a person is not constantly moving and is resting.
T2 is determined to be arousal when a state in which the absolute value of the body motion is S2 or more and the body motion amount difference value is S2 or more continues for judging the awake state from the sleep state. This is because body movements caused by turning over at night and the like are not determined to be awake.

  The activity state analysis unit 24 reads the absolute value data of the body movement amount from the data storage unit 22 and acquires the difference value data from the difference value calculation unit 23. Further, the activity state analyzing unit 24 acquires various threshold values from the threshold setting unit 26, and compares each of the threshold values with the absolute value data and the difference value data of the body movement amount (S108).

  FIG. 9 shows an example of sleep determination based on a determination criterion using such a threshold value. In FIG. 9, the amount of body movement decreased around 22:00, the body movement amount absolute value and the body movement amount difference value were within the threshold values S1 and S2, respectively, and the state continued for T1 or more. From this, it is determined that the subject is sleeping after about 22:00. Here, the amount of body movement of the subject increases rapidly after 02:00, but the time t1 exceeding the thresholds S1 and S2 is equal to or less than the threshold T2 for determining the awake state from the sleep state. From this, it is determined that the subject is turning over, and it is determined that the subject is not awake. On the other hand, the amount of body movement similarly appears around 04:00, and the time t2 when the threshold values S1 and S2 are exceeded is equal to or greater than T2. From this, it is determined that the subject is awake. Such state determination indicating sleep and awakening is output from the output means 25 and displayed, for example, as shown in FIG. 9 (S109).

  In this way, since the transition between sleep and awakening is automatically determined, it is possible for the monitoring staff to grasp the sleep time of the target person without the expertise to analyze the waveform of the body movement data. . Furthermore, since it is possible to grasp the awakening at night, it is possible to infer the subject's behavior that the subject has woken up in the toilet or the like. In the above sleep determination, a case where sleep is determined when both S1 and S2 are satisfied as a criterion is shown, but sleep may be determined when only one is satisfied.

  As described above, according to the monitoring support system 10 according to the present invention, the determination device 2 calculates the difference value of the body movement amount data stored in the data storage unit 22 for each predetermined time, and calculates the absolute value of the body movement amount data. From the transition of the value and the difference value, the activity state of the subject is analyzed based on each threshold value. Therefore, it is not necessary to arrange specialized staff with experience to analyze the graph as in the past, and it is possible to judge not only increase / decrease of exercise amount but also sleep and awakening state for a large number of subjects It becomes possible.

  As described above, the present invention collects body movement data that can be easily sensed from a subject such as an elderly person as data, and displays not only the body movement amount data of the subject as an absolute value but also the accumulated body movement amount data. To analyze. This makes it possible to automatically extract the status of sleep and awakening and the trend of activity status and report the physical condition of the subject to the care staff and call center of the elderly facility. Can help.

Embodiment 2 of the Invention
Hereinafter, the monitoring support system 10 according to the second embodiment will be described with reference to the drawings.
In elderly facilities, etc., rehabilitation is provided to residents to help them return to their home life. The staff is required to check the resident's activity level (activity) on a daily basis, and to establish the effect of rehabilitation and future curriculum. Therefore, it is effective to constantly measure the amount of activity, accumulate data, and analyze it in a form that is easy for the staff to understand. The monitoring support system 10 according to the second embodiment analyzes until the staff can easily determine.

FIG. 10 shows another configuration example of the determination apparatus 2 according to the second embodiment. As shown in FIG. 10, the determination device 2 includes an integral value calculating unit 27 in addition to the above-described components. In FIG. 10, the same components as those in the first embodiment are denoted by the same reference numerals, and the description thereof is omitted here.
As shown in FIG. 10, the data storage unit 22 is connected to the integral value calculation unit 27 together with the difference value calculation unit 23. The integral value calculating means 27 calculates the integral value of the body movement amount at a predetermined time.

The analysis result by such a determination apparatus 2 is shown in the graph of FIG. In this graph, for example, the integrated value of the body movement amount for 24 hours is calculated, and in FIG. 11, the horizontal axis is the date. As a method for the integral value calculating means 27 to calculate the integral value, for example, all the absolute values of the body motion amount in one day may be added, or the sum of the body motion amounts for every hour may be taken. Furthermore, as in the first embodiment, it is also effective to determine sleep and awakening and calculate only the integral value when awakening.
Conventionally, when calculating the amount of daytime activity, daytime and night time can only be roughly divided by time, and calculation according to the life rhythm of sleep and awakening for each subject cannot be performed. In contrast, according to the present invention, since sleep and awakening can be automatically determined, it is possible to accurately calculate the amount of activity only at the time of awakening for each individual of the subject.

  The staff can easily grasp the change in the occupant's activity by looking at the transition graph of the integrated value shown in FIG. In addition, for example, by automatically determining that the activity is decreasing or increasing, and indicating it as a sound or a comment as an alarm, the staff can be aware and can respond quickly.

Furthermore, as shown in FIG. 10, the determination device 2 according to the second embodiment can include a storage unit 28 in addition to the above components and the integral value calculation unit 27.
By providing the storage unit 28 in the determination device 2, an operator such as a staff can store a body motion amount absolute value graph, a body motion amount difference value graph, a body motion amount integrated value graph, and the like serving as a reference for the subject.

The analysis result by such a determination apparatus 2 is shown in the graph of FIG. For example, this graph is obtained by superimposing the result of analysis of today (graph b), which is obtained by storing, as a reference graph, a past body movement absolute value graph (graph a) of a subject.
The storage unit 28 may store data for the past day, but by storing an average value for several days, the daily change in the amount of body movement related to the subject can be made more accurate as the rhythm of the person. Can be standard as high.
The staff can grasp the difference between the reference data and today's data on a daily basis by observing a graph of the data stored in the storage means 28. For example, in the graph shown in FIG. 12, it can be seen that the wake-up time is delayed by about one hour because the subject was awake at around 04:00 in the night. Furthermore, by calculating the deviation between the graph a and the graph b, it is possible to grasp how much the rhythm is broken compared to the normal case.

  As described above, according to the watching support system 10 according to the second embodiment, it is possible to calculate the integral value of the body movement amount and store and compare the life rhythm that is the reference of the subject. Therefore, by displaying the subject's physical condition and the like so that anyone can understand it, it is possible for the nursing staff and the like to respond quickly, and there is a great practical effect.

Embodiment 3 of the Invention
Hereinafter, the monitoring support system 10 according to the third embodiment will be described with reference to the drawings.
Understanding the sleep state and activity level of the elderly is effective not only for elderly facilities but also for subjects at home. In particular, there is a need to change the living environment by detecting as soon as possible withdrawals and lack of sleep, etc. of elderly people at home by a specialized call center and reporting them to nursing staff. However, in the past, there was no system that could automatically determine this information, so even if time series data for sensors that measure activity, such as pyroelectric sensors, were collected from the user's home, a specialized operator would then make a visual decision. Was. Therefore, there has been a problem that it is not possible to cope with an increase in the number of users. In the third embodiment, a monitoring system that solves such a problem and can handle even when the number of users increases will be described.

An example of an internal configuration of the sensor device 1 that realizes the third embodiment is shown in the block diagram of FIG. In FIG. 13, 16 is a public line connection means. The public line connection means 16 is connected to the analysis means 14.
The flowchart of FIG. 14 shows the flow of data collection and analysis of the determination apparatus 2 according to the third embodiment.

User information is registered in advance in the determination device 2 (S201). The user information includes, for example, the user's home address, telephone number, age, and emergency contact information. In addition, there is a care station that performs home visits as emergency contact information.
When a predetermined time comes, the determination device 2 selects a registered user's home (S202), and connects a telephone line to collect data (S203). The public line connection means 16 detects that a telephone call has been received, and transmits the body movement amount data analyzed by the analysis means 14 via the telephone line. The determination device 2 collects the body movement amount data transmitted from the public line connection unit 16, and the data storage unit 22 stores the collected body movement amount data (S204). The accumulated body movement amount data is processed by the difference value calculation means 23 and the integral value calculation means 27, and a difference value and an integration value of the body movement amount data are generated.

The activity state analysis unit 24 acquires the processed data from the difference value calculation unit 23 and the integral value calculation unit 27, and analyzes the sleep time and the activity amount (S205). If there is no problem as a result of this analysis, the same operation is repeated for the next user's house (S206). Here, for example, if it is determined that the problem is related to sleep disorders such as those who have not slept for the last few days, or activities such as the amount of activity decreasing, the registered data of the user is displayed. (S207).
After that, the activity state analyzing means 24 creates a report (S208) and reports the handling method to the operator. The contents of the report include, for example, data for the last month. The output means 25 notifies the caregiver who is performing home care so that the care support method can be examined.

  In this way, by providing the public line connection means 16 in the sensor device 1 and configuring the sensor device 1 to transmit the body movement amount data with periodic access from the determination device 2, the determination device 2 The activity state and sleep state of the subject can be collected periodically. Since the analysis result based on the collected data can be easily grasped even by a staff member who does not have specialized knowledge, the state of the subject can be easily and more accurately determined.

It is explanatory drawing which shows the example of 1 structure of the monitoring assistance system which concerns on Embodiment 1 of this invention. It is a block diagram which shows an example of the internal structure of the sensor apparatus which concerns on Embodiment 1 of this invention. It is a block diagram which shows an example of the internal structure of the judgment apparatus which concerns on Embodiment 1 of this invention. It is a flowchart which shows the processing flow in the judgment apparatus which concerns on Embodiment 1 of this invention. It is a graph which shows an example of the body movement amount absolute value of the judgment apparatus concerning Embodiment 1 of this invention. It is a figure which shows an example of the calculation result of the body movement amount difference value of the judgment apparatus which concerns on Embodiment 1 of this invention. It is a graph which shows an example of the output result of the judgment apparatus concerning Embodiment 1 of this invention. It is a figure which shows an example of the screen of the threshold value setting in the judgment apparatus which concerns on Embodiment 1 of this invention. It is a figure which shows an example of the judgment result of sleep and awakening of the judgment apparatus which concerns on Embodiment 1 of this invention. It is a block diagram which shows an example of the internal structure of the judgment apparatus which concerns on Embodiment 2 of this invention. It is a graph which shows an example of the calculation result of the body movement amount integral value of the judgment apparatus concerning Embodiment 2 of the present invention. It is a graph which shows an example of the output result of the memory | storage means of the determination apparatus which concerns on Embodiment 2 of this invention. It is a block diagram which shows an example of the internal structure of the sensor apparatus which concerns on Embodiment 3 of this invention. It is a flowchart which shows the processing flow in the judgment apparatus which concerns on Embodiment 3 of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Sensor apparatus 2 Judgment apparatus 3 Personal computer (personal computer) 4 Receiving apparatus 10 Watch support system 11 Power supply part 12 Body motion sensor 13 Sensor signal processing means 14 Analysis means 15 Wireless transmission means 16 Public line Connection means 21 Registration means 22 Data accumulation means 23 Difference value calculation means 24 Activity state analysis means 25 Output means 26 Threshold setting means 27 Integral value calculation means 28 Storage means

Claims (11)

An activity state determination device that collects body movement amount data indicating the body movement of the subject and grasps the activity state of the subject,
Data accumulating means for accumulating an absolute value of body movement amount indicating the body movement amount data;
A difference value calculating means for acquiring a body movement amount absolute value stored in the data storage means and calculating a body movement amount difference value for each predetermined time from the acquired body movement amount absolute value;
Activity state analysis means for analyzing the activity state of the subject based on the transition of the body movement amount absolute value accumulated in the data accumulation means and the movement of the body movement amount difference value calculated by the difference value calculation means; An activity state determination device. The activity state analyzing means includes
Whether the subject is in a sleep state is determined based on a duration in which the absolute value of the body movement amount is equal to or less than a first threshold value and a duration in which the difference value in the body movement amount is equal to or less than a second threshold value. The activity state determination apparatus according to claim 1, wherein: The activity state analyzing means includes
It is determined whether the subject is in an awake state based on a duration in which the body movement amount absolute value exceeds a first threshold value and a duration in which the body movement amount difference value exceeds the second threshold value. The activity state determination apparatus according to claim 1 or 2, wherein   2. The apparatus according to claim 1, further comprising: an integral value calculating unit that acquires body motion amount data stored from the data storage unit, and calculates an integral value within a predetermined time from the acquired body motion amount data. 3. The activity state determination device according to any one of 3 above. Output means for outputting an analysis result by the activity state analysis means;
5. The activity state determination apparatus according to claim 1, further comprising storage means for storing an output result output by the output means. A sensor device that detects body motion of a subject and outputs the body motion amount data, and an activity state determination device according to any one of claims 1 to 5 that collects the body motion amount data from the sensor device,
The sensor device has communication means connectable to a public network,
The activity state determination device is a watching support system in which the body movement amount data is acquired by connecting to the public line connection unit at a preset time, and is acquired and stored in the data storage unit. An activity state determination method that collects body movement amount data indicating the body movement of the subject and grasps the activity state of the subject,
Accumulating body movement amount absolute values indicating the body movement amount data in storage means;
Obtaining the accumulated body motion amount absolute value, and calculating the body motion amount difference value for each predetermined time from the acquired body motion amount absolute value;
An activity state determination method comprising: analyzing an activity state of the subject based on the transition of the accumulated body motion amount absolute value and the transition of the calculated body motion amount difference value. The step of analyzing the activity status of the subject is
Whether the subject is in a sleep state is determined based on a duration in which the absolute value of the body movement amount is equal to or less than a first threshold value and a duration in which the difference value in the body movement amount is equal to or less than a second threshold value. The activity state determination method according to claim 7. The step of analyzing the activity status of the subject is
It is determined whether the subject is in an awake state based on a duration in which the body movement amount absolute value exceeds a first threshold value and a duration in which the body movement amount difference value exceeds the second threshold value. The activity state determination method according to claim 7 or 8, characterized in that:   The activity according to any one of claims 7 to 9, further comprising a step of acquiring the accumulated body movement amount data and calculating an integral value within a predetermined time from the acquired body movement amount data. State judgment method. Outputting the result analyzed by the step of analyzing the activity state of the target person;
The activity state determination method according to claim 7, further comprising a step of storing the output result to be output.

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