Determination device

Abstract

A determination device (500) comprises: an estimation unit (521) which estimates the cause of an error, on the basis of data that is to be used in determining an agitated state; and a notification unit (522) which gives notice in accordance with the result of estimation by the estimation unit (521).

Description

[Technical field]

[0001] The present invention relates to a determination device, a notification method, and a recording medium. [Background technology]

[0002] When a patient becomes restless, there is an increased risk of extubation, needle removal, falling, etc., which may result in injury to the patient. Therefore, in order to reduce such risks and fears, a technology is known that detects signs of restlessness.

[0003] For example, Patent Document 1 is known as a document that describes a technology for determining a sign of agitation. Patent Document 1 describes a biometric information processing system that includes a determination unit and an estimation unit. According to Patent Document 1, the determination unit determines identification information indicating whether the patient's condition has changed compared to a normal state based on a feature amount of the patient's biometric information. Then, the estimation unit estimates treatment information for the patient based on the identification information determined by the determination unit and a treatment prediction parameter that has been learned in advance. Patent Document 1 also discloses heart rate and the like as an example of biometric information, and discloses an agitation score that indicates the possibility that the patient is in an agitated state as an example of identification information. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] International Publication No. 2019 / 073927 Summary of the Invention [Problem to be solved by the invention]

[0005] In the case of the technology described in Patent Document 1, if an error occurs somewhere in the system, it becomes impossible to obtain the information necessary for estimation. As a result, it may become impossible to judge whether the person is in an unsettled state.

[0006] A state in which it is not possible to determine whether the subject is in an agitated state as described above is not a desirable state, and it is therefore desirable to resolve this state as soon as possible.

[0007] Therefore, an object of the present invention is to provide a determination device, a notification method, and a recording medium that are capable of dealing appropriately when it is not possible to determine whether a person is in an agitated state for some reason. [Means for solving the problem]

[0008] In order to achieve this object, a determination device according to one embodiment of the present disclosure includes: An estimation unit that estimates a cause of an error based on data used when determining whether the vehicle is in an unsettled state; a notification unit that issues a notification according to a result of the estimation by the estimation unit; have The structure is as follows.

[0009] In addition, a notification method according to another embodiment of the present disclosure includes: The computer Inferring the cause of the error based on the data used to determine the state of agitation; Notify according to the estimated results Notification method.

[0010] In addition, a recording medium according to another embodiment of the present disclosure includes: On the computer, Inferring the cause of the error based on the data used to determine the state of agitation; Providing a notification in accordance with the identified results; It is a recording medium on which a program for implementing the processing is recorded. Effect of the Invention

[0011] According to the above-mentioned configurations, when it is impossible to judge whether the subject is in an uneasy state for some reason, it becomes possible to take appropriate measures. [Brief description of the drawings]

[0012] [Figure 1]1 is a diagram illustrating an example of the overall configuration of an agitation determination system according to a first embodiment of the present disclosure. [Diagram 2] 2 is a block diagram showing a configuration example of the sensor device shown in FIG. 1. [Diagram 3] 2 is a block diagram showing an example of the configuration of the bed terminal shown in FIG. 1. [Figure 4] 2 is a block diagram showing an example of the configuration of the instability determination device shown in FIG. 1. [Diagram 5] FIG. 4 is a diagram illustrating an example of information stored in a storage unit. [Figure 6] FIG. 11 is a diagram showing an example of vital data included in sensing data. [Figure 7] FIG. 13 is a diagram showing an example of a score for determining unrest included in the score information. [Figure 8] 11 is a diagram for explaining an example of processing by a score calculation unit; FIG. [Figure 9] 10 is a flowchart showing an example of the operation of the instability determination device; [Figure 10] FIG. 13 is a block diagram showing another example of the configuration of the instability determination device. [Figure 11] FIG. 13 is a block diagram showing another example of the configuration of the instability determination device. [Figure 12] FIG. 11 is a diagram for explaining an example of an error occurrence situation. [Figure 13] FIG. 11 is a hardware configuration diagram of a determination device according to a second embodiment of the present disclosure. [Figure 14] FIG. 2 is a block diagram showing an example of the configuration of a determination device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] [First embodiment] A first embodiment of the present disclosure will be described with reference to FIG. 1 to FIG. 12. FIG. 1 is a diagram showing an example of the overall configuration of the agitation determination system 100. FIG. 2 is a block diagram showing an example of the configuration of the sensor device 200. FIG. 3 is a block diagram showing an example of the configuration of the bed terminal 300. FIG. 4 is a block diagram showing an example of the configuration of the agitation determination device 400. FIG. 5 is a diagram showing an example of information stored in the storage unit 440. FIG. 6 is a diagram showing an example of vital data included in the sensing data 442. FIG. 7 is a diagram showing an example of agitation determination score included in the score information 444. FIG. 8 is a diagram for explaining an example of processing of the score calculation unit 455. FIG. 9 is a flowchart showing an example of the operation of the agitation determination device 400. FIGS. 10 and 11 are block diagrams showing other examples of the configuration of the agitation determination device 400. FIG. 12 is a diagram for explaining an example of an error occurrence situation.

[0014] In the first embodiment of the present disclosure, an agitation determination system 100 that determines the agitation state of a patient based on data measured using a sensor device 200 will be described. For example, the agitation determination system 100 calculates an agitation determination score based on data measured by the sensor device 200. Then, the agitation determination system 100 determines the agitation state of the patient based on the calculated agitation determination score.

[0015] As will be described later, the unrest determination system 100 detects an error that has occurred in the unrest determination system 100 according to the data reception status of the unrest determination device 400 that performs the unrest determination, and identifies the location of the error. Then, the unrest determination system 100 performs processing according to the identification result. For example, the unrest determination system 100 transmits a restart instruction to correct the identified location of the error, or notifies an external terminal or the like that an error has been identified. This makes it possible to take appropriate action even if the unrest determination system 100 cannot determine an unrest state for some reason.

[0016] The agitation determination system 100 described in this embodiment can be used in various situations, such as acute care hospitals, convalescent care hospitals, nursing homes, and home monitoring. In the following, this embodiment will be described in terms of the case where the agitation determination system 100 is used in hospitals such as acute care hospitals and convalescent care hospitals. The agitation determination system 100 may be used in situations other than those exemplified above that require the determination of an agitation state.

[0017] In this embodiment, agitation refers to a state in which the patient is restless and excited. Agitation can be caused by delirium, etc. The agitated state indicates a state related to the agitation of the patient. The agitated state indicates, for example, whether the patient is agitated or not, and whether the patient shows signs of agitation or not. The agitated state may include other indicators related to the possibility of the patient being agitated. If the patient is agitated, there is a possibility that the patient will exhibit problematic behavior such as falling off the bed, removing the intubation tube, making strange noises, or becoming violent. Therefore, it is desirable to accurately determine the agitated state.

[0018] Fig. 1 shows an example of the configuration of an agitation determination system 100. Referring to Fig. 1, the agitation determination system 100 includes, for example, a sensor device 200, a bed terminal 300, and agitation determination device 400. As shown in Fig. 1, the sensor device 200 and the bed terminal 300 are connected to each other so as to be able to communicate with each other using short-range wireless communication such as Bluetooth (registered trademark) or a wired connection. In addition, the bed terminal 300 and the restlessness determination device 400 are connected to each other via a Wi-Fi (registered trademark) or the like. The bed terminal 300 and the agitation determination device 400 are connected so as to be able to communicate with each other using short-distance wireless communication, wired communication, etc. The bed terminal 300 and the agitation determination device 400 may be connected via a relay device such as a wireless base station.

[0019] The number of sensor devices 200, the number of bed terminals 300, and the number of agitation determination devices 400 included in the agitation determination system 100 are not limited to those illustrated in Fig. 1. For example, the agitation determination system 100 can include a plurality of sensor devices 200, bed terminals 300, and agitation determination devices 400.

[0020] The sensor device 200 measures vital data of a patient who is a subject. FIG. 2 shows an example of the configuration of the sensor device 200. Referring to FIG. 2, the sensor device 200 includes, for example, a sensor 210 and a transmitting / receiving unit 220. For example, the sensor device 200 can realize each of the above-mentioned processing units by hardware. The sensor device 200 may realize each of the above-mentioned processing units by causing a calculation device such as a CPU to execute a program stored in a storage device.

[0021] The sensor 210 is a sensor that acquires vital data of a patient. As described later, the time-series data acquired by the sensor 210 through measurement can be used, for example, when determining whether the patient is agitated. For example, the sensor 210 is at least one of vital sensors such as a heart rate sensor, a respiratory rate sensor, a blood pressure sensor, a body temperature sensor, and a blood oxygen saturation sensor.

[0022] Here, vital data refers to physical quantities that change with the patient's vital activities, and includes, for example, at least one of the patient's heart rate, respiratory rate, blood pressure, body temperature, skin temperature, blood flow, blood oxygen saturation, and the like.

[0023] Further, the sensor 210 can measure body movement data in addition to or instead of the vital data. For example, the sensor 210 can include at least one of body movement sensors such as an acceleration sensor, a gyro sensor (angular velocity sensor), an angle sensor, and a microphone as a configuration for measuring body movement data.

[0024] The body movement data is a physical quantity related to the movement of the patient's body, and includes, for example, at least one of the acceleration, angular velocity, angle, and vocalization volume of a specific part of the patient's arm, body, or leg.

[0025] The transmitting / receiving unit 220 has an antenna etc. The transmitting / receiving unit 220 transmits and receives data to and from the bed terminal 300.

[0026] For example, the transceiver unit 220 may communicate with the bed terminal 300 using low-power wireless communication such as Bluetooth. For example, the transmitting / receiving unit 220 transmits to the bed terminal 300 the vital data and body movement data acquired by the sensor 210 in association with the identification information of the sensor device 200.

[0027] The above is an example of the configuration of the sensor device 200. The sensor device 200 may be composed of one device or multiple devices. For example, the sensor device 200 may be realized by connecting multiple devices, such as one or multiple sensor devices and a device having a function as the transmission / reception unit 230, so that they can communicate with each other. The sensor 210 may be attached to the patient, or may be attached to, for example, a bed where the patient is staying. When the sensor device 200 is composed of multiple devices, each of the multiple devices may have a transmission / reception unit.

[0028] The bed terminal 300 is an information processing device that is installed in advance at a predetermined location such as near the bed where the patient is staying. For example, the bed terminal 300 is a smartphone or the like, and has a screen display function. The bed terminal 300 may be something other than a smartphone. The bed terminal 300 is a terminal that is installed at a predetermined location where the patient should stay, or a predetermined location that is a reference for determining the range where the patient should stay, and is not limited to being installed near the bed.

[0029] Fig. 3 shows an example of the configuration of the bed terminal 300. Referring to Fig. 3, the bed terminal 300 has, for example, a transmission / reception unit 310 and a screen display unit 320. For example, the bed terminal 300 can realize each of the above processing units by hardware. The bed terminal 300 may realize each of the above processing units by having a calculation device such as a CPU execute a program stored in a storage device.

[0030] The transmitting / receiving unit 310 has an antenna and the like, and transmits and receives data between the sensor device 200 and the resentment determination device 400. For example, the transmitting / receiving unit 310 receives body movement data, vital data, identification information of the sensor device 200, and the like transmitted by the sensor device 200. Then, the transmitting / receiving unit 310 transmits the body movement data, vital data, identification information, and the like received from the sensor device 200 to the resentment determination device 400. The transmitting / receiving unit 310 can also receive information indicating the resentment determination result from the resentment determination device 400.

[0031] Furthermore, the transmitting / receiving unit 310 can transmit, to the instability determination device 400, information according to the communication status with the sensor device 200. For example, when the low-power wireless communication established with the sensor device 200 is disconnected, the transmitting / receiving unit 310 can transmit, to the instability determination device 400, information indicating that the communication with the sensor device 200 has been disconnected.

[0032] The screen display unit 320 displays on a screen the vital data, body movement data, information indicating the results of the agitation determination and state determination, etc., received by the transmission / reception unit 310. For example, the screen display unit 320 can display on a screen that the patient corresponding to the bed terminal 300 is agitated, etc., based on the received information indicating the agitation determination result.

[0033] The agitation determination device 400 is an information processing device that performs agitation determination based on vital data and body movement data acquired by the sensor 210 of the sensor device 200. The agitation determination device 400 detects the occurrence of an error and identifies the location of the error according to the state and reception status of the vital data and body movement data. The agitation determination device 400 is installed at a predetermined location such as a nurse's station. For example, the agitation determination device 400 is an information processing device such as a personal computer or tablet used by a medical professional, a server installed in a hospital, or a cloud server. The agitation determination device 400 may be a combination of an information processing device such as a personal computer or tablet and a server. For example, the agitation determination device 400 is a combination of an on-premise server and a smartphone in a hospital, and the on-premise server performs a determination based on body movement data and vital data, and displays or notifies the result on a smartphone used by a medical professional. The medical professional is, for example, a doctor or a nurse. The medical professional in the present disclosure is not limited to those who are engaged in medical care.

[0034] Fig. 4 shows an example of the configuration of the unrest determination device 400. Referring to Fig. 4, the unrest determination device 400 has, as main components, for example, an operation input unit 410, a screen display unit 420, a communication I / F unit 430, a storage unit 440, and an arithmetic processing unit 450. The unrest determination device 400 has general functions such as a clock function that shows the time.

[0035] The operation input unit 410 is composed of an operation input device such as a keyboard, a mouse, etc. The operation input unit 410 detects an operation of a medical worker who operates the instability determination device 400, and outputs the operation to the calculation processing unit 450.

[0036] The screen display unit 420 is composed of a screen display device such as an LCD (Liquid Crystal Display). The screen display unit 420 can display various information stored in the storage unit 440, such as the sensing data 442, the connection status information 443, the score information 444, and the result information 445, in response to an instruction from the arithmetic processing unit 450. The screen display unit 420 may be installed in a location separate from the location where the arithmetic processing unit 450 and the like are installed. For example, among the components of the unrest determination device 400, only the screen display unit 420 may be installed in a nurse's station. In this case, the arithmetic processing unit 450 and the like may be installed in a location separate from the screen display unit 420, such as a server room.

[0037] The communication I / F unit 430 is composed of a data communication circuit and performs data communication with an external device such as the bed terminal 300 connected by wireless communication or a mobile terminal carried by a medical staff member.

[0038] The storage unit 440 is a storage device such as a hard disk or a memory. FIG. 5 shows an example of information stored in the storage unit 440. As shown in FIG. 5, the storage unit 440 stores processing information and a program 446 required for various processes in the arithmetic processing unit 450. The program 446 is read into the arithmetic processing unit 450 and executed to realize various processing units. The program 446 is read in advance from an external device or a recording medium via a data input / output function such as the communication I / F unit 430, and is stored in the storage unit 440. Main information stored in the storage unit 440 includes, for example, a model for determining unrest 441, sensing data 442, connection status information 443, score information 444, and result information 445.

[0039] The disturbance determination model 441 is a model that calculates a disturbance determination score based on vital data and body movement data acquired by the sensor 210. For example, the disturbance determination model 441 receives information corresponding to vital data and body movement data as input and outputs a disturbance determination score. The disturbance determination model 441 is a trained model that is generated in advance by performing machine learning using a support vector machine (SVM) or a neural network in an external device, for example. For example, the machine learning is performed by using data that is labeled with the presence or absence of disturbance for vital data and body movement data measured in the past as teacher data. The disturbance determination model 441 is acquired from an external device via the communication I / F unit 430, etc., and stored in the storage unit 440.

[0040] Note that the disturbance determination model 441 may include multiple types of models according to the type of data. For example, the disturbance determination model 441 may include a vital model that inputs vital data and a body movement model that inputs body movement data. The disturbance determination model 441 may also include multiple models according to the types of vital data and body movement data, such as acceleration and vocalization volume. The disturbance determination model 441 may be other than the above examples.

[0041] The agitation determination score output by the agitation determination model 441 is an index for determining whether the patient is agitated or not, and whether the patient has signs of agitation. The agitation determination score is, for example, a value between 0 and 1. The closer the agitation determination score is to 1, the more agitated the patient is or has signs of agitation, and the closer the agitation determination score is to 0, the less agitated the patient is or has no signs of agitation. The agitation determination score may be an index expressed by a binary value of 1 indicating agitation or signs of agitation and 0 indicating no agitation or no signs of agitation. The agitation determination score may be an index expressing the degree of strength, for example, 2 indicating strong agitation and 1 indicating weak agitation.

[0042] The data input to agitation determination model 441 may be the vital data or body movement data itself, or may be various features calculated by performing feature processing such as averaging or differentiation on time-series vital data or body movement data. Agitation determination model 441 may be configured to input one type of vital data or body movement data, or may be configured to input multiple types of vital data or body movement data.

[0043] The sensing data 442 includes data acquired by the sensor 210. For example, the sensing data 442 stores vital data, body movement data, and the like acquired by the sensor 210 for each piece of identification information of the sensor device 200.

[0044] For example, Fig. 6 shows an example of time series data of heart rate, which is a type of vital data. In Fig. 6, the x-axis shows time, and the y-axis shows heart rate.

[0045] The connection status information 443 indicates the connection status between devices that exists until the unrest determination device 400 acquires the data measured by the sensor 210, such as the connection status between the sensor device 200 and the bed terminal 300 and the connection status between the bed terminal 300 and the unrest determination device 400. For example, the connection status information 443 indicates whether or not the sensor device 200 and the bed terminal 300, and the bed terminal 300 and the unrest determination device 400 are connected so as to be able to communicate with each other. The connection status information 443 is updated according to, for example, information received from the bed terminal 300 and the connection status with the bed terminal 300.

[0046] The score information 444 includes a score for determining whether the patient is agitated or not (or whether there is a sign of agitation in the patient). For example, in the score information 444, the identification information of the sensor device 200 and the score for determining agitation are associated with each other.

[0047] Fig. 7 shows an example of the agitation determination score calculated by score calculation unit 455 based on the vital data shown in Fig. 6. In Fig. 7, the x-axis indicates time, and the y-axis indicates the agitation determination score. As shown in Fig. 7, the agitation determination score is expressed, for example, as a value between 0 and 1. The agitation determination score closer to 1 indicates that the patient is more agitated or there are signs of agitation, and the agitation determination score closer to 0 indicates that the patient is not agitated or there are no signs of agitation.

[0048] The result information 445 includes information indicating the result of the determination made by the uneasy state determination unit 456 based on the score information 444. For example, the result information 545 includes identification information of the sensor device 200 and information indicating the result of the uneasy state determination.

[0049] The arithmetic processing unit 450 has a microprocessor such as an MPU and its peripheral circuits. The arithmetic processing unit 450 reads and executes the program 446 from the storage unit 440, thereby implementing various processing units by making the above hardware and the program 446 work together. Major processing units implemented by the arithmetic processing unit 550 include, for example, a data acquisition unit 451, an error detection unit 452, an error cause estimation unit 453, a correction instruction unit 454, a score calculation unit 455, an uneasy state determination unit 456, and a notification unit 457.

[0050] The data acquisition unit 451 acquires the body movement data, vital data, identification information, and the like transmitted by the bed terminal 300 via the communication I / F unit 430. Then, the data acquisition unit 451 stores the acquired body movement data and vital data in the storage unit 440 as sensing data 442 in association with the identification information.

[0051] The disturbance determination system 100 performs disturbance determination using sensing data. However, if an error occurs for some reason, the disturbance state cannot be accurately determined. Therefore, the disturbance determination system 100 is provided with an error detection unit 452, an error cause estimation unit 453, and a correction instruction unit 454 described below, so that the disturbance determination system 100 can appropriately deal with the occurred error.

[0052] Error detection section 452 detects the occurrence of an error using data used for determining whether or not a person is uneasy. That is, error detection section 452 detects the occurrence of an error using vital data (or body movement data).

[0053] In this embodiment, the error detection unit 452 detects the occurrence of an error based on the acquisition status of the vital data, the status of the vital data, and the like. For example, the error detection unit 452 determines that an error has occurred when at least one of the vital data is no longer acquired normally. The determination that the data is no longer acquired normally can be made using at least one of a timestamp indicating the time when the data was acquired and the data itself, for example. For example, the error detection unit 452 can determine whether the vital data is acquired normally by comparing the timestamp with the current time, comparing the timestamps of multiple vital data, comparing the timestamps of the vital data and the body movement data, checking the data, and the like.

[0054] Specifically, for example, the error detection unit 452 can determine whether the vital data has been acquired normally based on a comparison result between a timestamp of the last vital data (the time when the vital data was last acquired) included in the sensing data 442 and the time when the detection is performed. For example, the error detection unit 452 compares a timestamp of the last vital data included in the sensing data 442 with the time when the detection is performed. Then, when the difference between the timestamp and the time when the detection is performed exceeds a predetermined allowable range, such as within 30 seconds, the error detection unit 452 determines that the vital data has not been acquired normally and detects the occurrence of an error.

[0055] Furthermore, the error detection unit 452 can determine whether the vital data has been acquired normally based on the confirmation result of whether the vital data included in the sensing data 442 satisfies a predetermined condition. For example, the error detection unit 452 confirms whether the vital data included in the sensing data 442 satisfies a predetermined condition. Then, the error detection unit 452 determines that the vital data has not been acquired normally and detects the occurrence of an error based on a predetermined condition, such as, for example, 50% or more of the vital data within a predetermined time indicates a value outside a predetermined range, the time difference between the heart rate and the time of the heart rate coincides less than 90%, the number of pieces of heart rate data acquired within a predetermined time is within 90% of the ideal number of pieces of data calculated from the heart rate, and so on.

[0056] For example, as described above, the error detection unit 452 detects the occurrence of an error based on a time stamp, a measurement value such as vital data included in the sensing data 442, or the like.

[0057] As described above, the sensing data 442 may include multiple types of data. That is, the sensing data 442 may include vital data and body movement data, or multiple types of vital data and multiple types of body movement data. In this way, when the sensing data 442 includes multiple types of data, the error detection unit 452 can detect the occurrence of an error when any one of the multiple types of data satisfies the above-mentioned condition.

[0058] When the error detection unit 452 detects an error, the error cause estimation unit 453 estimates the cause of the error. For example, the error cause estimation unit 453 estimates the cause of the error based on the acquisition status of the vital data, the connection status information 443, and the like. For example, the error cause estimation unit 453 estimates the cause of the error based on the time stamp of the vital data, the connection status information 443, and the like. The error cause estimation unit 453 may estimate the cause location as the cause of the error. That is, the error cause estimation unit 453 can identify the location of the error based on the state of the vital data and body movement data included in the sensing data 442, the acquisition status, the connection status information 443, and the like. The error cause estimation unit 453 also instructs the correction instruction unit 454 to perform processing according to the result of the estimation.

[0059] Specifically, for example, it is assumed that the error detection unit 452 detects an error because vital data included in the sensing data 442 satisfies a predetermined condition. In this case, the error cause estimation unit 453 estimates that the cause of the error is poor contact between the sensor 210 that acquires data that satisfies the predetermined condition and the patient's skin. The error cause estimation unit 453 can also identify the sensor 210 as the location where the error occurred. In this case, the error cause estimation unit 453 can instruct the correction instruction unit 454 to notify an external device or the like that an error such as poor contact has occurred in the identified sensor 210 or the bed terminal 300.

[0060] Also, assume that the error detection unit 452 detects an error based on a comparison result between the timestamp and the time of detection. In this case, for example, if the difference between the timestamp and the time of only some types of data among the multiple types of data included in the sensing data 442 exceeds the allowable range, the error cause estimation unit 453 estimates that the cause of the error is poor contact in the sensor 210 that acquires the data whose difference between the timestamp and the time exceeds the allowable range, or that the sensor 210 is not attached. In addition, the error cause estimation unit 453 can specify the sensor 210 as the location where the error occurred. In this case, the error cause estimation unit 453 can instruct the correction instruction unit 454 to notify an external device or the like that an error such as poor contact or not attached has occurred in the specified sensor 210 or the bed terminal 300.

[0061] Furthermore, if the difference between the timestamp and the time for all data included in the sensing data 442 exceeds the allowable range, the error cause estimation unit 453 estimates the cause of the error and identifies the location where the error occurred based on the connection status information 443.

[0062] For example, if it is determined based on the connection status information 443 that the bedside terminal 300 and the uneasiness determination device 400 are not connected to be able to communicate with each other, the error cause estimation unit 453 estimates that the cause of the error is a power-off or Wi-Fi error that occurred in the bedside terminal 300. Furthermore, the error cause estimation unit 453 can identify the bed terminal 300 as the location where the error occurred. In this case, the error cause estimation unit 453 can instruct the correction instruction unit 454 to notify an external device or the like that an error has occurred in the bed terminal 300. Note that, in addition to the above notification, the error cause estimation unit 453 may be configured to instruct the correction instruction unit 454 to instruct the bed terminal 300 to restart the communication function or the power supply of the terminal itself.

[0063] Also, for example, when it is determined based on the connection status information 443 that the bed terminal 300 and the agitation determination device 400 are connected while the sensor device 200 and the bed terminal 300 are not connected, the error cause estimation unit 453 estimates that the cause of the error is that the patient has left the bed, the power supply of the sensor device 200 is off, an error has occurred in the bed terminal 300, or the like. Also, the error cause estimation unit 453 can specify the sensor device 200 or the bed terminal 300 as the location where the error has occurred. In this case, the error cause estimation unit 453 can instruct the correction instruction unit 454 to notify an external device or the like that the patient may have left the bed, that an error may have occurred in the sensor device 200 or the bed terminal 300, or the like.

[0064] Also, for example, when it is determined based on the connection status information 443 that the bed terminal 300 and the uneasiness determination device 400 are connected and that the sensor device 200 and the bed terminal 300 are also connected, the error cause estimation unit 453 estimates that the cause of the error is that an error has occurred in the bed terminal 300, that all the sensors 210 have been removed, or the like. Also, the error cause estimation unit 453 can specify the sensor device 200 having the sensor 210 or the bed terminal 300 as the location where the error has occurred. In this case, the error cause estimation unit 453 can instruct the correction instruction unit 454 to instruct the bed terminal 300 to restart the power of the terminal itself. Also, the error cause estimation unit 453 can instruct the correction instruction unit 454 to notify an external device, etc., that the sensor 210 may be removed from the patient, together with the above-mentioned restart instruction.

[0065] If it is determined that the instability determination device 400 itself has frozen, the error cause estimation unit 453 may instruct the correction instruction unit 454 to instruct the restart of the instability determination device 400 itself.

[0066] For example, as described above, the error cause estimation unit 453 estimates the cause of the error based on the state of the vital data and body movement data included in the sensing data 442, the acquisition status, and the connection status information 443. The error cause estimation unit 453 can also identify the location where the error occurred. Then, the error cause estimation unit 453 instructs the correction instruction unit 454 to perform processing according to the estimation or identification result.

[0067] The estimation process performed by the error cause estimation unit 453 is not limited to the above-mentioned example. The error cause estimation unit 453 may estimate the cause of the error or identify the location of the error by a method other than the above-mentioned example. The error cause estimation unit 453 may also instruct each processing unit to perform processing according to a specific result other than the above-mentioned example. For example, the error cause estimation unit 453 may be configured to acquire information indicating the operating status of a sensor application that performs the measurement process from the sensor device 200 or the bed terminal 300. In this case, the error cause estimation unit 453 may estimate the cause of the error or identify the location of the error based on the acquired information.

[0068] The correction instruction unit 454 issues a correction instruction corresponding to the cause of the error estimated by the error cause estimation unit 453. For example, the correction instruction issued by the correction instruction unit 454 includes a notification to an external device, an instruction to restart the identified occurrence location, and the like.

[0069] In addition, the notification to the external device may notify the correction contents, etc., or may notify only the occurrence of the error. For example, in a case where the correction contents cannot be uniquely estimated, the correction instruction unit 454 may notify candidates for the correction contents. In addition, in a case where the error cause estimation unit 453 identifies the occurrence location, the correction instruction unit 454 can also notify the occurrence location. In addition, the correction instruction unit 454 may control the notification destination according to the type of error, etc. For example, in the case of poor contact of the sensor 210, the correction instruction unit 454 notifies a mobile terminal carried by the medical staff in charge. On the other hand, in the case of a system error such as restarting the device, the correction instruction unit 454 notifies a management device that manages the system, etc. For example, as described above, the correction instruction unit 454 may control the notification destination according to the type of error, etc.

[0070] Furthermore, the correction instruction unit 454 can transmit a restart instruction to the sensor device 200 or the bed terminal 300 in response to an instruction from the error cause estimation unit 453. Specifically, for example, the correction instruction unit 454 receives an instruction to transmit a restart instruction from the error cause estimation unit 453. Then, the correction instruction unit 454 transmits a restart instruction to instruct a restart to the sensor device 200 or the bed terminal 300 specified in the instruction to transmit the restart instruction.

[0071] The score calculation unit 455 and the uneasy state determination unit 456 perform a process of determining an uneasy state based on the sensing data 442. For example, the score calculation unit 455 and the uneasy state determination unit 456 perform a process of determining an uneasy state while no error is detected by the error detection unit 452. For example, when an error is detected by the error detection unit 452 but normal data is included in the sensing data 442, the score calculation unit 455 and the uneasy state determination unit 456 may continue to determine an uneasy state based on the normal data included in the sensing data 442. An example of the process of the score calculation unit 455 and the uneasy state determination unit 456 will be described below. Note that the uneasy state determination process is not limited to this.

[0072] The score calculation unit 455 calculates the unrest determination score using the unrest determination model 441.

[0073] For example, the score calculation unit 455 refers to the sensing data 442 and acquires vital data including time-series data of the heart rate as shown in Fig. 6. The score calculation unit 455 also inputs the acquired data to the agitation determination model 441 and calculates the agitation determination score at each time as shown in Fig. 7. Thereafter, the score calculation unit 455 stores information indicating the calculated agitation determination score in the storage unit 440 as score information 444.

[0074] In addition, the score calculation unit 455 may input the time series data itself to the model for determining disturbance 441, or may input various features calculated by performing feature quantity processing such as averaging and differentiation processing on the time series data to the model for determining disturbance 441.

[0075] The agitated state determination section 456 determines the agitated state of the patient based on the agitation determination score included in the score information 444. For example, the agitated state determination section 456 determines whether the patient is agitated or not, or whether the patient has a sign of agitation, as the agitated state of the patient. Then, the agitated state determination section 456 stores the result of the determination as result information 445 in the storage section 440. For example, the agitated state determination section 456 stores information indicating the result of the determination that the patient is agitated as result information 445 in the storage section 440.

[0076] For example, the agitated state determination unit 456 has a determination threshold for comparison with the agitation determination score in advance. Then, the agitated state determination unit 456 performs a determination based on the agitation determination score and the agitation determination threshold. For example, when the agitation determination score is equal to or greater than the agitation determination threshold, the agitated state determination unit 456 determines that the patient is agitated or has a sign of agitation. On the other hand, when the agitation determination score is less than the agitation determination threshold, the agitated state determination unit 456 determines that the patient is not agitated or has no sign of agitation.

[0077] Specifically, for example, in the case of the agitation determination score shown in Fig. 8, the agitation determination score is equal to or greater than the determination threshold between 22:30 and just before 1:00, and just before 2:00, as shown in Fig. 9. Therefore, the agitated state determination section 456 determines that the patient is agitated during the above-mentioned times.

[0078] In addition, in FIG. 9, a case where the judgment threshold is 0.5 is illustrated. However, the judgment threshold may be other than 0.5. The value of the judgment threshold may be set arbitrarily. The judgment threshold may be appropriately determined according to, for example, attribute information of a patient, which will be described later.

[0079] The notification section 457 performs necessary output when the restless state determination section 554 determines that the patient is restless.

[0080] For example, when the agitated state determination unit 554 determines that the patient is agitated, the notification unit 457 displays on the screen display unit 420 the fact that the patient is agitated, together with the identification information of the sensor device 200. The notification unit 457 also transmits the fact that the patient is agitated, together with the identification information of the sensor device 200, to an external device such as the bed terminal 300 related to the patient or a mobile terminal carried by a medical worker in charge of the patient. The notification unit 457 may perform notifications other than those exemplified above, such as turning on a lamp at the entrance to the room where the patient is hospitalized.

[0081] The resentment determination device 400 may be configured to be able to identify the medical staff (mobile terminal) who is staying at the location closest to the location where an error has occurred or the patient in an agitated state, based on, for example, location information of the mobile terminal. When the resentment determination device 400 is configured in this way, the notification unit 457 may send the above-mentioned notification to the mobile terminal carried by the identified medical staff.

[0082] The above is an example of the configuration of the instability determination system 100. Next, an example of the operation of the instability determination device 400 will be described with reference to Fig. 9. Note that the order of operations of the instability determination device 400 shown in Fig. 9 is one example, and is not limited to this.

[0083] Fig. 9 is a flowchart showing an example of the operation of the unrest determination device 400. Referring to Fig. 9, the data acquisition unit 451 acquires body movement data, vital data, identification information of the sensor device 200, and the like via the communication I / F unit 430 (step S101).

[0084] The error detection unit 452 detects an error that has occurred in the agitation determination system 100 based on the vital data included in the sensing data 442 (step S102). For example, the error detection unit 452 detects the occurrence of an error based on a comparison result between a timestamp and the time of detection, the state of data included in the sensing data 442, and the like.

[0085] When the error detection unit 452 detects the occurrence of an error (step S102, Yes), the error cause estimation unit 453 identifies the location of the error (step S103). For example, the error cause estimation unit 453 identifies the location of the error based on the state of the vital data and body movement data included in the sensing data 442, the acquisition status and connection status information 443, and the like.

[0086] Furthermore, when it is determined based on the identified result that the error may be corrected by restarting (step S104, Yes), the error cause estimation unit 453 instructs the correction instruction unit 454 to issue a restart instruction. In response to this, the correction instruction unit 454 issues a restart instruction to the sensor device 200 and the bed terminal 300 (step S105). A predetermined notification may be issued together with the restart instruction by the correction instruction unit 454. Furthermore, when it is determined that the error is difficult to correct by restarting (step S104, No), the error cause estimation unit 453 instructs the correction instruction unit 454 to notify the occurrence of an error. In response to this, the correction instruction unit 454 notifies the occurrence of an error to a mobile terminal carried by a medical worker or the like (step S106).

[0087] Moreover, if the error detection unit 452 does not detect the occurrence of an error (step S102, No), the unrest determination device 400 performs an unrest determination (step S107). The unrest determination by the unrest determination device 400 is performed, for example, using the score calculation unit 455 and the unrest state determination unit 456. Note that the unrest determination by the unrest determination device 400 is not limited to the example described above.

[0088] The above is an example of the operation of the instability determination device 400.

[0089] In this way, the unrest determination device 400 has an error detection unit 452, an error cause estimation unit 453, and a correction instruction unit 454. With this configuration, when the error detection unit 452 detects an error, the error cause estimation unit 453 can identify the location of the error. As a result, depending on the result of the identification by the error cause estimation unit 453, the correction instruction unit 454 can issue a restart instruction or a predetermined notification. This makes it possible to quickly take appropriate measures even if, for example, an error makes it impossible to determine an unrest state.

[0090] The configuration of the instability determination device 400 is not limited to the case described with reference to Fig. 4. For example, Fig. 10 shows another configuration example of the instability determination device 400. With reference to Fig. 10, the calculation processing unit 450 of the instability determination device 400 can have, for example, a prioritization unit 458.

[0091] The prioritization unit 458 prioritizes notifications according to the result of the determination of the disturbance state, such as the score for determining disturbance indicated by the score information 444. The notification unit 457 can provide notification with notification content or notification method according to the result of the prioritization performed by the prioritization unit 458, for example.

[0092] Here, the priority is an index indicating, for example, the importance, necessity, urgency, etc. of the notification. The higher the priority, the higher the importance, necessity, urgency, etc. of the notification. For example, when it is necessary to have a medical professional or the like quickly recognize the occurrence of an error, the importance, necessity, urgency, etc. of notifying the error is considered to be high, and the priority is high.

[0093] For example, the prioritization unit 458 can assign priorities based on past scores for determining disturbance, such as scores for the previous day or the previous hour. For example, the prioritization unit 458 refers to past scores for determining disturbance. Then, the prioritization unit 458 assigns priorities according to the past scores for determining disturbance. For example, the prioritization unit 458 determines that the higher the past scores for determining disturbance, the higher the priority. The prioritization unit 458 may assign priorities based on whether the past scores for determining disturbance exceed a predetermined past threshold (which may be any value). For example, if the past scores for determining disturbance exceed the past threshold, the prioritization unit 458 determines that the priority is high. In this case, the correction instruction unit 454 can notify the occurrence of an error more strongly. For example, the correction instruction unit 454 realizes a stronger notification by adopting at least one of the following methods: sounding a notification sound, making the notification sound louder, changing the notification sound, notifying multiple places, and the like. On the other hand, if the past unrest determination score is equal to or lower than the past threshold, the prioritization unit 458 determines that the priority is low. In this case, the correction instruction unit 454 can notify the error weakly. For example, the correction instruction unit 454 realizes a weak notification by adopting at least one method of not making a sound, reducing the sound, and the like. In addition, if there is no past unrest score, the prioritization unit 458 can determine that the priority is intermediate (or does not determine the priority). In this case, the correction instruction unit 454 may adopt a method between a strong notification and a weak notification, such as making a quiet sound. In addition, the past threshold may be one, or may include multiple different values. When the past threshold includes multiple values, the prioritization unit 458 can determine the priority in stages. In this way, by performing a notification reflecting the priority, the unrest determination device 400 can make a medical worker who receives the notification quickly recognize the importance of the notification, etc. Then, the medical worker, etc. can take an appropriate action more quickly in response to the occurrence of an error.

[0094] 11 shows another example of the configuration of the disturbance determination device 400. With reference to FIG. 11, the calculation processing unit 450 of the disturbance determination device 400 can have, for example, an attribute information acquisition unit 459 in addition to the prioritization unit 458 or instead of the prioritization unit 458.

[0095] The attribute information acquiring unit 459 acquires attribute information of the subject patient. For example, the attribute information acquiring unit 459 acquires the subject's medical record information from an external device or the like, and acquires attribute information such as age, sex, and paralysis state.

[0096] The attribute information acquired by the attribute information acquisition unit 459 can be used, for example, when adjusting a judgment threshold. Also, the attribute information acquired by the attribute information acquisition unit 459 can be used when the prioritization unit 458 judges the priority. For example, the prioritization unit 458 judges whether or not the occurrence of agitation is likely based on the prescription drug, free description field, disease name, age, sex, and the like indicated by the attribute information. Then, the prioritization unit 458 judges the priority to be high when it is judged that the occurrence of agitation is likely. Also, the prioritization unit 458 judges the priority to be low when it is judged that the occurrence of agitation is low. For example, as described above, the prioritization unit 458 may judge the notification method based on the attribute information. Note that the prioritization unit 458 may judge the priority by combining the past agitation judgment score and the attribute information.

[0097] As described above, the restlessness determination system 100 includes a plurality of sensor devices 200, bed terminals 300, etc. Therefore, as shown in Fig. 12, errors may occur at a plurality of locations at the same time.

[0098] In this way, when errors occur at multiple locations at the same time, the correction instruction unit 454 can adjust the order of notifications to be made to the mobile terminal carried by the medical staff, or create information indicating the order of correction and include it in the notification, based on the priority determined by the prioritization unit 458. That is, when errors occur at multiple locations at the same time, the prioritization unit 458 can prioritize notifications corresponding to the multiple locations. In addition, the correction instruction unit 454 determines, for example, notification content and notification method according to the priority determined by the prioritization unit 458. For example, the correction instruction unit 454 can notify with notification content and notification method according to the priority determined by the prioritization unit 458. Note that, as in the above-mentioned case, the prioritization unit 458 may determine the priority based on the highest past agitation determination score (average value, maximum value, etc.) or the highest probability of agitation occurring determined based on attribute information. Note that the priority in this case may be information indicating the order of notifications. In addition, the correction instruction unit 454 can create information indicating the order of correction and include it in the notification.

[0099] 4, 10, and 11 show an example in which the function of the disturbance determination device 400 is realized by one information processing device. However, the function of the disturbance determination device 400 may be realized by, for example, a plurality of information processing devices connected via a network.

[0100] [Second embodiment] Next, a second embodiment of the present disclosure will be described with reference to Fig. 13 and Fig. 14. In the second embodiment, an overview of the configuration of a determination device 500 will be described.

[0101] Fig. 13 shows an example of a hardware configuration of the determination device 500. Referring to Fig. 13, the determination device 500 has, as an example, the following hardware configuration. ·CPU (Central Processing Unit) 501 (computing unit) ROM (Read Only Memory) 502 (storage device) RAM (Random Access Memory) 503 (storage device) Programs 504 loaded into RAM 503 A storage device 505 for storing a group of programs 504 A drive device 506 that reads and writes from a recording medium 510 outside the information processing device A communication interface 507 for connecting to a communication network 511 outside the information processing device Input / output interface 508 for inputting and outputting data Bus 509 connecting each component

[0102] 14. The program group 504 is stored in advance in, for example, the storage device 505 or the ROM 502, and the CPU 501 loads the program group 504 into the RAM 503 or the like and executes it as necessary. The program group 504 may be supplied to the CPU 501 via the communication network 511, or may be stored in advance in the recording medium 510, and the drive device 506 may read out the program and supply it to the CPU 501.

[0103] 13 shows an example of a hardware configuration of the determination device 500. The hardware configuration of the determination device 500 is not limited to the above. For example, the determination device 500 may be configured with a part of the above configuration, such as not including the drive device 506.

[0104] The estimation unit 521 estimates the cause of the error based on the data used when determining whether the user is in an unsettled state.

[0105] The notification unit 522 issues a notification according to the result of the estimation by the estimation unit 521 .

[0106] In this way, the determination device 500 has the estimation unit 521 and the notification unit 522. With this configuration, the notification unit 522 can provide a notification according to the result estimated by the estimation unit 521 based on the data used to determine the state of agitation. As a result, even if an error occurs and it is not possible to determine the state of agitation, it is possible to take an appropriate action quickly.

[0107] The above-mentioned determination device 500 can be realized by incorporating a predetermined program in the determination device 500. Specifically, the program according to another embodiment of the present invention is a program for realizing, in the determination device 500, an estimation unit 521 that estimates a cause of an error based on data used when determining whether the user is in an uneasy state, and a notification unit 522 that issues a notification according to the result identified by the estimation unit 521.

[0108] In addition, the notification method realized by the above-mentioned judgment device 500 is a method in which the judgment device infers the cause of the error based on the data used when judging the disturbing state, and issues a notification according to the inferred result.

[0109] The invention of the program (or recording medium) or notification method having the above-mentioned configuration can achieve the above-mentioned object of the present invention because it has the same action and effect as the above-mentioned determination device 500. Note that the present invention may also be applied to other devices that determine an error based on measurement data of a subject.

[0110] <Additional Notes> A part or all of the above-described embodiments can be described as follows: The following provides an overview of the determination device and the like in the present invention. However, the present invention is not limited to the following configuration.

[0111] (Appendix 1) An estimation unit that estimates a cause of an error based on data used when determining whether the vehicle is in an unsettled state; a notification unit that issues a notification according to a result of the estimation by the estimation unit; have Judgment device. (Appendix 2) 2. The determination device according to claim 1, The estimation unit estimates a cause of the error based on a state of data used when determining whether the vehicle is in an unsettled state. Judgment device. (Appendix 3) The determination device according to claim 1 or 2, The estimation unit estimates that, when data used to determine an unrest state satisfies a predetermined condition, the error is caused by a sensor that acquires data that satisfies the condition. Judgment device. (Appendix 4) The determination device according to any one of Supplementary Note 1 to Supplementary Note 3, The estimation unit estimates a cause of the error based on an acquisition status of data used for determining whether the vehicle is in an unsettled state. Judgment device. (Appendix 5) The determination device according to any one of Supplementary Note 1 to Supplementary Note 4, The estimation unit estimates a cause of the error based on information indicating a time when data used for determining the unsettled state was acquired. Judgment device. (Appendix 6) The determination device according to any one of Supplementary Note 1 to Supplementary Note 5, The estimation unit estimates a cause of the error based on information indicating a connection state between a sensor that acquires data used to determine the unrest state and a device that exists between the determination device and the sensor. Judgment device. (Appendix 7) The determination device according to any one of Supplementary Note 1 to Supplementary Note 6, a correction instruction unit that issues a restart instruction in response to a result of the estimation by the estimation unit; Judgment device. (Appendix 8) The determination device according to any one of claims 1 to 7, further comprising a prioritization unit that determines a priority level, which is an index of importance of a notification, according to information indicating a result of the determination of the agitation state based on data used for determining the agitation state, The notification unit performs notification according to the priority determined by the prioritization unit. Judgment device. (Appendix 9) 9. The determination device according to claim 8, The prioritization unit determines the priority based on attribute information indicating attributes of the subject. Judgment device. (Appendix 10) The determination device according to any one of Supplementary Note 1 to Supplementary Note 9, The device further includes a detection unit that detects the occurrence of an error based on data used when determining whether the device is in an unsettled state, and the estimation unit estimates the cause of the error in response to the detection of the occurrence of the error by the detection unit. Judgment device. (Appendix 11) The computer Inferring the cause of the error based on the data used to determine the state of agitation; Notify according to the estimated results Notification method. (Appendix 12) On the computer, Inferring the cause of the error based on the data used to determine the state of agitation; Providing a notification according to the estimated result; A recording medium on which a program for implementing processing is recorded

[0112] The programs described in the above embodiments and appendices may be stored in a storage device or a computer-readable recording medium, such as a portable medium such as a flexible disk, an optical disk, a magneto-optical disk, or a semiconductor memory.

[0113] Although the present invention has been described with reference to the above-mentioned embodiments, the present invention is not limited to the above-mentioned embodiments. Various modifications that can be understood by a person skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention. [Explanation of symbols]

[0114] 100 Disturbance Judgment System 200 Sensor device 210 Sensors 220 Transmitter / receiver 300 Bed Terminal 310 Transmitter / receiver 320 Screen display section 400 Suspiciousness Detection Device 410 Operation input section 420 Screen display section 430 Communication I / F section 440 Storage section 441 Model for determining disturbance 442 Sensing Data 443 Connection status information 444 Score Information 445 Results information 446 Programs 450 Processing Unit 451 Data Acquisition Department 452 Error detection unit 453 Error Cause Estimation Department 454 Correction instruction section 455 Score Calculation Unit 456 Unsettling State Judgment Unit 457 Notification Department 458 Prioritization Division 459 Attribute information acquisition section 500 Judgment device 501 CPU 502 ROM 503 RAM 504 Programs 505 Storage device 506 Drive Unit 507 Communication Interface 508 Input / Output Interface 509 Bus 510 Recording media 511 Communication Network 521 Estimation Department 522 Notification Department

Claims

1. A detection unit that detects an occurrence of an error based on a plurality of data used when determining an unsettled state; an estimation unit that estimates a cause of the error based on a plurality of data used to determine an unsettled state when the detection unit detects an error; a notification unit that issues a notification according to a result of the estimation by the estimation unit; having When the difference between the time when the device last acquired data and the time when the detection unit performs detection exceeds an allowable range and is part of the multiple data used to determine the uneasy state, the estimation unit estimates that the cause of the error is the sensor that acquired the data that exceeds the allowable range, and when the difference exceeds the allowable range for all of the multiple data used to determine the uneasy state, estimates the cause of the error based on information indicating the connection status between devices existing between the sensor that acquires the data used to determine the uneasy state and the determination device. Judgment device.

2. The determination device according to claim 1 , a correction instruction unit that issues a restart instruction in response to a result of the estimation by the estimation unit; Judgment device.

3. The determination device according to claim 1 , a prioritization unit that determines a priority level, which is an index showing the importance of a notification, according to information showing a result of the determination of the agitation state based on data used for determining the agitation state; The notification unit performs notification according to the priority determined by the prioritization unit. Judgment device.

4. The determination device according to claim 3, The prioritization unit determines the priority based on attribute information indicating attributes of the subject. Judgment device.

5. The computer Detecting the occurrence of an error based on multiple data used to determine the unrest state; When an error is detected, the cause of the error is estimated based on a plurality of data used to determine the unrest state; Notification will be given based on the estimated results. When estimating the cause of the error, if the difference between the time when the device last acquired data and the time when the occurrence of the error is detected exceeds an allowable range and is part of the multiple data used to determine the unrest state, it is estimated that the cause of the error lies in the sensor that acquired the data that exceeds the allowable range, and if the difference exceeds the allowable range for all of the multiple data used to determine the unrest state, the cause of the error is estimated based on information indicating the connection status between the devices existing between the sensor that acquires the data used to determine the unrest state and the determination device. Notification method.

6. On the computer, Detecting the occurrence of an error based on multiple data used to determine the unrest state; When an error is detected, the cause of the error is estimated based on a plurality of data used to determine the unrest state; Notify according to the estimated results To realize the processing, When estimating the cause of the error, if the difference between the time when the device last acquired data and the time when the occurrence of the error is detected exceeds an allowable range and is part of the multiple data used to determine the unrest state, it is estimated that the cause of the error lies in the sensor that acquired the data that exceeds the allowable range, and if the difference exceeds the allowable range for all of the multiple data used to determine the unrest state, the cause of the error is estimated based on information indicating the connection status between the devices existing between the sensor that acquires the data used to determine the unrest state and the determination device. program.

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