Monitoring system and monitoring program

Abstract

To provide a monitoring system and a monitoring program, capable of reducing an installation cost.SOLUTION: A monitoring system 1 is a system for monitoring a monitoring target within a monitoring environment. The monitoring system includes: an acquisition part 22a configured to acquire picked-up image information showing a picked-up image imaging the monitoring target; a state specification part 22b configured to specify a state of the monitoring target according to an angle and / or a position of a portion of the monitoring target in the picked-up image of the picked-up image information acquired by the acquisition part 22a; and a provision part 22c configured to provide state information showing the state of the monitoring target specified by the state specification part 22b.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a monitoring system and a monitoring program.

Background Art

[0002] Conventionally, as one of the systems for identifying the state of a care recipient, a system for determining the state (posture) of a care recipient based on the body pressure distribution of the care recipient detected by an elastomer sensor disposed on a bedding has been proposed (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Here, in the above-described conventional system, although an elastomer sensor is used when identifying the state of a care recipient as described above, since the sensor is relatively expensive, when there are a large number of care recipients to be monitored, the installation cost of the system may become excessive. Therefore, from the viewpoint of suppressing the installation cost of the system, there has been room for improvement.

[0005] The present invention has been made in view of the above, and an object thereof is to provide a monitoring system and a monitoring program capable of reducing the installation cost.

Means for Solving the Problems

[0006] In order to solve the above-described problems and achieve the object, the monitoring system according to claim 1 is a monitoring system for monitoring a monitoring target in a monitoring environment, comprising: an acquisition means for acquiring imaging image information indicating an imaging image of the monitoring target; a state specifying means for specifying the state of the monitoring target based on the angle and / or position of a part of the monitoring target in the imaging image of the imaging image information acquired by the acquisition means; and a providing means for providing state information indicating the state of the monitoring target specified by the state specifying means.

[0007] The monitoring system according to claim 2 is the monitoring system according to claim 1, wherein the monitoring target includes a patient and / or a care recipient, the angle of a part of the monitoring target includes the angle of the upper body of the monitoring target and the angle of the neck of the monitoring target, and the position of a part of the monitoring target includes the position of the knee of the monitoring target and the position below the knee of the monitoring target.

[0008] The monitoring system according to claim 3 is the monitoring system according to claim 2, wherein the state specifying means determines whether the monitoring target is covered by a hanging object in the imaging image of the imaging image information, and specifies the state of the monitoring target with reference to the result of the determination.

[0009] The monitoring system according to claim 4 is the monitoring system according to any one of claims 1 to 3, wherein the acquisition means acquires past imaging image information indicating a past imaging image and past state information corresponding to the past imaging image information, the past state information indicating the state of the monitoring target in the past imaging image, and the state specifying means performs machine learning based on the past imaging image information and the past state information acquired by the acquisition means, and specifies the state of the monitoring target with reference to the result of the machine learning.

[0010] The monitoring system according to claim 5 is the monitoring system according to any one of claims 1 to 3, and includes an abnormality degree specifying means for specifying an abnormality degree indicating the degree of possibility that an abnormality regarding the state of the monitoring target occurs based on the state of the monitoring target specified by the state specifying means, and the providing means provides abnormality degree information indicating the abnormality degree specified by the abnormality degree specifying means together with the state information.

[0011] The monitoring system according to claim 6 is the monitoring system according to any one of claims 1 to 3, and includes a tendency specifying means for specifying a tendency of the state of the monitoring target based on a plurality of pieces of the state information having different time series, and the providing means provides tendency information indicating the tendency of the state of the monitoring target specified by the tendency specifying means.

[0012] The monitoring program according to claim 7 is a monitoring program for causing a monitoring system for monitoring a monitoring target in a monitoring environment to execute, and causes a computer to function as an acquisition means for acquiring imaging image information indicating an imaging image of the monitoring target, a state specifying means for specifying the state of the monitoring target based on an angle or / and a position of a part of the monitoring target in the imaging image of the imaging image information acquired by the acquisition means, and a providing means for providing state information indicating the state of the monitoring target specified by the state specifying means.

Effect of the Invention

[0013] According to the monitoring system described in claim 1 or the monitoring program described in claim 7, based on the angle and / or position of the part of the monitoring target in the captured image information of the captured image obtained by the acquisition means, there is provided a state specifying means for specifying the state of the monitoring target, and a providing means for providing state information indicating the state of the monitoring target specified by the state specifying means. Therefore, compared with the prior art (a technique for discriminating the state of a person requiring care based on the body pressure distribution of the person requiring care detected by a sensor made of elastomer), the cost of the means for specifying the state of the monitoring target can be reduced, and the installation cost of the monitoring system can be reduced. Also, the state of the monitoring target can be specified based on the angle and / or position of the part of the monitoring target, and the accuracy of the specification can be improved.

[0014] According to the monitoring system described in claim 2, the monitoring target includes a patient and / or a person requiring care. The angle of the part of the monitoring target includes the angle of the upper body of the monitoring target and the angle of the neck of the monitoring target. The position of the part of the monitoring target includes the position of the knees of the monitoring target and the position below the knees of the monitoring target. Therefore, the state of the monitoring target can be specified more accurately, and the accuracy of the specification can be further improved.

[0015] According to the monitoring system described in claim 3, the state specifying means determines whether the monitoring target in the captured image of the captured image information is covered by a hanging object, and based on the result of the determination, specifies the state of the monitoring target. Therefore, the state of the monitoring target can be specified even more accurately, and the accuracy of the specification can be further improved.

[0016] According to the monitoring system described in claim 4, the acquisition means acquires past captured image information and past state information corresponding to the past captured image information. The state specifying means performs machine learning based on the past captured image information and past state information acquired by the acquisition means, and based on the result of the machine learning, specifies the state of the monitoring target. Therefore, the state of the monitoring target can be specified even more accurately, and the accuracy of the specification can be further improved.

[0017] According to the monitoring system described in claim 5, it includes an abnormality degree specifying means for specifying an abnormality degree based on the state of the monitoring target specified by the state specifying means, and the providing means provides abnormality degree information indicating the abnormality degree specified by the abnormality degree specifying means together with the state information. Therefore, it is possible to easily grasp the degree of possibility that an abnormality related to the state of the monitoring target occurs, and it becomes possible to take appropriate measures before the occurrence of the abnormality.

[0018] According to the monitoring system described in claim 6, it includes a tendency specifying means for specifying the tendency of the state of the monitoring target based on a plurality of state information with different time series, and the providing means provides tendency information indicating the tendency of the state of the monitoring target specified by the tendency specifying means. Therefore, it is possible to grasp the tendency of the state of the monitoring target, and it becomes possible to take measures according to the tendency.

Brief Description of the Drawings

[0019]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Modes for Carrying Out the Invention

[0020] With reference to the accompanying drawings, embodiments of the monitoring system and monitoring program according to the present invention will be described in detail. First, [I] the basic concept of the embodiment will be described, then [II] the specific content of the embodiment will be described, and finally, [III] modifications to the embodiment will be described. However, the present invention is not limited by the embodiments.

[0021] [I] Basic Concept of the Embodiment First, the basic concept of the embodiment will be described. The embodiment generally relates to a monitoring system and a monitoring program for monitoring a monitoring target in a monitoring environment.

[0022] Here, the "monitoring environment" means the environment where the monitoring target is temporarily or permanently located. This monitoring environment includes, for example, the wards of medical facilities, the rooms of nursing facilities, specific rooms (such as the living room as an example) in single-family or apartment houses, the store areas of commercial facilities, the working areas of factory facilities, etc. In the embodiment, the wards of medical facilities where the above patients are admitted and the rooms of nursing facilities will be described.

[0023] Also, the "monitoring target" means the object to be monitored. This monitoring target includes, for example, patients admitted to medical facilities, care recipients living in nursing facilities, children or the elderly in single-family or apartment houses, customers in commercial facilities, and / or workers in factory facilities. In the embodiment, patients admitted to medical facilities and care recipients living in nursing facilities will be described.

[0024] [II] Specific Content of the Embodiment Next, the specific content of the embodiment will be described.

[0025] [Embodiment 1] First, the monitoring system according to Embodiment 1 will be described. This Embodiment 1 is configured to include an acquisition unit to be described later, a state determination unit to be described later, and a provision unit to be described later.

[0026] (Configuration) First, the configuration of the monitoring system according to Embodiment 1 will be described.

[0027] The monitoring system 1 is a system for monitoring a monitoring target (specifically, a patient hospitalized in a medical facility or a care recipient living in a care facility) in a monitoring environment (specifically, a hospital ward in a medical facility or a living room in a care facility). As shown in FIG. 1, it includes a terminal device 10 and a processing device 20.

[0028] Here, although one terminal device 10 is shown in FIG. 1, actually, the terminal device 10 is configured to include a plurality of terminal devices 10 held by two or more monitors described later, and a processing device 20 capable of communicating with these plurality of terminal devices 10 via a network 2. However, it is not limited to this. For example, there may be only one terminal device 10.

[0029] (Configuration - Terminal Device) First, the configuration of the terminal device 10 will be described.

[0030] The terminal device 10 is a device held by a monitor (not shown), and is a device for communicating various information with the processing device 20. This terminal device 10 is communicably connected to the processing device 20 via a network 2. As shown in FIG. 1, it includes a terminal-side communication unit 11, a terminal-side operation unit 12, a terminal-side output unit 13, a terminal-side power supply unit 14, a terminal-side control unit 15, and a terminal-side storage unit 16. However, for the configuration of the terminal device 10 that is not particularly noted, the description will be omitted as being the same as that of a known portable terminal such as a smartphone.

[0031] Note that the "monitor" is a person who monitors the monitoring target. This monitor includes, for example, doctors and nurses in medical facilities, caregivers in care facilities, relatives of children and the elderly in general housing or apartment houses, store clerks in commercial facilities, managers of factory facilities, etc. However, in Embodiment 1, it will be described as doctors and nurses in medical facilities and caregivers in care facilities.

[0032] (Configuration - Terminal Device - Terminal-Side Communication Unit) The terminal-side communication unit 11 is terminal-side communication means for performing communication at least with the processing device 20, and is configured using, for example, known communication means for performing wireless communication using a wireless communication network (as an example, communication means using a long-distance wireless communication standard such as 4G, 5G, wireless LAN, or LTE (registered trademark), etc.). However, it is not limited to this, and for example, it may be configured using communication means for performing wired communication using a wired communication network.

[0033] (Configuration - Terminal Device - Terminal-side Operation Unit) The terminal-side operation unit 12 is terminal-side operation means for receiving operation inputs to the terminal device 10, and is configured using known operation means such as various switches and touch pads.

[0034] (Configuration - Terminal Device - Terminal-side Output Unit) The terminal-side output unit 13 is output means for outputting various information based on the control of the terminal-side control unit 15, and is configured using, for example, known display means (as an example, a display) or / and voice output means (as an example, a speaker).

[0035] (Configuration - Terminal Device - Terminal-side Power Supply Unit) The terminal-side power supply unit 14 is terminal-side power supply means for supplying power to each part of the terminal device 10.

[0036] (Configuration - Terminal Device - Terminal-side Control Unit) The terminal-side control unit 15 is terminal-side control means for controlling the terminal device 10. Specifically, this terminal-side control unit 15 is a computer configured to include a CPU, various programs (including basic control programs such as an OS and application programs that are interpreted and executed on the CPU and that realize specific functions when launched on the OS), and internal memory such as a RAM for storing programs and various data (note that the same applies to the configuration of the processing-side control unit 22 described later).

[0037] Note that the details of the processing executed by this terminal-side control unit 15 will be described later.

[0038] (Configuration - Terminal Device - Terminal - Side Memory Unit) The terminal - side memory unit 16 is a terminal - side memory means for storing programs and various data necessary for the operation of the terminal device 10. Specifically, this terminal - side memory unit 16 is configured using a rewritable recording medium, and for example, a non - volatile recording medium such as a flash memory can be used (the same applies to the configuration of the processing - side memory unit 23 described later).

[0039] (Configuration - Processing Device) Next, the configuration of the processing device 20 will be described.

[0040] The processing device 20 is a device for executing processing related to the monitoring of a monitoring target in a monitoring environment. This processing device 20 is communicably connected to the terminal device 10 via the network 2, and as shown in FIG. 1, includes a processing - side communication unit 21, a processing - side control unit 22, and a processing - side memory unit 23. However, for the configuration of the processing device 20 that is not particularly noted, the description will be omitted assuming it is the same as a known cloud server.

[0041] (Configuration - Processing Device - Processing - Side Communication Unit) The processing - side communication unit 21 is a processing - side communication means for communicating with the terminal device 10. For example, it is configured using a known communication means for performing wireless communication using a wireless communication network (as an example, communication means using a long - distance wireless communication standard such as 4G, 5G, wireless LAN, or LTE (registered trademark), etc.). However, it is not limited to this, and for example, it may be configured using a communication means for performing wired communication using a wired communication network.

[0042] (Configuration - Processing Device - Processing - Side Control Unit) The processing - side control unit 22 is a processing - side control means for controlling each part of the processing device 20. As shown in FIG. 1, functionally conceptually, it includes an acquisition unit 22a, a state determination unit 22b, and a provision unit 22c.

[0043] Note that the monitoring program according to Embodiment 1 (specifically, the monitoring program for executing the monitoring process described later) is installed in the processing device 20 via an arbitrary recording medium or the network 2, thereby substantially constituting each part of the processing side control unit 22.

[0044] (Configuration - Processing Device - Processing Side Control Unit - Acquisition Unit) The acquisition unit 22a is an acquisition means for acquiring imaging image information.

[0045] Here, the "imaging image information" is information indicating an imaging image obtained by imaging a monitoring target.

[0046] This imaging image information includes, for example, imaging image information directly or indirectly obtained from known imaging means (for example, a still image camera, a video camera, etc.) provided at a predetermined position (as an example, the ceiling part, the wall part, the floor part, etc.) in the monitoring environment. In Embodiment 1, it will be described as imaging image information obtained from known imaging means provided at the ceiling part of a hospital room or a living room of a nursing facility.

[0047] (Configuration - Processing Device - Processing Side Control Unit - State Identification Unit) The state identification unit 22b is a state identification means for identifying the state of the monitoring target based on the angle or / and position of the part of the monitoring target in the imaging image of the imaging image information acquired by the acquisition unit 22a.

[0048] Here, the "angle of the part of the monitoring target" includes, for example, the angle of the upper body of the monitoring target, the angle of the neck of the monitoring target, the angle of the knee of the monitoring target, or / and the angle below the knee of the monitoring target. In Embodiment 1, from the perspective of accurately identifying the state of the monitoring target, it will be described as including the angle of the upper body of the monitoring target and the angle of the neck of the monitoring target.

[0049] Further, the "position of the part to be monitored" is a concept including, for example, the position of the upper body of the object to be monitored, the position of the neck of the object to be monitored, the position of the knees of the object to be monitored, and / or the position below the knees of the object to be monitored. However, in Embodiment 1, from the viewpoint of accurately specifying the state of the object to be monitored, it will be described as including the position of the knees of the object to be monitored and the position below the knees of the object to be monitored.

[0050] Also, in Embodiment 1, the "state of the object to be monitored" corresponds to, for example, the state where the object to be monitored is sleeping in bed (specifically, the posture state at bedtime and the sleep state at bedtime), the state where the object to be monitored is getting out of bed (specifically, the posture state at getting up and the movement state at getting up).

[0051] (Configuration - Processing Device - Processing - Side Control Unit - Providing Unit) The providing unit 22c is a providing means for providing information indicating the state of the object to be monitored specified by the state specifying unit 22b (hereinafter referred to as "state information").

[0052] Details of the processing executed by this processing - side control unit 22 will be described later.

[0053] (Configuration - Processing Device - Processing - Side Storage Unit) The processing - side storage unit 23 is a processing - side storage means for recording programs and various data necessary for the operation of the processing device 20. As shown in FIG. 1, it includes a state database (hereinafter, the database is referred to as "DB") 23a.

[0054] (Configuration - Processing Device - Processing - Side Storage Unit - State DB) The state DB 23a is a state - information storage means for storing state information.

[0055] As shown in FIG. 2, this state DB 23a is configured by associating with each other the items "upper - body angle information", "neck angle information", "knee - position information", "position - below - knees information", and "state information", and the information corresponding to each item.

[0056] Among these, the information corresponding to the item "upper body angle information" is the upper body angle information indicating the angle of the upper body of the monitoring target (specifically, the angle in the vertical direction). As shown in FIG. 2, "less than 60°" or the like, which is the angle of the upper body of the monitoring target, is applicable.

[0057] Also, the information corresponding to the item "neck angle information" is the neck angle information indicating the angle of the neck of the monitoring target (specifically, the angle in the horizontal direction). As shown in FIG. 2, "-45° < angle < +45°" or the like, which is the angle of the neck of the monitoring target, is applicable (note that the "-" shown in FIG. 2 indicates that the angle of the neck of the monitoring target is not relevant).

[0058] Also, the information corresponding to the item "knee position information" is the knee position information indicating the position of the knee of the monitoring target (specifically, the position in the horizontal direction). As shown in FIG. 2, "a position outside the shoulders of the monitoring target" or the like, which is the position of the knee of the monitoring target, is applicable (note that the "-" shown in FIG. 2 indicates that the position of the knee of the monitoring target is not relevant).

[0059] Also, the information corresponding to the item "below-knee position information" is the below-knee position information indicating the position below the knee of the monitoring target (specifically, the position in the horizontal direction). As shown in FIG. 2, "a position inside the bed" or the like, which is the position below the knee of the monitoring target, is applicable (note that the "-" shown in FIG. 2 indicates that the position below the knee of the monitoring target is not relevant).

[0060] Also, the information corresponding to the item "status information" is the status information. As shown in FIG. 2, "supine position" or the like, which is the status of the monitoring target, is applicable.

[0061] Note that the method for generating this status information is arbitrary. For example, it may be generated as follows (note that the method for generating the abnormality degree information of the abnormality degree DB23b described later and the method for generating the trend information of the trend DB23c described later are also substantially the same).

[0062] That is, after the processing side control unit 22 of the processing device 20 acquires past captured image information indicating a past captured image and past state information corresponding to the past captured image information by a predetermined method, a known statistical processing method or a known machine learning method is used to determine the causal relationship between the past captured image information and the past state information (as an example, the causal relationship between the angle or / and position of the part of the patient or / and the caregiver and the state of the monitoring target). Then, among the past state information, the past state information with a deep causal relationship may be extracted, and the extracted information may be generated as state information.

[0063] Alternatively, the processing side control unit 22 of the processing device 20 may generate information arbitrarily set by the administrator of the processing device 20 as state information.

[0064] (Monitoring Process) Next, the monitoring process executed by the terminal side control unit 15 of the terminal device 10 configured as described above and the processing side control unit 22 of the processing device 20 will be described.

[0065] In the following description, in the description of each process shown in FIG. 3, the steps are abbreviated as "S".

[0066] (Monitoring Process - Introduction) The monitoring process is a process for monitoring a monitoring target in a monitoring environment.

[0067] The timing for executing this monitoring process is arbitrary. However, in the first embodiment, it will be described as being started after the power of the terminal device 10 and the processing device 20 is turned on.

[0068] In the first embodiment, although the monitoring system 1 includes a plurality of terminal devices 10, the contents of the monitoring process executed by these terminal devices 10 are all the same. Therefore, hereinafter, the monitoring process executed by the terminal device 10 to be described (hereinafter referred to as the "target terminal device") and the processing device 20 will be described.

[0069] (Monitoring Process - Details of the Process) When the monitoring process is started, as shown in FIG. 3, in SA1, the processing side control unit 22 of the processing device 20 determines whether the timing for providing the state information (hereinafter referred to as "providing timing") has arrived.

[0070] The method for determining whether this providing timing has arrived is arbitrary. However, in Embodiment 1, after the start of the monitoring process (or after it is determined in SA5 described later that the end timing described later has not arrived), it is determined based on whether a predetermined time (for example, one hour, etc.) has elapsed, or whether information indicating a request to provide state information (hereinafter referred to as "providing request information") has been received from the target terminal device via a dedicated application (or a dedicated website).

[0071] Here, when the above-mentioned predetermined time has elapsed or the above-mentioned providing request information has been received, it is determined that the providing timing has arrived. When the above-mentioned predetermined time has not elapsed and the above-mentioned providing request information has not been received, it is determined that the providing timing has not arrived.

[0072] Then, the processing side control unit 22 of the processing device 20 waits until it is determined that the providing timing has arrived (SA1, No). When it is determined that the providing timing has arrived (SA1, Yes), the process proceeds to SA2.

[0073] In SA2, the acquisition unit 22a of the processing device 20 acquires imaging image information.

[0074] Specifically, the acquisition unit 22a of the processing device 20 is imaging means provided at a predetermined position within the monitoring environment and directly or indirectly acquires imaging image information from the imaging means that has been previously associated with the target terminal device (specifically, the imaging means that images the monitoring target monitored by the monitor of the target terminal device) (when a plurality of imaging means are provided, imaging image information may be acquired from each imaging means).

[0075] In SA3, the state specifying unit 22b of the processing device 20 specifies the state of the monitoring target.

[0076] The method for specifying the state of the monitoring target is arbitrary, but in the first embodiment, it is specified as follows.

[0077] That is, first, the state specifying unit 22b of the processing device 20 uses a known image analysis method to specify the angle or / and position of the part of the monitoring target in the captured image of the captured image information obtained in SA2.

[0078] Specifically, the angle of the upper body of the monitoring target, the angle of the neck of the monitoring target, the position of the knee of the monitoring target, and the position below the knee of the monitoring target are specified.

[0079] Note that since the specification of the angle or / and position of the part of the monitoring target is performed based on the captured image information obtained by capturing the monitoring target without attaching a marker to the monitoring target, the specification can be performed simply and easily.

[0080] Then, the state specifying unit 22b of the processing device 20 refers to the information stored in the state DB 23a and specifies the state of the monitoring target based on the angle or / and position of the part of the monitoring target specified above.

[0081] Specifically, the state specifying unit 22b of the processing device 20 extracts the upper body angle information corresponding to the angle of the upper body of the specified monitoring target from among the upper body angle information stored in the state DB 23a. Also, the state specifying unit 22b extracts the neck angle information corresponding to the angle of the neck of the specified monitoring target from among the neck angle information stored in the state DB 23a. Further, the state specifying unit 22b extracts the knee position information corresponding to the position of the knee of the specified monitoring target from among the knee position information stored in the state DB 23a. Additionally, the state specifying unit 22b extracts the position information below the knee corresponding to the position below the knee of the specified monitoring target from among the position information below the knee stored in the state DB 23a. Then, the state specifying unit 22b extracts the state information corresponding to the extracted upper body angle information, neck angle information, knee position information, and position information below the knee from among the state information stored in the state DB 23a, and specifies the state of the monitoring target corresponding to the extracted state information as the state to be specified.

[0082] As an example, when the angle of the upper body of the specified monitoring target = 0°, the angle of the neck of the specified monitoring target = -50°, the position of the knee of the specified monitoring target = a position inside the shoulder of the monitoring target, and the position below the knee of the specified monitoring target = a position inside the bed, with reference to the state DB 23a in FIG. 2, the state of the monitoring target = left lateral lying position (the lying position on the side opposite to the wall side) may be specified.

[0083] However, it is not limited to this. For example, when the angle of the upper body of the specified monitoring target < 60°, the state of the monitoring target may be specified based on only one of the angle of the neck of the specified monitoring target or the position of the knee of the specified monitoring target (when specifying the state of the monitoring target based on the angle of the upper body of the specified monitoring target and the angle of the neck of the specified monitoring target, the state of the monitoring target can be specified based on only the angle of the part of the monitoring target in the captured image of the captured image information).

[0084] Also, the state specifying unit 22b of the processing device 20 determines whether the monitoring target in the captured image of the captured image information acquired at SA2 is covered by a hanging object (e.g., futon, blanket, towel, etc.), and may specify the state of the monitoring target with reference to the result of the determination.

[0085] As an example, first, the state specifying unit 22b of the processing device 20 determines whether the monitoring target is covered with a hanging object by using a known image analysis method.

[0086] Here, when it is determined that the monitoring target is covered with a hanging object, since it is difficult to specify the position of the knees of the monitoring target, the state of the monitoring target may be specified based on only the angle of the upper body of the monitoring target specified above, the angle of the neck of the monitoring target specified above, and the position below the knees of the monitoring target.

[0087] Alternatively, the state specifying unit 22b of the processing device 20 performs machine learning (specifically, creates a machine learning model) based on the past captured image information and past state information acquired by the acquisition unit 22a and related to the monitoring target being covered with a hanging object, and may specify the state of the monitoring target with reference to the machine learning (specifically, specify the state of the monitoring target using the machine learning model).

[0088] On the other hand, when it is determined that the monitoring target is not covered with a hanging object, the state of the monitoring target may be specified based on the angle of the upper body of the monitoring target specified above, the angle of the neck of the monitoring target specified above, the position of the knees of the monitoring target specified above, and the position below the knees of the monitoring target specified above.

[0089] Alternatively, the state specifying unit 22b of the processing device 20 performs machine learning (specifically, creates a machine learning model) based on the past captured image information and past state information acquired by the acquisition unit 22a and related to the monitoring target not being covered with a hanging object, and may specify the state of the monitoring target with reference to the machine learning (specifically, specify the state of the monitoring target using the machine learning model).

[0090] By such processing, the state of the monitoring target can be specified more accurately, and the accuracy of the specification can be further improved.

[0091] Returning to FIG. 3, in SA4, the providing unit 22c of the processing device 20 provides state information indicating the state of the monitoring target specified in SA3.

[0092] The method of providing this state information is arbitrary. However, in Embodiment 1, the state information is transmitted to the target terminal device, and the transmitted state information is output to the terminal-side output unit 13 of the target terminal device (specifically, the display means, the audio output means), thereby providing it.

[0093] Thereby, the state information can be presented to the monitor of the target terminal device, and the monitor can grasp the details of the state of the monitoring target.

[0094] However, it is not limited to this. For example, the providing unit 22c of the processing device 20 may transmit the state information to another device other than the target terminal device (for example, another terminal device 10, an external device (as an example, a management device that manages the processing device 20, etc.)), and output the transmitted state information to the output means of the other device, thereby providing it.

[0095] Alternatively, the providing unit 22c of the processing device 20 may provide the state information only by transmitting the state information to the target terminal device. In this case, the terminal-side control unit 15 of the target terminal device may output the state information to the terminal-side output unit 13 at the timing when a predetermined operation is received via the terminal-side operation unit 12.

[0096] In SA5, the processing-side control unit 22 of the processing device 20 determines whether or not the timing to end the monitoring process (hereinafter referred to as the "end timing") has arrived.

[0097] The method of determining whether or not this end timing has arrived is arbitrary. However, in Embodiment 1, it is determined based on whether or not information indicating that it is required to end the monitoring process (hereinafter referred to as "end request information") has been received from the target terminal device via a dedicated application (or a dedicated website), or whether or not a predetermined monitoring period (for example, one week, etc.) has elapsed since the start of the monitoring process.

[0098] Here, when the above-mentioned end request information is received, or when the above-mentioned predetermined monitoring period has elapsed, it is determined that the end timing has arrived. When the above-mentioned end request information has not been received and the above-mentioned predetermined monitoring period has not elapsed, it is determined that the end timing has not arrived.

[0099] Then, when it is determined that the above-mentioned end timing has arrived (SA5, Yes), the processing side control unit 22 of the processing device 20 ends the monitoring process. On the other hand, when it is determined that the above-mentioned end timing has not arrived (SA5, No), the processing side control unit 22 of the processing device 20 shifts to SA1 and repeats the processes from SA1 to SA5 in the same manner thereafter.

[0100] Through such a monitoring process, compared with the prior art (a technique for discriminating the state of a person requiring care based on the body pressure distribution of the person requiring care detected by a sensor made of elastomer), the cost of the means for specifying the state of the monitoring target can be reduced, and the installation cost of the monitoring system 1 can be reduced. In addition, the state of the monitoring target can be specified based on the angle or / and position of the part of the monitoring target in the captured image of the captured image information acquired by the acquisition means, and the accuracy of the specification can be improved.

[0101] (Effect of Embodiment 1) As described above, according to Embodiment 1, based on the angle or / and position of the part of the monitoring target in the captured image of the captured image information acquired by the acquisition means, there are provided a state specifying unit 22b for specifying the state of the monitoring target, and a providing unit 22c for providing state information indicating the state of the monitoring target specified by the state specifying unit 22b. Therefore, compared with the prior art (a technique for discriminating the state of a person requiring care based on the body pressure distribution of the person requiring care detected by a sensor made of elastomer), the cost of the means for specifying the state of the monitoring target can be reduced, and the installation cost of the monitoring system 1 can be reduced. In addition, the state of the monitoring target can be specified based on the angle or / and position of the part of the monitoring target, and the accuracy of the specification can be improved.

[0102] In addition, the monitoring target includes the patient and / or the caregiver. The angles of the parts of the monitoring target include the angle of the upper body of the monitoring target and the angle of the neck of the monitoring target. The positions of the parts of the monitoring target include the position of the knees of the monitoring target and the position below the knees of the monitoring target. Therefore, the state of the monitoring target can be specified more accurately, and the accuracy of the specification can be further improved.

[0103] In addition, the state specifying unit 22b determines whether the monitoring target in the captured image of the captured image information is covered by a hanging object, and refers to the result of the determination to specify the state of the monitoring target. Therefore, the state of the monitoring target can be specified even more accurately, and the accuracy of the specification can be further improved.

[0104] [Embodiment 2] Next, the monitoring system according to Embodiment 2 will be described. In addition to the configuration of the monitoring system according to Embodiment 1, this Embodiment 2 further includes an abnormality degree specifying unit and a trend specifying unit described later. However, the configuration of this Embodiment 2 is substantially the same as the configuration of Embodiment 1 except in the case of special description. For the configuration substantially the same as the configuration of Embodiment 1, the same reference numerals and / or names as those used in this Embodiment 1 are attached as necessary, and the description thereof is omitted.

[0105] (Configuration) First, the configuration of the monitoring system according to Embodiment 2 will be described.

[0106] As shown in FIG. 4, the monitoring system 100 includes a terminal device 10 and a processing device 20.

[0107] (Configuration - Terminal Device) First, the configuration of the terminal device 10 will be described.

[0108] The terminal device 10 according to Embodiment 2 is configured substantially the same as the terminal device 10 according to Embodiment 1.

[0109] (Configuration - Processing Device) Next, the configuration of the processing device 20 will be described.

[0110] The processing device 20 according to Embodiment 2 is configured substantially the same as the processing device 20 according to Embodiment 1. However, the following improvements are made to the details of the configurations of the processing side control unit 22 and the processing side storage unit 23.

[0111] (Configuration - Processing Device - Processing Side Control Unit) As shown in FIG. 4, the processing side control unit 22 functionally conceptually includes an acquisition unit 22a, a state identification unit 22b, a provision unit 22c, an abnormality degree identification unit 22d, and a trend identification unit 22e.

[0112] (Configuration - Processing Device - Processing Side Control Unit - Abnormality Degree Identification Unit) Among these, the abnormality degree identification unit 22d is an abnormality degree identification means for identifying an abnormality degree indicating the degree of possibility that an abnormality related to the state of the monitoring target occurs based on the state of the monitoring target identified by the state identification unit 22b.

[0113] Here, the "abnormality related to the state of the monitoring target" includes, for example, the monitoring target falling or toppling while in bed or getting up, the monitoring target falling while in the living room, entrance, or staircase, the monitoring target not moving while in the living room, etc. However, in Embodiment 2, it will be described as the monitoring target falling or toppling while in bed or getting up.

[0114] Also, in Embodiment 2, the "abnormality degree" is described as three degrees (specifically, as shown in FIG. 5, "low possibility of abnormality occurring", "possibility of abnormality occurring", and "high possibility of abnormality occurring" (increasing in the order of description)). However, it is not limited to this, and for example, it may be two degrees or four or more degrees.

[0115] (Configuration - Processing Device - Processing Side Control Unit - Trend Identification Unit) Returning to FIG. 4, the trend identification unit 22e is a trend identification means for identifying the trend of the state of the monitoring target based on a plurality of state information with different time series.

[0116] Here, the "tendency of the state of the object to be monitored" in the second embodiment corresponds to, for example, the tendency for the object to be monitored to frequently turn over, the tendency for the object to have a poor sleeping posture, and the tendency for the object to frequently wander around.

[0117] (Configuration - Processing Device - Processing - side Storage Unit) As shown in FIG. 4, the processing - side storage unit 23 includes a state DB 23a, an abnormality degree DB 23b, and a tendency DB 23c.

[0118] (Configuration - Processing Device - Processing - side Storage Unit - Abnormality Degree DB) Among these, the abnormality degree DB 23b is an abnormality degree information storage means for storing abnormality degree information.

[0119] Here, the "abnormality degree information" is information indicating the above - mentioned abnormality degree (specifically, the degree of the possibility of falling or tumbling in the state where the object to be monitored is going to bed or getting up in the bed).

[0120] As shown in FIG. 5, this abnormality degree DB 23b is configured by associating the item "state information" and the item "abnormality degree information" with the information corresponding to each item.

[0121] Among these, the information corresponding to the item "state information" is state information, and as shown in FIG. 5, it corresponds to the state of the object to be monitored such as "supine position".

[0122] Also, the information corresponding to the item "abnormality degree information" is abnormality degree information, and as shown in FIG. 5, it corresponds to the above - mentioned abnormality degree such as "there may be an abnormality".

[0123] (Configuration - Processing Device - Processing - side Storage Unit - Tendency DB) Returning to FIG. 4, the tendency DB 23c is a tendency information storage means for storing tendency information.

[0124] Here, the "tendency information" is information indicating the tendency of the state of the object to be monitored.

[0125] As shown in FIG. 6, this tendency DB23c is configured by associating the item “status history information” and the item “tendency information” with the information corresponding to each item.

[0126] Among these, the information corresponding to the item “status history information” is status history information indicating the time-series history of the status of the monitoring target. As shown in FIG. 6, the time-series history of the status of the monitoring target such as “having performed the right lateral decubitus position or / and the left lateral decubitus position a predetermined number of times or more” is applicable.

[0127] Also, the information corresponding to the item “tendency information” is tendency information. As shown in FIG. 6, the tendency of the status of the monitoring target such as “the monitoring target has a tendency to frequently turn over” is applicable.

[0128] (Monitoring Process) Next, the monitoring process executed by the terminal-side control unit 15 of the terminal device 10 and the process-side control unit 22 of the processing device 20 configured as described above will be described.

[0129] Regarding the monitoring process according to the second embodiment, since the processes of SB1 to SB3 in FIG. 7 are the same as the processes of SA1 to SA3 in FIG. 3, the description of the processes of SB1 to SB3 in FIG. 7 will be omitted.

[0130] As shown in FIG. 7, in SB4, the abnormality degree specifying unit 22d of the processing device 20 specifies the abnormality degree.

[0131] The method of specifying this abnormality degree is arbitrary. In the second embodiment, among the status information stored in the abnormality degree DB23b, the status information indicating the status of the monitoring target specified in SB3 is extracted. Then, among the abnormality degree information stored in the abnormality degree DB23b, the abnormality degree information corresponding to the extracted status information is extracted, and the abnormality degree of the extracted abnormality degree information is specified as the abnormality degree to be specified.

[0132] As an example, when the state of the monitoring target specified by SB3 is the left lateral position (the lying position opposite to the wall side), referring to the abnormality degree DB23b in FIG. 5, the abnormality degree = "high possibility of occurrence of an abnormality" may be specified.

[0133] Returning to FIG. 7, in SB5, the providing unit 22c of the processing device 20 provides state information indicating the state of the monitoring target specified by SB3 and abnormality degree information indicating the abnormality degree specified by SB4, in substantially the same manner as the processing of SA4.

[0134] Through the processing of SB4 and SB5 as described above, it is possible to easily grasp the degree of possibility of occurrence of an abnormality related to the state of the monitoring target, and it becomes possible to take appropriate measures before the occurrence of the abnormality.

[0135] In SB6, the processing side control unit 22 of the processing device 20 determines whether the timing for providing the trend information (hereinafter referred to as "trend providing timing") has arrived.

[0136] The method for determining whether or not this trend providing timing has arrived is arbitrary. However, in the second embodiment, it is determined based on whether information indicating a request to provide trend information (hereinafter referred to as "trend providing request information") has been received from the target terminal device via a dedicated application (or a dedicated website), or whether the number of executions of the processing of SB4 has reached a predetermined number of times or more (for example, 10 times or more, etc.).

[0137] Here, when the above-mentioned trend providing request information is received, or when the above-mentioned predetermined number of times or more is reached, it is determined that the trend providing timing has arrived. When the above-mentioned trend providing request information has not been received, and when the above-mentioned predetermined number of times or more has not been reached, it is determined that the trend providing timing has not arrived.

[0138] Note that, for example, even when the above-mentioned trend providing request information is received, if the above-mentioned predetermined number of times is only once, it may be determined that the trend providing timing has not arrived.

[0139] Then, when it is determined that the tendency provision timing has arrived (SB6, Yes), the processing side control unit 22 of the processing device 20 shifts to SB7, and when it is determined that the tendency provision timing has not arrived (SB6, No), it shifts to SB9.

[0140] In SB7, the tendency specifying unit 22e of the processing device 20 specifies the tendency of the state of the monitoring target.

[0141] Although the method for specifying the tendency of the state of the monitoring target is arbitrary, in the second embodiment, among the state history information stored in the tendency DB 23c, a plurality of state information provided in SB4 by SB7 until the processing of SB7 (specifically, a plurality of state information with different time series) is extracted for the state history information that matches the state of the monitoring target. Then, among the tendency information stored in the tendency DB 23c, the tendency information corresponding to the extracted state history information is extracted, and the tendency of the extracted tendency information is specified as the tendency of the state of the monitoring target to be specified.

[0142] As an example, when a plurality of state information (a plurality of state information with different time series) provided in SB4 by SB7 until the processing of SB7 = "supine position", "right lateral position", "supine position", "right lateral position", "right lateral position", "left lateral position", "right lateral position", "right lateral position", "supine position", "right lateral position", with reference to the tendency DB 23c in FIG. 6, the tendency of the state of the monitoring target = "the tendency for the monitoring target to frequently turn over" may be specified.

[0143] Returning to FIG. 7, in SB8, the providing unit 22c of the processing device 20 provides tendency information indicating the tendency of the state of the monitoring target specified in SB7, in substantially the same manner as the processing of SA4.

[0144] Through the processing from SB6 to SB8 like this, the tendency of the state of the monitoring target can be grasped, and it becomes possible to take measures according to the tendency.

[0145] In SB9, the processing side control unit 22 of the processing device 20 determines whether the end timing has arrived, in substantially the same manner as the processing of SA5.

[0146] Then, when it is determined that the above end timing has arrived (SB9, Yes), the processing side control unit 22 of the processing device 20 ends the monitoring process. On the other hand, when it is determined that the above end timing has not arrived (SB9, No), the processing side control unit 22 of the processing device 20 shifts to SB1 and repeats the processes from SB1 to SB9 in the same manner thereafter.

[0147] Through such a monitoring process, in addition to the state information, it is possible to provide abnormality degree information and trend information, and it becomes possible to effectively monitor the monitoring target.

[0148] (Effect of Embodiment 2) As described above, according to Embodiment 2, an abnormality degree specifying unit 22d that specifies an abnormality degree is provided based on the state of the monitoring target specified by the state specifying unit 22b, and the providing unit 22c provides the abnormality degree information indicating the abnormality degree specified by the abnormality degree specifying unit 22d together with the state information. Therefore, it is possible to easily grasp the degree of possibility that an abnormality related to the state of the monitoring target occurs, and it becomes possible to take appropriate measures before the abnormality occurs.

[0149] Further, a trend specifying unit 22e that specifies the trend of the state of the monitoring target is provided based on a plurality of state information having different time series, and the providing unit 22c provides trend information indicating the trend of the state of the monitoring target specified by the trend specifying unit 22e. Therefore, it is possible to grasp the trend of the state of the monitoring target, and it becomes possible to take measures according to the trend.

[0150] [III] Modification Examples of the Embodiment Although the embodiments of the present invention have been described above, the specific configurations and means of the present invention can be arbitrarily modified and improved within the scope of the technical idea of each invention described in the claims. Hereinafter, such modification examples will be described.

[0151] (Regarding the problems to be solved and the effects of the invention) First, the problems to be solved by the invention and the effects of the invention are not limited to the above-described content. According to the present invention, it is also possible to solve problems not described above or to achieve effects not described above. Further, it may solve only some of the described problems or achieve only some of the described effects.

[0152] (Regarding dispersion and integration) In addition, each of the above-described electrical components is a functional concept and does not necessarily need to be physically configured as shown in the drawings. That is, the specific form of dispersion or integration of each part is not limited to that shown in the drawings, and all or part of them can be functionally or physically dispersed or integrated in any unit according to various loads, usage situations, etc. For example, the processing device 20 may be configured to be dispersed into a plurality of devices capable of communicating with each other, a processing-side control unit 22 may be provided in a part of these plurality of devices, and a processing-side storage unit 23 may be provided in another part of these plurality of devices (note that a part of the processing-side control unit 22 (for example, the acquisition unit 22a, etc.) may be configured to be dispersed from another part of the processing-side control unit 22). In this case, the processing-side control unit 22 and the processing-side storage unit 23 may be connected to each other via the network 2.

[0153] (Regarding shape, numerical value, structure, time series) Regarding the components exemplified in the embodiments and the drawings, the shape, numerical value, or the structure or time-series mutual relationship of a plurality of components can be arbitrarily modified and improved within the scope of the technical idea of the present invention.

[0154] (Regarding the state of the monitoring target) In the above-described Embodiments 1 and 2, it was explained that the state of the monitoring target corresponds to the state in which the monitoring target is sleeping in the bed and the state in which the monitoring target is getting up from the bed, but it is not limited thereto.

[0155] For example, when the monitoring target is a child or an elderly person in a general house or an apartment house, the state of the monitoring target may correspond to a state in which the monitoring target is walking or sitting.

[0156] In addition, when the object to be monitored is a customer in a commercial facility, the state of the object to be monitored may include a state in which the object to be monitored is staying in a purchase area or an event area.

[0157] In addition, when the object to be monitored is a worker in a factory facility, the state of the object to be monitored may include a state in which the object to be monitored is working or taking a break.

[0158] (Regarding the angle or / and position of the part of the object to be monitored) In the above-described Embodiment 1, it was described that the angle of the part of the object to be monitored includes the angle of the upper body of the object to be monitored and the angle of the neck of the object to be monitored, and the position of the part of the object to be monitored includes the position of the knees of the object to be monitored and the position below the knees of the object to be monitored, but it is not limited thereto. For example, the angle of the part of the object to be monitored may further include the angle of the knees of the object to be monitored or / and the angle below the knees of the object to be monitored. Further, the position of the part of the object to be monitored may further include the position of the upper body of the object to be monitored or / and the position of the neck of the object to be monitored.

[0159] Note that, for example, when the position of the part of the object to be monitored includes the position of the upper body of the object to be monitored, among the state information stored in the state DB23a, the state information regarding the lying position may include information indicating the details of the position of the object to be monitored on the bed.

[0160] As an example, among the state information regarding the right lateral lying position (lying position on the wall side), when the position of the upper body of the object to be monitored is located on the right side of the bed, the state information = "right lateral lying position at the position on the right side of the bed" may be included. Further, when the position of the upper body of the object to be monitored is located on the left side of the bed, the state information = "right lateral lying position at the position on the left side of the bed" may be included.

[0161] Thereby, it becomes possible to more accurately grasp the state of the object to be monitored.

[0162] (Regarding the monitoring system) In the above-described Embodiment 1, it has been described that the monitoring system 1 includes the terminal device 10 and the processing device 20, but it is not limited thereto. For example, the terminal device 10 may be omitted, and only the processing device 20 configured using a stationary personal computer may be provided (note that the same applies to the monitoring system 100 according to Embodiment 2).

[0163] In this case, for example, in the process of SA4 of the monitoring process, the providing unit 22c of the processing device 20 may provide the state information via the display means or the voice output means of the processing device 20 (note that the same applies to the processes of SB5 and SB8 according to Embodiment 2).

[0164] Also, in the above-described Embodiment 2, it has been described that the monitoring system 100 includes the abnormality degree specifying unit 22d and the trend specifying unit 22e, but it is not limited thereto. For example, either one of the abnormality degree specifying unit 22d or the trend specifying unit 22e may be omitted.

[0165] Note that when the abnormality degree specifying unit 22d is omitted, the abnormality degree DB23b may be omitted, and the processes of SB4 and the process of providing the abnormality degree information in SB5 of the monitoring process may also be omitted.

[0166] Also, when the trend specifying unit 22e is omitted, the trend DB23c may be omitted, and the processes from SB6 to SB8 of the monitoring process may also be omitted.

[0167] (Regarding the monitoring process) In the above-described Embodiment 1, it has been described that in the monitoring process, the processes of SA1 and SA5 are executed, but it is not limited thereto. For example, the processes of SA1 or / and SA5 may be omitted (note that the same applies to the processes of SB1 and SB9 according to Embodiment 2).

[0168] Also, in the above-described Embodiment 1, in SA3, the state specifying unit 22b of the processing device 20 refers to the information stored in the state DB23a and specifies the state of the monitoring target based on the angle or / and position of the part of the monitoring target specified by a known image analysis method, but it is not limited thereto.

[0169] For example, the acquisition unit 22a of the processing device 20 acquires past captured image information indicating the past captured images and past state information corresponding to the past captured image information, where the past state information indicates the state of the monitoring target in the past captured images (for example, past state information that matches the state of the monitoring target actually confirmed by the monitor, etc.). Then, the state identification unit 22b of the processing device 20 may perform machine learning based on the past captured image information and past state information acquired by the acquisition unit 22a, and refer to the result of the machine learning to identify the state of the monitoring target.

[0170] Here, the method for identifying the state of the monitoring target by referring to the result of the machine learning is arbitrary. For example, it may be identified as follows.

[0171] That is, first, referring to the information stored in the state DB 23a, the state of the monitoring target is tentatively identified based on the angle or / and position of the part of the monitoring target identified by a known image analysis method.

[0172] Next, it is determined whether the state of the monitoring target of the past state information having a high relevance (or high similarity) to the angle or / and position of the part of the monitoring target tentatively identified among the results of the machine learning matches (or whether the matching ratio is equal to or greater than a threshold value).

[0173] And when it is determined that they match (or when it is determined that the matching ratio is equal to or greater than the threshold value), the tentatively identified state of the monitoring target may be identified as the state to be identified.

[0174] On the other hand, when it is determined that they do not match (or when it is determined that the matching ratio is less than the threshold value), the tentatively identified state of the monitoring target may not be identified as the state to be identified. In this case, in the process of SA4, instead of the state information, information indicating that the state of the monitoring target cannot be identified may be provided.

[0175] Through such processing, the state of the monitoring target can be identified more accurately, and the accuracy of the identification can be further improved.

[0176] Also, in the above-described Embodiment 1, in SA5, it was explained that the processing-side control unit 22 of the processing device 20 determines whether the end timing has arrived based on whether the end request information has been received from the target terminal device via the dedicated application (or dedicated website). However, it is not limited to this. For example, when the processing of SA1 to SA4 is being performed, the processing-side control unit 22 of the processing device 20 determines whether end request information has been received from the target terminal device. If end request information has been received, the monitoring process may be terminated (note that the monitoring process according to Embodiment 2 is substantially the same).

[0177] Also, in the above-described Embodiment 2, in SB4, it was explained that the abnormality degree specifying unit 22d of the processing device 20 specifies the abnormality degree by referring to the information stored in the abnormality degree DB23b. However, it is not limited to this. For example, in addition to the information stored in the abnormality degree DB23b, the abnormality degree may be specified by referring to the tendency of the state of the monitoring target specified in SB7.

[0178] As an example, when the state of the monitoring target specified in SB3 = dorsal recumbent position and the state of the monitoring target specified in SB7 = the sleep phase of the monitoring target tends to be poor (or the monitoring target tends to be in a deep sleep state), among the abnormality degree information stored in the abnormality degree DB23b of FIG. 5, even if the abnormality degree information corresponding to the specified state of the monitoring target = "there is a possibility of an abnormality occurring", from the viewpoint of ensuring the safety of the monitoring target, the abnormality degree = "there is a high possibility of an abnormality occurring" may be specified.

[0179] Also, when the state of the monitoring target specified by SB3 = dorsal recumbent position and the state of the monitoring target specified by SB7 = the sleeping posture of the monitoring target tends to be good, among the abnormality degree information stored in the abnormality degree DB23b of FIG. 5, even if the abnormality degree information corresponding to the specified state of the monitoring target = "there may be an abnormality", from the perspective of ensuring the safety of the monitoring target, the abnormality degree may be specified as "the possibility of an abnormality occurring is low".

[0180] (Appendix) The monitoring system of Appendix 1 is a monitoring system for monitoring a monitoring target in a monitoring environment, comprising: an acquisition means for acquiring imaging image information indicating an imaging image of the monitoring target; a state specifying means for specifying the state of the monitoring target based on the angle and / or position of a part of the monitoring target in the imaging image of the imaging image information acquired by the acquisition means; and a providing means for providing state information indicating the state of the monitoring target specified by the state specifying means.

[0181] The monitoring system of Appendix 2 is the monitoring system according to Appendix 1, wherein the monitoring target includes a patient and / or a person requiring care, the angle of the part of the monitoring target includes the angle of the upper body of the monitoring target and the angle of the neck of the monitoring target, and the position of the part of the monitoring target includes the position of the knees of the monitoring target and the position below the knees of the monitoring target.

[0182] The monitoring system of Appendix 3 is the monitoring system according to Appendix 2, wherein the state specifying means determines whether the monitoring target is covered by a hanging object in the imaging image of the imaging image information, and specifies the state of the monitoring target with reference to the result of the determination.

[0183] The monitoring system of Supplementary Note 4 is the monitoring system according to any one of Supplementary Notes 1 to 3, wherein the acquisition means acquires past captured image information indicating the past captured images and past state information corresponding to the past captured image information, the past state information indicating the state of the monitoring target in the past captured image, and the state specifying means performs machine learning based on the past captured image information and the past state information acquired by the acquisition means, and specifies the state of the monitoring target with reference to the result of the machine learning.

[0184] The monitoring system of Supplementary Note 5 is the monitoring system according to any one of Supplementary Notes 1 to 3, and includes an abnormality degree specifying means for specifying an abnormality degree indicating the degree of possibility that an abnormality related to the state of the monitoring target occurs based on the state of the monitoring target specified by the state specifying means, and the providing means provides abnormality degree information indicating the abnormality degree specified by the abnormality degree specifying means together with the state information.

[0185] The monitoring system of Supplementary Note 6 is the monitoring system according to any one of Supplementary Notes 1 to 3, and includes a tendency specifying means for specifying the tendency of the state of the monitoring target based on a plurality of pieces of the state information having different time series, and the providing means provides tendency information indicating the tendency of the state of the monitoring target specified by the tendency specifying means.

[0186] The monitoring program of Supplementary Note 7 is a monitoring program for causing a monitoring system for monitoring a monitoring target in a monitoring environment to execute, and causes a computer to function as an acquisition means for acquiring captured image information indicating a captured image of the monitoring target, a state specifying means for specifying the state of the monitoring target based on the angle or / and position of the part of the monitoring target in the captured image of the captured image information acquired by the acquisition means, and a providing means for providing state information indicating the state of the monitoring target specified by the state specifying means.

[0187] (Effect of Supplementary Note) According to the monitoring system described in Supplementary Note 1 or the monitoring program described in Supplementary Note 7, based on the angle and / or position of the part of the monitoring target in the captured image information of the captured image obtained by the acquisition means, there are a state identification means for identifying the state of the monitoring target, and a providing means for providing state information indicating the state of the monitoring target identified by the state identification means. Therefore, compared with the prior art (a technique for discriminating the state of a care recipient based on the body pressure distribution of the care recipient detected by an elastomer sensor), the cost of the means for identifying the state of the monitoring target can be reduced, and the installation cost of the monitoring system can be reduced. Also, based on the angle and / or position of the part of the monitoring target, the state of the monitoring target can be identified, and the accuracy of the identification can be improved.

[0188] According to the monitoring system described in Supplementary Note 2, the monitoring target includes a patient and / or a care recipient. The angle of the part of the monitoring target includes the angle of the upper body of the monitoring target and the angle of the neck of the monitoring target. The position of the part of the monitoring target includes the position of the knees of the monitoring target and the position below the knees of the monitoring target. Therefore, the state of the monitoring target can be identified more accurately, and the accuracy of the identification can be further improved.

[0189] According to the monitoring system described in Supplementary Note 3, the state identification means determines whether the monitoring target in the captured image of the captured image information is covered by a hanging object, and based on the result of the determination, identifies the state of the monitoring target. Therefore, the state of the monitoring target can be identified even more accurately, and the accuracy of the identification can be further improved.

[0190] According to the monitoring system described in Supplementary Note 4, the acquisition means acquires past captured image information and past state information corresponding to the past captured image information. The state identification means performs machine learning based on the past captured image information and past state information acquired by the acquisition means, and based on the result of the machine learning, identifies the state of the monitoring target. Therefore, the state of the monitoring target can be identified even more accurately, and the accuracy of the identification can be further improved.

[0191] According to the monitoring system described in Supplementary Note 5, it includes an abnormality degree specifying means for specifying the degree of abnormality based on the state of the monitoring target specified by the state specifying means. The providing means provides the abnormality degree information indicating the degree of abnormality specified by the abnormality degree specifying means together with the state information. Therefore, it is possible to easily grasp the degree of possibility that an abnormality related to the state of the monitoring target occurs, and it becomes possible to take appropriate measures before the occurrence of the abnormality.

[0192] According to the monitoring system described in Supplementary Note 6, it includes a tendency specifying means for specifying the tendency of the state of the monitoring target based on a plurality of state information with different time series. The providing means provides the tendency information indicating the tendency of the state of the monitoring target specified by the tendency specifying means. Therefore, it is possible to grasp the tendency of the state of the monitoring target, and it becomes possible to take measures according to the tendency.

Explanation of Reference Signs

[0193] 1 Monitoring system 2 Network 10 Terminal device 11 Terminal-side communication unit 12 Terminal-side operation unit 13 Terminal-side output unit 14 Terminal-side power supply unit 15 Terminal-side control unit 16 Terminal-side storage unit 20 Processing device 21 Processing-side communication unit 22 Processing-side control unit 22a Acquisition unit 22b State specifying unit 22c Providing unit 22d Abnormality degree specifying unit 22e Tendency specifying unit 23 Processing-side storage unit 23a State DB 23b Abnormality degree DB 23c Tendency DB 100 Monitoring system

Claims

1. A monitoring system for monitoring a monitoring target within a monitoring environment, comprising: an acquisition means for acquiring imaging image information indicating an imaging image of the monitoring target; a state specifying means for specifying the state of the monitoring target based on the angle and / or position of the part of the monitoring target in the imaging image of the imaging image information acquired by the acquisition means; a providing means for providing state information indicating the state of the monitoring target specified by the state specifying means; A monitoring system comprising the above.

2. The monitoring target includes a patient and / or a care recipient, the angle of the part of the monitoring target includes the angle of the upper body of the monitoring target and the angle of the neck of the monitoring target, the position of the part of the monitoring target includes the position of the knee of the monitoring target and the position below the knee of the monitoring target, The monitoring system according to Claim 1.

3. The state specifying means determines whether the monitoring target in the imaging image of the imaging image information is covered by a hanging object, and specifies the state of the monitoring target with reference to the result of the determination. The monitoring system according to Claim 2.

4. The acquisition means acquires past imaging image information indicating a past imaging image and past state information corresponding to the past imaging image information, the past state information indicating the state of the monitoring target in the past imaging image, the state specifying means performs machine learning based on the past imaging image information and the past state information acquired by the acquisition means, and specifies the state of the monitoring target with reference to the result of the machine learning. The monitoring system according to any one of Claims 1 to 3.

5. An abnormality degree specifying means for specifying an abnormality degree indicating the degree of possibility that an abnormality related to the state of the monitoring target occurs based on the state of the monitoring target specified by the state specifying means is provided, the providing means provides abnormality degree information indicating the abnormality degree specified by the abnormality degree specifying means together with the state information. The monitoring system according to any one of Claims 1 to 3.

6. A tendency specifying means for specifying the tendency of the state of the monitoring target based on a plurality of the state information having different time series is provided, the providing means provides tendency information indicating the tendency of the state of the monitoring target specified by the tendency specifying means. The monitoring system according to any one of Claims 1 to 3.

7. A monitoring program for causing a monitoring system for monitoring a monitoring target within a monitoring environment to execute, causing a computer to an acquisition means for acquiring imaging image information indicating an imaging image obtained by imaging the monitoring target; a state specifying means for specifying a state of the monitoring target based on an angle or / and a position of a part of the monitoring target in the imaging image of the imaging image information acquired by the acquisition means; a providing means for providing state information indicating the state of the monitoring target specified by the state specifying means; A monitoring program for functioning as.

Images