Target monitoring device, target monitoring method, program, and recording medium
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Filing Date
- 2024-05-01
- Publication Date
- 2026-03-19
AI Technical Summary
Existing fall detection devices can only detect falls after they occur and cannot prevent accidents, making continuous monitoring impractical for preventing injuries or deaths among vulnerable individuals such as patients in hospitals and nursing care facilities.
A target monitoring device and method that includes a status information acquisition unit, accident risk determination unit, and monitoring unit to automatically identify and monitor individuals at high risk of accidents, using acquired status information and warning standards to determine the necessity of monitoring and set them as targets for continuous surveillance.
Enables the automatic monitoring of individuals at high risk of accidents, potentially preventing falls and other incidents by identifying and tracking them in real-time, thereby enhancing safety in healthcare settings.
Abstract
Description
Object monitoring device, object monitoring method, program, and recording medium
[0001] The present disclosure relates to an object monitoring device, an object monitoring method, a program, and a recording medium.
[0002] In recent years, hospitals, nursing care facilities, and the like have been researching technologies for reducing the risk of falls among individuals under their care (e.g., patients, individuals requiring care). A specific example is a known fall detection device that can detect falls and the type of fall (see Patent Document 1). The fall detection device described in Patent Document 1 includes multiple fall detection units that detect multiple different types of falls in a subject, and a notification unit that, for each of the multiple fall detection units, notifies an external device of the detection of the type of fall when the fall detection unit detects the type of fall.
[0003] JP 2016-067641 A
[0004] Accidents such as falls can cause injury or even death to the subject when they occur, so it is desirable to prevent them before they occur. However, while the device described in Patent Document 1 can detect falls that have occurred, it has the problem that it cannot prevent accidents such as falls from occurring. On the other hand, it is not realistic to constantly monitor the subject in order to prevent accidents from occurring.
[0005] Therefore, an object of the present disclosure is to provide a target monitoring device, a target monitoring method, a program, and a recording medium that can automatically monitor targets at high risk of accidents.
[0006] In order to achieve the above-mentioned objective, the target monitoring device of the present disclosure includes a status information acquisition unit, an accident risk determination unit, a judgment unit, and a monitoring unit, wherein the status information acquisition unit acquires status information of a monitoring candidate, the accident risk determination unit determines the accident risk of the monitoring candidate based on the status information and alert standard information, the judgment unit determines whether or not the monitoring candidate needs to be monitored based on the accident risk, and the monitoring unit designates the monitoring candidate who is judged to need monitoring as a monitoring target.
[0007] The target monitoring method disclosed herein includes a status information acquisition process, an accident risk determination process, a judgment process, and a monitoring process, wherein the status information acquisition process acquires status information of a monitoring candidate, the accident risk determination process determines the accident risk of the monitoring candidate based on the status information and alert standard information, the judgment process determines whether or not the monitoring candidate needs to be monitored based on the accident risk, and the monitoring process designates the monitoring candidate who is determined to need monitoring as a monitoring target.
[0008] The program disclosed herein includes a status information acquisition procedure, an accident risk determination procedure, a judgment procedure, and a monitoring procedure, wherein the status information acquisition procedure acquires status information of a monitoring candidate, the accident risk determination procedure determines the accident risk of the monitoring candidate based on the status information and alert standard information, the judgment procedure determines whether or not the monitoring candidate needs to be monitored based on the accident risk, and the monitoring procedure designates a monitoring candidate who is judged to need monitoring as a person to be monitored.The program is for causing a computer to execute each of the above procedures.
[0009] The recording medium of the present disclosure includes a status information acquisition procedure, an accident risk determination procedure, a judgment procedure, and a monitoring procedure, wherein the status information acquisition procedure acquires status information of a monitoring candidate, the accident risk determination procedure determines the accident risk of the monitoring candidate based on the status information and alert standard information, the judgment procedure determines whether or not the monitoring candidate needs to be monitored based on the accident risk, and the monitoring procedure sets the monitoring candidate who is determined to need monitoring as a monitoring target, and is a computer-readable recording medium having recorded thereon a program for causing a computer to execute each of the above procedures.
[0010] According to the present disclosure, subjects at high risk of accidents can be automatically monitored.
[0011] Fig. 1 is a block diagram showing an example of the configuration of a target monitoring device of the present disclosure. Fig. 2 is a block diagram showing an example of the hardware configuration of a target monitoring device of the present disclosure. Fig. 3 is a flowchart showing an example of processing in the target monitoring device of the present disclosure. Fig. 4 is a block diagram showing an example of the configuration of a target monitoring device of the present disclosure. Fig. 5 is a flowchart showing an example of processing in the target monitoring device of the present disclosure.
[0012] Next, embodiments of the present disclosure will be described with reference to the drawings. The present disclosure is not limited to the following embodiments. In the following drawings, the same parts are denoted by the same reference numerals. Furthermore, the descriptions of the embodiments can be mutually incorporated unless otherwise specified, and the configurations of the embodiments can be combined unless otherwise specified.
[0013] [Embodiment 1] An object monitoring device of this embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing an example of the configuration of an object monitoring device 10 of this embodiment. As shown in Fig. 1, the object monitoring device 10 (hereinafter also referred to as "this device 10") includes a state information acquisition unit 11, an accident risk determination unit 12, a determination unit 13, and a monitoring unit 14. Although not shown, this device 10 may also include, for example, a storage unit.
[0014] The device 10 may be, for example, a single device including the above-mentioned components, or a device in which the components can be connected via a communication network. The device 10 can also be connected to an external device (described later) via the communication network. The communication network is not particularly limited, and any known network can be used, and may be wired or wireless. Examples of communication networks include the Internet, the World Wide Web (WWW), telephone lines, LANs (Local Area Networks), SANs (Storage Area Networks), DTNs (Delay Tolerant Networking), LPWAs (Low Power Wide Area Networks), and L5Gs (Local 5G). Examples of wireless networks include Wi-Fi (registered trademark), Bluetooth (registered trademark), local 5G, and LPWA. The wireless communication may be a form in which each device communicates directly (ad hoc communication), infrastructure communication, indirect communication via an access point, or the like. The device 10 may be incorporated into a server as a system, for example. The device 10 may also be a personal computer (e.g., desktop or laptop PC), a smartphone, a tablet terminal, or the like, on which the program of the present disclosure is installed. Furthermore, the device 10 may be in the form of cloud computing or edge computing, for example, in which at least one of the units is located on a server and the other units are located on a terminal.
[0015] 2 is a block diagram illustrating an example of the hardware configuration of the device 10. The device 10 includes, for example, a central processing unit (CPU, GPU, etc.) 101, a memory 102, a bus 103, a storage device 104, an input device 105, an output device 106, and a communication device 107. The components of the device 10 are connected to each other via the bus 103 and their respective interfaces (I / F).
[0016] The central processing unit 101 cooperates with other components via a controller (such as a system controller or an I / O controller) and is responsible for overall control of the device 10. In the device 10, the central processing unit 101 executes, for example, the program disclosed herein and other programs, and also reads and writes various types of information. Specifically, for example, the central processing unit 101 functions as a status information acquisition unit 11, an accident risk determination unit 12, a judgment unit 13, and a monitoring unit 14. The device 10 may include other computing devices such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or an APU (Accelerated Processing Unit), or may include a combination of these as a computing device.
[0017] The bus 103 can also be connected to, for example, external devices. Examples of the external devices include external storage devices (external databases, etc.), printers, external input devices, external display devices, audio output devices such as speakers, external imaging devices such as cameras, and various sensors such as acceleration sensors, geomagnetic sensors, and direction sensors. The device 10 can be connected to an external network (the communication line network) via, for example, a communication device 107 connected to the bus 103, and can also be connected to other devices such as a user terminal via the external network.
[0018] The memory 102 may be, for example, a main memory (primary storage device). When the central processing unit 101 performs processing, the memory 102 reads various operating programs, such as the program of the present disclosure, stored in the storage device 104 (described later), and the central processing unit 101 receives data from the memory 102 and executes the programs. The main memory may be, for example, a RAM (random access memory). Alternatively, the memory 102 may be, for example, a ROM (read only memory).
[0019] The storage device 104 is also referred to as an auxiliary storage device, in contrast to the main memory (primary storage device). As described above, the storage device 104 stores an operating program, including the program of the present disclosure. The storage device 104 may be, for example, a combination of a recording medium and a drive for reading and writing data from and to the recording medium. The recording medium is not particularly limited and may be, for example, an internal or external hard disk, a CD-ROM, a CD-R, a CD-RW, an MO, a DVD, a flash memory, a memory card, or the like. The storage device 104 may be, for example, a hard disk drive (HDD) or a solid-state drive (SSD) that integrates a recording medium and a drive. When the device 10 includes the storage unit, for example, the storage device 104 functions as the storage unit. The storage unit may store, for example, at least one selected from the group consisting of status information of a monitoring candidate, accident risk, side effect information, monitoring candidate identification information, detection information, and a detection threshold.
[0020] In the present device 10, the memory 102 and the storage device 104 can also store various information such as log information, information acquired from an external database (not shown) or an external device, information generated by the present device 10, and information used when the present device 10 executes processing. In this case, the memory 102 and the storage device 104 may store, for example, the above-mentioned information on the user of the present device. Note that at least a portion of the information may be stored, for example, in an external server other than the memory 102 and the storage device 104, or may be stored in a distributed manner across multiple terminals using blockchain technology or the like.
[0021] The apparatus 10 further includes, for example, an input device 105 and an output device 106. Examples of the input device 105 include pointing devices such as a touch panel, track pad, or mouse; a keyboard; imaging means such as a camera or scanner; card readers such as an IC card reader or a magnetic card reader; and audio input means such as a microphone. Examples of the output device 106 include display devices such as an LED display or a liquid crystal display; audio output devices such as a speaker; a printer; etc. In this embodiment, the input device 105 and the output device 106 are configured separately, but the input device 105 and the output device 106 may also be configured as an integrated device, such as a touch panel display.
[0022] Next, an example of the object monitoring method of this embodiment will be described based on the flowchart of Fig. 3. The object monitoring method of this embodiment can be implemented as follows, for example, using the object monitoring device 10 shown in Fig. 1 or Fig. 2. Note that the object monitoring method of this embodiment is not limited to use of the object monitoring device 10 of Fig. 1 or Fig. 2. Fig. 3 is a flowchart showing an example of processing by the object monitoring device 10.
[0023] First, the status information acquisition unit 11 acquires status information of the monitoring candidate (S1, status information acquisition step). The monitoring candidate is, for example, a person who is a candidate to be monitored by the device 10 to prevent accidents. It is known that people receiving medication are prone to falls due to the effects (side effects) of the medication. For this reason, the monitoring candidate may be, for example, a medication recipient. Note that the monitoring candidate of the present disclosure is not limited to a medication recipient. The medication recipient may be, for example, a patient at a medical institution, a resident of a nursing home, or someone receiving medication under the supervision of a supervisor (doctor, nurse, caregiver), but is not limited thereto. For example, the monitoring candidate may be someone taking over-the-counter medication or a person taking prescription medication. The status information is information for determining the accident risk of the monitoring candidate, and may include, for example, medication history, whether or not the person consumes alcohol, and dementia status. The medication history information includes, for example, the duration of medication administration to the monitoring candidate and information on the medication administered. The status information acquisition unit 11 may also acquire identification information of the monitoring candidate by linking it to the status information, for example. The identification information is not particularly limited as long as it can identify an individual, and examples thereof include name, nickname, address, telephone number, email address, patient registration card number, health insurance card number, My Number, ID, password, IP address, MAC address, and device-specific information of the terminal (such as a terminal serial number or an identification number such as an International Mobile Equipment Identifier). The status information acquisition unit 11 may acquire the status information by, for example, accepting input to the input device 105 of the device 10, or may acquire the status information from outside the device 10. In the latter case, the status information acquisition unit 11 may acquire the status information by, for example, accessing a hospital database or the like and referring to an electronic medical record or the like. The status information acquisition unit 11 may store the acquired status information in the memory 102 or the storage device 104, for example.
[0024] Next, the accident risk determination unit 12 determines the accident risk of the monitoring candidate based on the condition information and the alert standard information (S2, accident risk determination step). The condition information may be, for example, the medication history information described above. The alert standard information is information that serves as a standard for determining the accident risk, and is information in which the type of condition information is linked to an accident alert level. The alert standard information may also be, for example, linked to an alert time. The alert time is, for example, information on the time at which the linked accident alert level is set. A specific example of the alert standard information is, for example, side effect information. The side effect information is, for example, information in which drug information such as the type of drug and drug interactions is linked to side effect information such as the presence or absence, type, and time of side effect occurrence, and an accident alert level for each side effect. The accident alert level may be, for example, information on whether or not alert is required (alert required: 1, alert not required: 0), or information indicating the level of alert in stages (e.g., alert level 1, 2, 3, ... n (n is an integer greater than or equal to 1)). When the condition information includes whether or not the patient has drunk alcohol, the alert standard information includes, for example, information linking information such as whether or not the patient has drunk alcohol and the amount of alcohol consumed with the accident alert level. When the condition information includes information on the state of dementia, the alert standard information includes, for example, information linking the state of dementia with the accident alert level. The accident risk determination unit 12 can determine the accident risk of the monitoring candidate based on, for example, the medication history information and side effect information. Specifically, the accident risk determination unit 12 references, for example, the type of medication administered to the monitoring candidate and the time of administration of the medication from the medication history information of the monitoring candidate. Next, the accident risk determination unit 12 references the side effect information to extract the presence or absence of side effects and the type of side effect for the medication and drug combination administered to the monitoring candidate. Then, the accident risk determination unit 12 can determine, for example, the accident alert level linked to the side effect as the accident risk of the monitoring candidate for the period from the administration time to the side effect occurrence time. The alert standard information may be stored, for example, in the storage unit of the device 10 or in an external database.In the latter case, the accident risk determination unit 12 can refer to the alert standard information by, for example, accessing the external database via a communication network. The accident risk determination unit 12 may, for example, store the determined accident risk of the monitoring candidate in the memory 102 or the storage device 104.
[0025] Next, the determination unit 13 determines whether or not monitoring of the monitoring candidate is necessary based on the accident risk (S3, determination step). For example, the determination unit 13 may determine that monitoring is necessary for a monitoring candidate whose accident risk (accident alert level) is alert required (1), or may determine that monitoring is necessary for a monitoring candidate whose accident risk level is equal to or greater than a predetermined value. Furthermore, if an alert time is associated with the alert standard information, the determination unit 13 may determine that monitoring of the monitoring candidate is necessary during the alert time associated with the accident alert level. Furthermore, the determination unit 13 may, for example, refer to a monitoring candidate list in which monitoring candidate identification information, detection information for the monitoring candidate, and a detection threshold for the monitoring candidate are associated, and determine whether or not monitoring of the monitoring candidate is necessary based on the accident risk and the detection threshold. In this case, the determination unit 13, for example, refers to the monitoring candidate list, and compares the detection threshold associated with the corresponding monitoring candidate identification information for each monitoring candidate with the accident risk of the monitoring candidate, and can determine that a monitoring candidate whose accident risk exceeds the detection threshold is a monitoring target. The monitoring candidate identification information is not particularly limited as long as it can identify an individual, and examples thereof include name, nickname, address, telephone number, email address, patient registration card number, health insurance card number, My Number, ID, password, IP address, MAC address, and device-specific information of the terminal (such as the terminal's serial number and an identification number such as an International Mobile Equipment Identifier). The detection information is, for example, information used by the monitoring unit 14 described below to detect monitoring candidates. Specific examples of the detection information include images of the monitoring target (such as a facial image or a full-body image), features of the facial image, and the like. The detection threshold is, for example, a threshold for determining whether or not monitoring of the monitoring candidate is necessary, and information corresponding to the accident alert level can be set. In the monitoring candidate list, the detection threshold may be, for example, the same threshold or different thresholds for each monitoring candidate. In the latter case, the threshold may be set according to the attributes of the monitoring candidate.The attributes are not particularly limited, and examples thereof include information such as gender, age, disease status, whether or not the person is injured, whether or not the person has a disability, eyesight, and hearing ability.
[0026] The monitoring unit 14 then designates the monitoring candidate determined to require monitoring as a monitoring target (S4, monitoring step). The monitoring unit 14 may designate, for example, a monitoring candidate whose accident risk exceeds the detection threshold as a monitoring target. The device 10 may, for example, monitor the designated monitoring candidate, or may transmit information about the designated monitoring candidate to an external monitoring device (monitoring system) and have the external monitoring device monitor the designated monitoring target. When the device 10 monitors the designated monitoring target, the monitoring unit 14, for example, first acquires an image of the monitoring target area. The monitoring target area is not particularly limited and can be any area. Specific examples of the monitoring target area include medical facilities such as hospitals and nursing homes, public roads, etc. The monitoring unit 14 can acquire an image of the monitoring target area from a monitoring camera installed in the monitoring target area and / or a server device recording footage from the monitoring camera via a communication network. The image of the monitoring target area may be, for example, a still image or a video. The monitoring unit 14 can then, for example, detect the person to be monitored from an image of the area to be monitored based on the detection information of the monitoring candidate and monitor the detected person to be monitored. The method for detecting the person to be monitored from the image of the area to be monitored is not particularly limited, and for example, a known image processing method can be used. The image processing method is not particularly limited, and for example, face recognition processing can be used. In this case, the monitoring unit 14, for example, detects people and facial images from the image of the area to be monitored by object detection processing or the like, and performs face recognition processing on the detected facial images using the detection information (e.g., a facial image of the person to be monitored, feature information of the facial image of the person to be monitored). The monitoring unit 14 can then, for example, monitor and track the authenticated person to be monitored in the image of the area to be monitored.
[0027] The target monitoring device of this embodiment acquires status information of the monitoring candidate, determines the accident risk of the monitoring candidate based on the status information and alert standard information, determines whether or not the monitoring candidate needs to be monitored based on the accident risk, and can designate the monitoring candidate who is determined to need monitoring as the monitoring target.
[0028] Second Embodiment A second embodiment is another example of an object monitoring device according to the present disclosure.
[0029] FIG. 4 is a block diagram showing an example configuration of the object monitoring device 10A. As shown in FIG. 4, the object monitoring device 10A includes a risk determination unit 15 and a warning unit 16 in addition to the configuration of the object monitoring device 10 of embodiment 1. The hardware configuration of the object monitoring device 10A is the same as that of the object monitoring device 10 of FIG. 2, except that the central processing unit 101 includes the configuration of the object monitoring device 10A of FIG. 4 instead of the configuration of the object monitoring device 10 of FIG. 1. The processing of the risk determination unit 15 and the warning unit 16 will be described below. The processing of the risk determination unit 15 and the warning unit 16 can be inserted, for example, at any position in the flowchart of FIG. 3 described in embodiment 1, but is preferably inserted after S4, as shown in FIG. 5.
[0030] The risk determination unit 15 determines that the monitored person is in a dangerous state when the monitored person satisfies a warning condition (S11, risk determination process). The warning condition is not particularly limited, and examples thereof include entering a pre-designated dangerous area, wandering during a no-wandering time period, and the presence or absence of prohibited behavior. The dangerous area is not particularly limited, and can be set appropriately depending on the type and characteristics of the monitored area. The prohibited behavior is not particularly limited, and examples thereof include behavior that should be avoided in a state corresponding to the status information (e.g., administration of a predetermined drug), such as strenuous exercise or driving a vehicle. The risk determination unit 15 may, for example, set a warning threshold for the monitored person and determine that the monitored person is in a dangerous state when the monitored person's accident risk exceeds the warning threshold.
[0031] The warning unit 16 issues a warning when it is determined that the monitored person is in a dangerous state (S12, warning step). The warning unit 16 may, for example, issue a warning to an output device (e.g., a display, a speaker, etc.) 106 of the device 10A, or may issue a warning external to the device 10A. An example of the warning issued externally is an alert to a manager of the monitored area (e.g., a staff terminal of a hospital, a nursing home, etc.). The form of the warning is not particularly limited and may be audio, text, or an image. A specific example of the warning may be the output of an alert sound.
[0032] According to the target monitoring device of this embodiment, if the monitored person meets the warning conditions and / or if the monitored person's accident risk exceeds the warning threshold, it can determine that the monitored person is in a dangerous state and issue a warning.
[0033] [Third Embodiment] A third embodiment is an example of using the object monitoring device of the present disclosure.
[0034] In this embodiment, a patient in a hospital is used as an example of a monitoring candidate, but the present disclosure is not limited to the following example. Note that the term "monitoring" may be read as, for example, "watching over" or the like.
[0035] First, prior to processing by the target monitoring device (hereinafter also referred to as the present device) of the present disclosure, a database (monitoring candidate list) linking patient facial images, patient identification information, and patient detection thresholds is prepared. Also, a database (side effect database) is prepared in which side effect information linking the type of administered drug, its side effects, and the expected time of side effect occurrence is recorded as the alert standard information.
[0036] Next, a doctor or nurse administers medication (e.g., medications A, B, and C) to patient A. The doctor or nurse then inputs medication information (i.e., medications A, B, and C were administered to patient A at 1:00 PM on July 4th) into the status information acquisition unit of the device as patient status information. The device acquires the input status information (medication information), references the side effect database, and, based on the medication information, determines patient A's accident risk as "Caution Required" and determines whether patient A needs to be monitored. The device then accesses surveillance cameras in the hospital, which is the monitored area, and acquires images of the hospital interior. The device then references the monitoring candidate list, detects patient A from the acquired hospital images using facial recognition, and monitors and tracks patient A. If patient A meets the aforementioned warning conditions, it can alert the doctor or nurse.
[0037] [Embodiment 4] A program of this embodiment is a program for causing a computer to execute each step of the above-described object monitoring method. Specifically, the program of this embodiment is a program for causing a computer to execute a status information acquisition procedure, an accident risk determination procedure, a judgment procedure, and a monitoring procedure.
[0038] The status information acquisition procedure acquires status information of the monitoring candidate, the accident risk determination procedure determines the accident risk of the monitoring candidate based on the status information and warning standard information, the judgment procedure determines whether or not the monitoring candidate needs to be monitored based on the accident risk, and the monitoring procedure designates the monitoring candidate who is determined to need monitoring as a person to be monitored.
[0039] The program of this embodiment can also be said to be a program that causes a computer to function as a status information acquisition procedure, an accident risk determination procedure, a judgment procedure, and a monitoring procedure.
[0040] The program of this embodiment can be implemented by incorporating the descriptions of the target monitoring device and target monitoring method disclosed herein. For example, the term "procedure" in each of the steps can be replaced with "processing." The program of this embodiment may be recorded on a computer-readable recording medium, for example. The recording medium may be a non-transitory computer-readable storage medium. The recording medium is not particularly limited, and examples include random access memory (RAM), read-only memory (ROM), hard disk (HD), flash memory (e.g., solid state drive (SSD), USB flash memory, SD / SDHC card, etc.), optical disk (e.g., CD-R / CD-RW, DVD-R / DVD-RW, BD-R / BD-RE, etc.), magneto-optical disk (MO), floppy disk (FD), etc. The program of this embodiment (also referred to as a programming product or program product) may be distributed from an external computer, for example. The "distribution" may be, for example, distribution via a communication network or distribution via a device connected via a wire. The program of this embodiment may be installed and executed on the device to which it is distributed, or may be executed without being installed.
[0041] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.
[0042] This application claims priority based on Japanese Patent Application No. 2023-116954, filed on July 18, 2023, the disclosure of which is incorporated herein in its entirety by reference.
[0043] <Supplementary Notes> Some or all of the above embodiments may be described as in the following supplementary notes, but are not limited to the following. (Supplementary Note 1) An object monitoring device including a status information acquisition unit, an accident risk determination unit, a judgment unit, and a monitoring unit, wherein the status information acquisition unit acquires status information of a monitoring candidate, the accident risk determination unit determines an accident risk of the monitoring candidate based on the status information and alert standard information, the judgment unit judges whether or not monitoring of the monitoring candidate is necessary based on the accident risk, and the monitoring unit designates a monitoring candidate determined to require monitoring as a monitoring target. (Supplementary Note 2) The object monitoring device according to Supplementary Note 1, wherein the status information acquisition unit acquires medication history information of the monitoring candidate as the status information, and the accident risk determination unit determines the accident risk of the monitoring candidate based on the medication history information and side effect information. (Supplementary Note 3) The object monitoring device according to Supplementary Note 1 or 2, wherein the determination unit references a monitoring candidate list in which monitoring candidate identification information, detection information for the monitoring candidates, and detection thresholds for the monitoring candidates are linked, and determines whether or not monitoring of the monitoring candidates is necessary based on the accident risk and the detection threshold, and the monitoring unit designates the monitoring candidates whose accident risk exceeds the detection threshold as monitoring targets. (Supplementary Note 4) The object monitoring device according to Supplementary Note 3, wherein the monitoring unit acquires an image of the monitoring target area, detects the monitoring target person from the image of the monitoring target area based on the detection information for the monitoring candidates, and monitors the detected monitoring target person. (Supplementary Note 5) The object monitoring device according to any of Supplements 1 to 4, including a danger determination unit and a warning unit, wherein the danger determination unit determines that the monitoring target person is in a dangerous state when the monitoring target person satisfies a warning condition, and the warning unit issues a warning when it is determined that the monitoring target person is in a dangerous state. (Appendix 6) The target monitoring device described in Appendix 5, wherein the danger determination unit sets a warning threshold for the monitored person, and determines that the monitored person is in a dangerous state when the accident risk of the monitored person exceeds the warning threshold, and the warning unit issues a warning when it is determined that the monitored person is in a dangerous state.(Supplementary Note 7) A subject monitoring method comprising a status information acquisition step, an accident risk determination step, a judgment step, and a monitoring step, wherein the status information acquisition step acquires status information of a monitoring candidate, the accident risk determination step determines an accident risk of the monitoring candidate based on the status information and alert standard information, the judgment step judges whether or not monitoring of the monitoring candidate is necessary based on the accident risk, and the monitoring step designates a monitoring candidate determined to require monitoring as a monitoring target, and each of the steps is executed by a computer. (Supplementary Note 8) A subject monitoring method according to Supplementary Note 7, wherein the status information acquisition step acquires medication history information of the monitoring candidate as the status information, and the accident risk determination step determines the accident risk of the monitoring candidate based on the medication history information and side effect information. (Supplementary Note 9) The object monitoring method according to Supplementary Note 7 or 8, wherein the determination step refers to a monitoring candidate list in which monitoring candidate identification information, detection information for the monitoring candidates, and detection thresholds for the monitoring candidates are linked, and determines whether or not monitoring of the monitoring candidates is necessary based on the accident risk and the detection threshold, and the monitoring step designates a monitoring candidate whose accident risk exceeds the detection threshold as a monitoring target. (Supplementary Note 10) The object monitoring method according to Supplementary Note 9, wherein the monitoring step acquires an image of an area to be monitored, detects the monitoring target person from the image of the monitoring target area based on the detection information for the monitoring candidates, and monitors the detected monitoring target person. (Supplementary Note 11) The object monitoring method according to any of Supplements 7 to 10, including a danger determination step and a warning step, wherein the danger determination step determines that the monitoring target person is in a dangerous state when the monitoring target person satisfies a warning condition, and the warning step issues a warning when it is determined that the monitoring target person is in a dangerous state. (Appendix 12) The object monitoring method described in Appendix 11, wherein the danger determination process sets a warning threshold for the monitored person, and determines that the monitored person is in a dangerous state when the accident risk of the monitored person exceeds the warning threshold, and the warning process issues a warning when it is determined that the monitored person is in a dangerous state.(Supplementary Note 13) A subject monitoring program comprising a status information acquisition procedure, an accident risk determination procedure, a judgment procedure, and a monitoring procedure, wherein the status information acquisition procedure acquires status information of a monitoring candidate, the accident risk determination procedure determines an accident risk of the monitoring candidate based on the status information and alert standard information, the judgment procedure judges whether or not monitoring of the monitoring candidate is necessary based on the accident risk, and the monitoring procedure designates a monitoring candidate determined to require monitoring as a monitoring target, the program causing a computer to execute each of the procedures. (Supplementary Note 14) A subject monitoring program according to Supplementary Note 13, wherein the status information acquisition procedure acquires medication history information of the monitoring candidate as the status information, and the accident risk determination procedure determines the accident risk of the monitoring candidate based on the medication history information and side effect information. (Supplementary Note 15) The object monitoring program according to Supplementary Note 13 or 14, wherein the determination step refers to a monitoring candidate list in which monitoring candidate identification information, detection information for the monitoring candidate, and a detection threshold for the monitoring candidate are linked, and determines whether or not monitoring of the monitoring candidate is necessary based on the accident risk and the detection threshold, and the monitoring step designates a monitoring candidate whose accident risk exceeds the detection threshold as a monitoring target. (Supplementary Note 16) The object monitoring program according to Supplementary Note 15, wherein the monitoring step acquires an image of an area to be monitored, and detects the monitoring target from the image of the monitoring target area based on the detection information for the monitoring candidate, and monitors the detected monitoring target. (Supplementary Note 17) The object monitoring program according to any of Supplements 13 to 16, including a danger determination step and a warning step, wherein the danger determination step determines that the monitoring target is in a dangerous state if the monitoring target satisfies a warning condition, and the warning step issues a warning if the monitoring target is determined to be in a dangerous state. (Appendix 18) The target monitoring program described in Appendix 17, wherein the danger determination procedure sets a warning threshold for the monitored person, and determines that the monitored person is in a dangerous state when the accident risk of the monitored person exceeds the warning threshold, and the warning procedure issues a warning when it is determined that the monitored person is in a dangerous state.(Supplementary Note 19) A computer-readable recording medium having recorded thereon a target monitoring program for causing a computer to execute each of the above procedures, the target monitoring program including a status information acquisition procedure, an accident risk determination procedure, a judgment procedure, and a monitoring procedure, wherein the status information acquisition procedure acquires status information of a monitoring candidate, the accident risk determination procedure determines an accident risk of the monitoring candidate based on the status information and alert standard information, the judgment procedure judges whether or not monitoring of the monitoring candidate is necessary based on the accident risk, and the monitoring procedure designates a monitoring candidate determined to require monitoring as a monitoring target, and (Supplementary Note 20) The recording medium according to Supplementary Note 19, wherein the status information acquisition procedure acquires medication history information of the monitoring candidate as the status information, and the accident risk determination procedure determines the accident risk of the monitoring candidate based on the medication history information and side effect information. (Supplementary Note 21) The recording medium according to Supplementary Note 19 or 20, wherein the determination step refers to a monitoring candidate list in which monitoring candidate identification information, detection information for the monitoring candidate, and a detection threshold for the monitoring candidate are linked, and determines whether or not monitoring of the monitoring candidate is necessary based on the accident risk and the detection threshold, and the monitoring step designates a monitoring candidate whose accident risk exceeds the detection threshold as a monitoring target. (Supplementary Note 22) The recording medium according to Supplementary Note 21, wherein the monitoring step acquires an image of an area to be monitored, and detects the monitoring target from the image of the monitoring target area based on the detection information for the monitoring candidate, and monitors the detected monitoring target. (Supplementary Note 23) The recording medium according to any of Supplements 19 to 22, wherein the risk determination step determines that the monitoring target is in a dangerous state if the monitoring target satisfies a warning condition, and the warning step issues a warning if the monitoring target is determined to be in a dangerous state. (Appendix 24) The recording medium described in Appendix 23, wherein the danger judgment procedure sets a warning threshold for the monitored person, and when the accident risk of the monitored person exceeds the warning threshold, judges that the monitored person is in a dangerous state, and the warning procedure issues a warning when it is judged that the monitored person is in a dangerous state.
[0044] The subject monitoring device of the present disclosure can automatically monitor, for example, subjects at high risk of accidents. Therefore, the present disclosure can be used in various fields where accident prevention is important, such as the medical field and the nursing care field.
[0045] 10, 10A Target monitoring device 11 Status information acquisition unit 12 Accident risk determination unit 13 Determination unit 14 Monitoring unit 15 Danger determination unit 16 Warning unit 101 CPU 102 Memory 103 Bus 104 Storage device 105 Input device 106 Output device 107 Communication device
Claims
1. It includes a status information acquisition unit, an accident risk determination unit, a judgment unit, and a monitoring unit, The status information acquisition unit acquires status information of the monitoring candidate, The accident risk determination unit determines the accident risk of the monitoring candidate based on the status information and warning criteria information. The determination unit determines whether or not to monitor the candidate for monitoring based on the accident risk, The aforementioned monitoring unit is a target monitoring device that identifies monitoring candidates determined to require monitoring as monitoring targets.
2. The status information acquisition unit acquires the medication history information of the monitoring candidate as status information, The target monitoring device according to claim 1, wherein the accident risk determination unit determines the accident risk of the monitoring candidate based on the medication history information and the side effect information.
3. The determination unit, Referencing a list of monitoring candidates, which is linked to monitoring candidate identification information, monitoring candidate detection information, and monitoring candidate detection thresholds, Based on the accident risk and the detection threshold, the necessity of monitoring the candidate for monitoring is determined. The target monitoring device according to claim 1 or 2, wherein the monitoring unit designates monitoring candidates whose accident risk exceeds the detection threshold as the target of monitoring.
4. The aforementioned monitoring unit, Acquire images of the monitored area, The target monitoring device according to claim 3, which detects the person to be monitored from an image of the area to be monitored based on the detection information for the candidate to be monitored, and monitors the detected person to be monitored.
5. Including a danger determination unit and a warning unit, The danger determination unit determines that the monitored person is in a dangerous state if the monitored person meets the warning conditions. The warning unit issues a warning when it determines that the monitored person is in a dangerous situation. The target monitoring device according to claim 1 or 2.
6. The aforementioned risk determination unit, Set the warning threshold for the aforementioned monitored person, When the accident risk of the monitored person exceeds the warning threshold, it is determined that the monitored person is in a dangerous state. The target monitoring device according to claim 5, wherein the warning unit issues a warning when it is determined that the person being monitored is in a dangerous condition.
7. This includes a status information acquisition process, an accident risk determination process, a judgment process, and a monitoring process. The aforementioned status information acquisition step acquires status information of the monitoring candidate, The accident risk determination process determines the accident risk of the monitoring candidate based on the status information and warning criteria information. The determination step determines whether or not monitoring of the monitoring candidate is necessary based on the accident risk, The aforementioned monitoring process designates the monitoring candidates determined to require monitoring as the monitoring subjects. A target monitoring method in which each of the above steps is performed by a computer.
8. The state information acquisition step acquires the medication history information of the monitoring candidate as state information, The method for monitoring a target according to claim 7, wherein the accident risk determination step determines the accident risk of the monitoring candidate based on the medication history information and the side effect information.
9. This includes procedures for acquiring status information, determining accident risk, making a judgment, and monitoring. The aforementioned status information acquisition procedure acquires status information of the monitoring candidate, The accident risk determination procedure determines the accident risk of the monitoring candidate based on the status information and warning criteria information. The aforementioned determination procedure determines whether or not monitoring of the monitoring candidate is necessary based on the accident risk, The aforementioned monitoring procedure designates the monitoring candidates who have been determined to require monitoring as the monitoring subjects. A target monitoring program that causes a computer to execute each of the aforementioned procedures.
10. This includes procedures for acquiring status information, determining accident risk, making a judgment, and monitoring. The aforementioned status information acquisition procedure acquires status information of the monitoring candidate, The accident risk determination procedure determines the accident risk of the monitoring candidate based on the status information and warning criteria information. The aforementioned determination procedure determines whether or not monitoring of the monitoring candidate is necessary based on the accident risk, The aforementioned monitoring procedure designates the monitoring candidates who have been determined to require monitoring as the subjects of monitoring. A computer-readable recording medium containing a target monitoring program for causing a computer to execute each of the aforementioned procedures.