Method for supporting creation of service menu, program for causing a computer to execute said method, and information providing device

Abstract

To provide information that is suppressed from varying with users of service.SOLUTION: A system 10 comprises: a block 11 which receives input of resident basic information; a watch system 100 which acquires, for each of residents ("care receivers") including a new resident of nursing facilities, information representing an ordinary ADL state and activity of the resident based upon outputs of various sensors provided in each living room; a block 12 which outputs automatic determination results of the ordinary ADL state and activity based upon an output of the watch system 100; a block 13 which holds up-to-now ADL states of the resident and transition thereof, menus of rehabilitation, etc., in the form of a database; a block 14 which determines a nursing care level of the new resident, and creates a care plan to create a menu of rehabilitation; and a block 15 which outputs an execution result of assessment by the block 14.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to providing information, and more particularly to techniques for deriving information provided to users of a service. [Background technology]

[0002] When providing rehabilitation menus or care services to care recipients or new residents of care facilities, it is desirable to provide information tailored to the care recipient or resident.

[0003] Regarding the provision of information, for example, Japanese Patent Application Laid-Open No. 2019-57283 (Patent Document 1) discloses a technology that "displays only information necessary for dental, medical, or care workers, or patients / families who operate a terminal, according to their attributes, in order to contribute to preventive medical care and nursing care prevention" (see [Abstract]). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2019-57283 Summary of the Invention [Problem to be solved by the invention]

[0005] If information tailored to a care recipient or resident is presented based on the judgment of, for example, caregivers, medical professionals, or other related parties, the information may vary. Therefore, there is a need for technology that ensures that information is consistent depending on the related parties.

[0006] The present disclosure has been made in view of the above-described background, and according to a certain aspect, a technique is disclosed that suppresses variations in information provided to users of a service. [Means for solving the problem]

[0007] According to one embodiment, a computer-implemented method for assisting in the creation of a menu of one or more services is provided, the method including the steps of accessing attribute information associated with a new user of a service, accessing observation data obtained by observing the user's activities of daily living, accessing observation data obtained about other users of one or more services, attribute information of the previous users, and menus of services created for the other users, selecting a menu of services created for the other users based on the attribute information and observation data of the other users that match the attribute information and observation data of the new user, and outputting the selected menu as a candidate menu of services for the new user.

[0008] In one aspect, the attribute information includes the new user's desires and goals. Creating the menu includes selecting, from one or more services, a service associated with the new user's desires and goals.

[0009] In one aspect, the attribute information includes the new user's family's aspirations and goals. Creating the menu includes selecting, from one or more services, a service associated with the family's aspirations and goals.

[0010] In one aspect, the step of outputting the selected menu includes displaying the selected menu on a computer monitor, and the method further includes associating the displayed menu with a time period based on an input to the computer.

[0011] In one aspect, the menu of services includes either items that make up a care plan or a rehabilitation menu.

[0012] According to another embodiment, a computer-implemented method for assisting a user in evaluating one or more services is provided. The method includes the steps of acquiring attribute information of a service user, accessing observation data acquired by observing the user's activities of daily living, and accessing a database having a plurality of pre-prepared evaluation comments. Each evaluation comment is associated with a pre-categorized combination of attribute information and observation data. The method further includes the steps of searching the database for evaluation comments associated with the combination of attribute information and observation data based on the user's attribute information and observation data, and outputting the retrieved evaluation comments as the user's evaluation result.

[0013] In one aspect, the attribute information includes aspirations and goals of the new user. The aspirations and goals are associated with each of the plurality of evaluation comments. The searching step includes searching for evaluation comments associated with the aspirations and goals.

[0014] In one aspect, the attribute information includes aspirations and goals of the new user's family. Each of the plurality of evaluation comments is associated with the family's aspirations and goals. The searching step includes searching for evaluation comments associated with the aspirations and goals.

[0015] In one aspect, the method further includes a step of determining the level of care required of the user based on predetermined criteria for determining the level of care required, the user's attribute information and observation data, and a step of outputting the determined level of care required.

[0016] According to another embodiment, there is provided a program for causing a computer to execute any of the methods described above.

[0017] According to yet another embodiment, there is provided an information providing device comprising a memory storing the above program and a processor that executes the program. [Effects of the Invention]

[0018] According to an embodiment, the variation in information (eg, care plans, rehabilitation menus) provided to service users is reduced.

[0019] The above and other objects, features, aspects and advantages of the present invention will become apparent from the following detailed description of the invention taken in conjunction with the accompanying drawings. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a diagram showing an overview of a system 10 that realizes a technical concept according to an embodiment. [Figure 2] FIG. 1 is a diagram illustrating an example of a configuration of a monitoring system 100 according to an embodiment. [Figure 3] 1 is a block diagram showing an outline of the configuration of a monitoring system 100. FIG. [Figure 4] FIG. 1 is a diagram showing an outline of a monitoring system 100 using a sensor box 119. [Figure 5] FIG. 4 is a block diagram showing the hardware configuration of a computer system 400. [Figure 6] FIG. 2 is a diagram showing one mode of storing attribute information on a hard disk 5. [Figure 7] FIG. 2 is a diagram showing an example of an ADL stored on a hard disk 5 according to an embodiment. [Figure 8] FIG. 1 is a diagram illustrating an example of a basic module used to create a care plan. [Figure 9] 10 is a flowchart illustrating a part of a process executed by a CPU 1 of a management server 200 to derive a basic module according to an embodiment. [Figure 10] FIG. 2 is a diagram showing an example of service items displayed on a monitor 8 connected to a management server 200 according to an embodiment. [Figure 11]FIG. 1 illustrates an example of a care plan generated in accordance with an embodiment. [Figure 12] FIG. 10 is a diagram showing the evaluation results displayed on the monitor 8 for a specified user. [Figure 13] FIG. 1 illustrates criteria for generating rehabilitation recommendations according to one embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0021] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In the following description, the same components are denoted by the same reference numerals. The names and functions of the components are also the same. Therefore, detailed description thereof will not be repeated.

[0022] The technical concept disclosed in this specification will be described with reference to Fig. 1. Fig. 1 is a diagram showing an overview of a system 10 that realizes the technical concept according to an embodiment. The system 10 includes blocks 11, 12, 13, 14, and 15 and a monitoring system 100.

[0023] Block 11 receives input of basic information about a resident. Block 11 is realized by an input device of a computer system, etc. The basic information about a resident is input to monitoring system 100.

[0024] The monitoring system 100 acquires information representing the usual ADL status and activity level of each resident (also referred to as a "care recipient"), including new residents of the nursing facility, based on the output from various sensors installed in each room. The monitoring system 100 outputs the acquired information to block 12. The monitoring system 100 will be described in detail later.

[0025] Block 12 outputs the results of automatic assessment of the usual ADL status and activity level based on the output of monitoring system 100. Block 12 is realized as a storage device and monitor of a computer system. In a certain aspect, the ADL status is determined based on the Barthel Index or ICF (International Classification of Functioning, Disability and Health) staging. ICF staging is an assessment method that evaluates the resident's usual activities and was created from the perspective of supporting independence. Note that ICF staging is well known to those skilled in the art. Therefore, a detailed description of ICF staging will not be repeated.

[0026] In other situations, if the person being cared for is not residing in a facility, for example, if they are receiving home care or using a day care service, the person being cared for can temporarily stay in the facility, for example, as a short stay, and sleep and wake up in a room equipped with a sensor box 119, thereby making it possible to obtain information on the person's ADL status, etc.

[0027] Block 13 stores the resident's ADL status and progress, rehabilitation menu, etc. Block 13 is realized as a database constructed on the hard disk or other storage device of a computer system.

[0028] Block 14 performs an assessment of a new resident. More specifically, block 14 determines the level of care required for the new resident, creates a care plan, and creates a rehabilitation menu. Block 14 is realized by a processor of a computer system.

[0029] Block 15 outputs the results of the assessment performed by block 14. Block 15 may be implemented by a monitor or storage device in the computer system.

[0030] <System Overview> Referring to Fig. 2, a monitoring system 100 capable of acquiring information related to ADL will be described. Fig. 2 is a diagram showing an example of the configuration of the monitoring system 100 according to an embodiment. An example of the monitoring target is the occupants of each room provided in the room area of ​​the facility 180. In the monitoring system 100 of Fig. 2, rooms 110 and 120 are provided in the room area. The room 110 is assigned to the resident 111. The room 120 is assigned to the resident 121.

[0031] The monitoring system 100 includes a gateway server 130, an exchange device 135, an access point 140, a management server 200, a sensor box 119, various devices that communicate with the sensor box 119, and mobile terminals 161, 162, 163, and 164.

[0032] The gateway server 130 connects the internal network (intranet) of the facility 180 to an external network 16 of the facility 180. The external network 16 is, for example, the Internet or a public telephone network. The external network 16 is also connected to a cloud server 150, a push server 160, and a wireless base station 195.

[0033] The switching device 135 connects each device in the internal network of the facility 180 to each other. In some aspects, a router or a switch may be used as the switching device 135. In the example shown in FIG. 2, the number of switching devices 135 is two, but the number is not limited to this. The internal network of the facility 180 may be configured by a combination of multiple switching devices 135.

[0034] The access point 140 is used to connect the mobile terminals 161 and 162 to the internal network of the facility 180. In one aspect, a Wi-Fi (Wireless Fidelity) router can be used as the access point 140.

[0035] The management server 200 receives event information from the sensor box 119 in the facility 180 and manages information about the residents of each room. The management server 200 also communicates with mobile terminals 161 and 162, manages staff who carry those mobile terminals, and sends various notifications to each mobile terminal. Note that the management server 200 may use an external push server 160 when sending notifications to the mobile terminals 161 and 162. Also, an external cloud server 150 may have some or all of the functions of the management server 200.

[0036] The sensor box 119 acquires information about the residents 111, 121 in the rooms 110, 120 by linking with the camera and sensors built into its housing and various other sensors in the rooms 110, 120. This information may include images showing each resident's gait, body temperature, pulse rate, and other vital signs. The sensor box 119 also transmits the acquired information about the residents 111, 121 to the management server 200 via the internal network. Details of the sensor box 119 will be described later.

[0037] The mobile terminals 161, 162 are used by caregivers and other staff members engaged in care at the facility 180. The staff members can use the mobile terminals 161, 162 to input care records, etc. The mobile terminals 161, 162 transmit the care records to the management server 200. Furthermore, if a problem occurs with the residents 111, 121, the staff members use the mobile terminals 161, 162 to receive a notification from the management server 200. The mobile terminals 161, 162 are connected to the access point 140 within the facility 180 and communicate with the management server 200 via the internal network. In the example of this specification, the caregivers 141, 142, 143, and 144 each have the mobile terminals 161, 162, 163, and 164.

[0038] From outside the facility 180, the mobile terminals 163, 164 can communicate with the management server 200 via the gateway server 130 via a wireless base station 195 or the like. When the mobile terminals 163, 164 communicate with the management server 200 from outside the facility 180, some of the services provided by the management server 200 to the mobile terminals 163, 164 may be restricted in order to protect the information of the residents.

[0039] The number of other devices such as the mobile terminals 161 and 162, the access point 140, and the exchange device 135 is not limited to the number exemplified in FIG.

[0040] Each of the rooms 110 and 120 includes furniture 112, a bed 113, and a toilet 114 as its facilities. Door sensors 118 are installed on the doors of the rooms 110 and 120, respectively, to detect whether the doors are open or closed. A toilet sensor 116 is installed on the door of the toilet 114, to detect whether the toilet 114 is open or closed. An odor sensor 117 is installed on the bed 113, to acquire excretion information of the resident 111. The resident 111 wears a vital sensor 290 that detects vital information of the resident 111. One example of the detected vital information is the resident's body temperature. Another example is the resident's breathing. Another example is the resident's heart rate. Yet another example is two or more of these types of information. In the room 110, the resident 111 can operate a care call handset 115. When the resident 111 operates the care call handset 115, the care call handset 115 transmits a call signal, which is received by the sensor box 119. The sensor box 119 transmits the received call signal to the management server 200. The management server 200 transmits a signal to the mobile terminal 220 notifying that a call from the resident 111 has been received.

[0041] The sensor box 119 has built-in sensors for detecting the behavior of objects in the rooms 110 and 120. One example of a sensor is a Doppler sensor for detecting the movement of an object. Another example is a camera. Still other examples are the care call handset 115, the door sensor 118, the toilet sensor 116, the odor sensor 117, or the vital sign sensor 290. The sensor box 119 may include at least one of these sensors.

[0042] The components of the monitoring system 100 will be described with reference to Fig. 3. Fig. 3 is a block diagram showing an outline of the configuration of the monitoring system 100.

[0043] [Sensor Box 119] The sensor box 119 includes a control device 101, a ROM (Read Only Memory) 102, a RAM (Random Access Memory) 103, a communication interface 104, a camera 105, a Doppler sensor 106, a wireless communication device 107, and a storage device 108.

[0044] The control device 101 controls the sensor box 119. The control device 101 is configured, for example, by at least one integrated circuit. The integrated circuit is configured, for example, by at least one CPU (Central Processing Unit), MPU (Micro Processing Unit) or other processor, at least one ASIC (Application Specific Integrated Circuit), at least one FPGA (Field Programmable Gate Array), or a combination thereof.

[0045] An antenna (not shown) and the like are connected to the communication interface 104. The sensor box 119 exchanges data with external communication devices via the antenna. The external communication devices include, for example, the management server 200, mobile terminals 161, 162, 163, 164 and other terminals, the access point 140, the cloud server 150, and other communication terminals.

[0046] In one implementation, the camera 105 is a near-infrared camera. The near-infrared camera includes an IR (Infrared) projector that projects near-infrared light. By using a near-infrared camera, images showing the interior of the rooms 110, 120 can be captured even at night. In another implementation, the camera 105 is a surveillance camera that receives only visible light. In still another implementation, the camera 105 may be a 3D sensor or a thermographic camera. The sensor box 119 and the camera 105 may be configured as an integrated unit or as a combination of separate devices.

[0047] The Doppler sensor 106 functions as a body movement sensor. The Doppler sensor 106 transmits and receives microwaves, ultrasound, and other radio waves to detect the behavior (movement) of objects (e.g., residents 111, care staff, etc.) in the rooms 110, 120. This allows the biological information of the residents 111, 121 in the rooms 110, 120 to be detected.

[0048] More specifically, the Doppler sensor 106 is connected to the control device 101 and, under the control of the control device 101, measures the movement of the chest surface of the resident 111 associated with breathing. The Doppler sensor 106 transmits microwaves or ultrasound waves (hereinafter also referred to as "transmitted waves"), receives microwaves or ultrasound waves reflected by an object (i.e., "reflected waves"), and outputs a Doppler signal of Doppler frequency components based on the transmitted waves and reflected waves. When an object is moving, the frequency of the reflected wave shifts in proportion to the object's moving speed due to the so-called Doppler effect. This results in a difference (Doppler frequency component) between the frequency of the transmitted wave and the frequency of the reflected wave. The Doppler sensor 106 generates a signal of this Doppler frequency component as a Doppler signal at a predetermined sampling rate and outputs the Doppler signal to the control device 101. When the control device 101 receives the Doppler signal from the Doppler sensor 106, it stores the received Doppler signal in chronological order in the storage device 108. When microwaves are used as transmission waves, the microwaves pass through clothing and are reflected by the body surface of resident 111. Therefore, even if resident 111 is wearing clothes, body surface movements can be detected.

[0049] In one example, each Doppler sensor 106 emits microwaves in the 24 GHz band toward the bed 113 in each room 110, 120, and receives waves reflected by the occupants 111, 121, etc. The reflected waves are Doppler shifted by the movements of the occupants 111, 121. The Doppler sensor 106 can detect the breathing state and heart rate of the occupants 111, 121 from the reflected waves.

[0050] The wireless communication device 107 receives signals from the care call handset 115, the door sensor 118, the toilet sensor 116, the odor sensor 117, and the vital sensor 290, and transmits the signals to the control device 101. The care call handset 115 includes a care call button 241. When the care call button 241 is operated, the care call handset 115 transmits a signal (e.g., a call signal) indicating that the operation has been performed. The transmitted signal is received by the wireless communication device 107. When the door sensor 118, the toilet sensor 116, the odor sensor 117, and the vital sensor 290 transmit their respective detection results, the transmitted signals are received by the wireless communication device 107.

[0051] The storage device 108 is, for example, a fixed storage device such as a flash memory or a hard disk, or a recording medium such as an external storage device. The storage device 108 stores programs executed by the control device 101 and various data used to execute the programs. The various data may include behavioral information of the residents 111, 121. Details of the behavioral information will be described later.

[0052] At least one of the above programs and data may be stored in a storage device other than storage device 108 (for example, a storage area of ​​control device 101 (for example, cache memory, etc.), ROM 102, RAM 103, external device (for example, management server 200 or mobile terminals 161, 162, 163, 164, etc.)) as long as the storage device is accessible by control device 101.

[0053] [Behavioral Information] Next, the behavior information in this embodiment will be described. The behavior information is, for example, information indicating that the resident 111, 121 has performed a predetermined behavior. In one example, the predetermined behavior includes four behaviors: "getting up" indicating that the resident 111, 121 has woken up, "getting out of bed" indicating that the resident 111, 121 has left the bed (bedding) 113, "falling" indicating that the resident 111, 121 has fallen off the bed (bedding) 113, and "falling down" indicating that the resident 111, 121 has collapsed.

[0054] Furthermore, the behavioral information may include actions that the resident performs to refuse to receive care, such as shaking off the caregiver with their hands, trying to kick the caregiver with their legs, clinging to the bed 113 and refusing to be changed, etc.

[0055] In one embodiment, the control device 101 generates behavioral information for each of the residents 111, 121 associated with each of the rooms 110, 120 based on images captured by the cameras 105 installed in each of the rooms 110, 120. For example, the control device 101 detects the heads of the residents 111, 121 from the images, and based on changes in the size of the detected heads of the residents 111, 121 over time, detects information such as "refusal of care" in addition to the usual information such as "getting up," "getting out of bed," "falling," and "falling down" of the residents 111, 121. A specific example of generating behavioral information will be described in more detail below.

[0056] First, the storage device 108 stores the location area of ​​each bed 113 in the living room 110, 120, a first threshold value Th1, a second threshold value Th2, and a third threshold value Th3. The first threshold value Th1 distinguishes the size of the resident's head between a lying position and a sitting position within the location area of ​​the bed 113. The second threshold value Th2 distinguishes whether the resident is in a standing position or not based on the size of the resident's head within the living room 110, 120 excluding the location area of ​​the bed 113. The third threshold value Th3 distinguishes whether the resident is in a lying position or not based on the size of the resident's head within the living room 110, 120 excluding the location area of ​​the bed 113.

[0057] The control device 101 extracts moving object regions from the target image as regions of the occupants 111, 121, for example, by background subtraction or frame subtraction. The control device 101 further extracts the head regions of the occupants 111, 121 from the extracted moving object regions by, for example, a circular or elliptical Hough transform, pattern matching using a pre-prepared head model, and using a threshold derived by a neural network trained for head detection. The control device 101 detects "getting up," "getting out of bed," "falling," and "falling down" from the position and size of the extracted head.

[0058] The control device 101 may determine that the action "getting up" has occurred when it detects that the position of the head extracted as described above is within the location area of ​​the bed 113 and that the size of the head extracted as described above has changed from the size of a lying position to the size of a sitting position by using the first threshold value Th1.

[0059] When the position of the head extracted as described above moves from within the area where the bed 113 is located to outside the area where the bed 113 is located, the control device 101 may apply a second threshold value Th2 to the size of the head extracted as described above, and when it detects that the head has changed from a certain size to the size of an upright position, determine that the action of "leaving bed" has occurred.

[0060] When the position of the head extracted as described above moves from within the area where the bed 113 is located to outside the area where the bed 113 is located, the control device 101 may apply a third threshold value Th3 to the size of the head extracted as described above, and when it detects that the head has changed from a certain size to the size of a recumbent position, determine that the behavior of "falling" has occurred.

[0061] The control device 101 may determine that the behavior of "falling" has occurred if it detects that the position of the head extracted as described above is located within the room 110, 120 excluding the area where the bed 113 is located, and that the size of the extracted head has changed from a certain size to the size of a lying position by using a third threshold value Th3.

[0062] Furthermore, the control device 101 detects the caregiver in addition to the resident from the image data and estimates the distance between the resident and the caregiver. If the control device estimates that the distance is shorter than a predetermined normal distance, it can determine that care refusal behavior is occurring. Furthermore, if the control device 101 determines that the resident's movements are abnormal, it can determine that the resident is exhibiting care refusal behavior toward the caregiver.

[0063] As described above, in one specific example, the control device 101 of the sensor box 119 generates behavioral information of each of the residents 111 and 121. Note that in the monitoring system 100 according to another aspect, an element other than the control device 101 (for example, the cloud server 150) may generate behavioral information of the residents 111 and 121 using images of the inside of the rooms 110 and 120.

[0064] [Mobile terminal 220] Mobile terminal 220 includes control device 221, ROM 222, RAM 223, communication interface 224, display 226, storage device 228, and input device 229. In one aspect, mobile terminals 161, 162, 163, and 164 are realized as, for example, smartphones, tablet terminals, wristwatch-type terminals, or other wearable devices.

[0065] The control device 221 controls the mobile terminals 161, 162, 163, and 164. The control device 221 is configured, for example, by at least one integrated circuit. The integrated circuit is configured, for example, by at least one CPU, at least one ASIC, at least one FPGA, or a combination thereof.

[0066] An antenna (not shown) and the like are connected to the communication interface 224. The mobile terminals 161, 162, 163, and 164 exchange data with external communication devices via the antenna and the access point 140. Examples of the external communication devices include the sensor box 119 and the management server 200.

[0067] Display 226 is realized by, for example, an organic EL (Electro Luminescence) display, a liquid crystal display, etc. Input device 229 is realized by, for example, a touch sensor provided on display 226. The touch sensor receives a touch operation on mobile terminals 161, 162, 163, and 164, and outputs a signal corresponding to the touch operation to control device 221.

[0068] The storage device 228 is realized by, for example, a flash memory, a hard disk or other fixed storage device, or a removable data recording medium.

[0069] In one aspect, the control device 101 distinguishes between going to bed, lying down, getting up, getting out of bed, falling, tipping over, and abnormal slight body movement, for example, as follows: The area in the target image where the bed 113 is located (the area where the bed 113 is located) is stored in advance in the ROM 102 as one of various data. Furthermore, each threshold value and the duration determination time are appropriately set from a plurality of samples, and are stored in advance in the ROM 102 as one of various data.

[0070] [Coming to bed] In determining whether to admit to bed, the control device 101 provisionally determines that the person has admitted to bed if the previous state variable (variable that stores the behavior determination result) was "leaving bed" and the person area extracted this time from the target image acquired from the camera 105, for example by background subtraction, completely overlaps the area where the bed 113 is located (if the person area is completely within the area where the bed 113 is located), and if the duration of this complete overlap state continues beyond the stay-in-bed continuation determination time, the control device 101 finally determines that the person has admitted to bed and detects admission to bed. The control device 101 updates the state variable to "stay-in-bed." The stay-in-bed continuation determination time is used as a threshold for finally determining that the person has admitted to bed, which was provisionally determined based on the complete overlap between the extracted person area and the area where the bed 113 is located, is admitted to bed.

[0071] [Lying down] "Lying in bed" refers to a state in which a resident (person to be monitored) is lying down in bed 113. For example, when the area occupied by the resident in the image is included in the area of ​​bed 113 and the amount of movement of the resident is equal to or less than a predetermined amount, control device 101 detects "lying in bed" as the behavior information of the resident.

[0072] [Wake up] In determining whether or not a person has woken up, the control device 101 provisionally determines that the person has woken up if the previous state variable was "lying down" and the area of ​​the person area extracted from the target image acquired from the camera 105 that currently extends beyond the area where the bed 113 is located is equal to or greater than the wake-up determination threshold and less than the bed-leaving determination threshold. The control device 101 finally determines that the person has woken up and detects the person having woken up if the duration of the area in which the area is equal to or greater than the wake-up determination threshold and less than the bed-leaving determination threshold exceeds the continued wake-up determination time. The control device 101 updates the state variable to "wake-up." The wake-up determination threshold is used to determine whether or not a person has woken up based on the size of the area. The bed-leaving determination threshold is used to determine whether or not a person has woken up based on the size of the area. The bed-leaving determination threshold is set to a value greater than the wake-up determination threshold. The continued wake-up determination time is used as a threshold for finally determining that a person has woken up, which was provisionally determined by comparing the area with the wake-up determination threshold.

[0073] [Getting out of bed] In determining whether or not a person has left bed, the control device 101 provisionally determines that the person has left bed if the previous state variable was either "in bed" or "wake up" and the area of ​​the person area extracted from the target image acquired this time from the camera 105 that extends beyond the area where the bed 113 is located is equal to or greater than the bed exit determination threshold. If the duration of time that the area remains equal to or greater than the bed exit determination threshold exceeds the continued bed exit determination time, the control device 101 finally determines that the person has left bed and detects the person having left bed. The control device 101 updates the state variable to "out of bed". The continued bed exit determination time is used as a threshold for finally determining that the person has left bed, which was provisionally determined by comparing the area with the bed exit determination threshold.

[0074] [Fall] In determining whether a fall has occurred, the control device 101 determines that a fall has occurred and detects a fall if the size of the head region of the person region extracted from the target image acquired this time from the camera 105 is equal to or smaller than the lying posture determination threshold, the rate of change in the size of the head region is equal to or greater than the fall determination speed threshold, and the person region is within a fall determination region set around the area where the bed 113 is located. The lying posture determination threshold is used to determine whether the size of the head region is in a lying posture. Whether the posture is lying or sitting is determined based on the size of the head region. The fall determination speed threshold is used to determine whether a fall has occurred based on the rate of change in the size of the head region.

[0075] [fall down] In determining whether a fall has occurred, the control device 101 determines that a fall has occurred and detects a fall if the size of the head area of ​​the person area extracted from the target image acquired this time from the camera 105 is equal to or smaller than the recumbent posture determination threshold, the speed of change in the size of the head area is equal to or greater than the fall determination speed threshold, and the person area is located in an area excluding the area where the bed 113 is located and the fall determination area. The fall determination speed threshold is used to determine whether or not a fall has occurred based on the speed of change in the size of the head area.

[0076] [Microbody abnormality] Micro-movement abnormalities are detected based on the Doppler signals output from the Doppler sensor 106. More specifically, the control device 101 performs, for example, a fast Fourier transform (FFT) on the Doppler signals measured within a predetermined time period from the time of measurement to the past, and calculates the average amplitude in a frequency band corresponding to the general breathing frequency from the spectrum obtained by the FFT. The control device 101 compares the calculated average with a threshold value for determining whether or not micro-movement abnormalities exist. If the calculated average value is equal to or less than the threshold value, the control device 101 provisionally determines that micro-movement abnormalities exist. If the duration of the state in which the average value is equal to or less than the threshold value exceeds a predetermined determination time, the control device 101 finally determines that micro-movement abnormalities exist, thereby detecting micro-movement abnormalities. The control device 101 updates the state variable with "micro-movement abnormality." The determination time is used as a threshold value for finally determining that micro-movement abnormalities provisionally determined by comparing the calculated average value with the micro-movement abnormality determination threshold are micro-movement abnormalities.

[0077] When the control device 101 detects the predetermined behavior from the behavior of the resident in this way, it transmits an event notification signal including event information indicating the content of the predetermined event related to the resident to the management server 200 via the communication interface 104. More specifically, the control device 101 transmits an event notification signal including the sensor ID of the sensor box 119, event information indicating the content of the event, and the target image used when detecting getting into bed, getting up, getting out of bed, falling, and tipping over to the management server 200 via the communication interface 104.

[0078] In one embodiment, the event information includes one or more of: going to bed, lying down, getting up, getting out of bed, falling, tipping over, abnormal slight body movement, and care call. Here, the control device 101 includes one or more of the detected going to bed, getting up, getting out of bed, falling, tipping over, and abnormal slight body movement as event information in the event notification signal. The image may include at least one of a still image and a video. In one embodiment, as described below, for example, a still image may first be transmitted from the sensor box 119 to the management server 200, and a video may be distributed in response to a request from a user (e.g., a caregiver, administrator, doctor, or other staff member). Note that in other aspects, the video may be distributed first. Alternatively, the still image and the video may be transmitted to the management server 200, and the mobile terminal 220 may display the still image or the video on the display 226 in a split-screen format based on a signal transmitted from the management server 200.

[0079] When the care call handset 115 receives a nurse call, the control device 101 transmits an event notification signal to the management server 200, including the event notification signal as another example of a predetermined event, and establishes a voice call with the mobile terminal 220 using a speaker (not shown) or the like. More specifically, when the care call button 241 is operated, a signal corresponding to the operation is received by the wireless communication device 107. The sensor box 119 generates an event notification signal including its sensor ID and a nurse call as event information, and transmits the event notification signal to the management server 200 via the communication interface 104. The control device 101 establishes a voice call, for example, by VoIP (Voice over Internet Protocol), between the microphone (not shown) and speaker (not shown) of the care call handset 115 and the mobile terminal 220 via the wireless communication device 107.

[0080] When the control device 101 receives a request for video distribution from an image display device such as the management server 200, the cloud server 150, or the mobile terminal 220 via the communication interface 104, it responds to the request by streaming video (e.g., live video) captured by the camera 105 and distributing the video to the image display device.

[0081] [Overview of monitoring] 4, a description will be given of monitoring using the monitoring system 100. FIG. 4 is a diagram showing an outline of the monitoring system 100 using a sensor box 119.

[0082] The monitoring system 100 is used to monitor occupants 111, 121 and other occupants who are the targets of monitoring (persons to be monitored). A sensor box 119 is attached to the ceiling of the room 110. Similar sensor boxes 119 are attached to the other rooms.

[0083] The range 31 represents the detection range of the sensor box 119. If the sensor box 119 has the aforementioned Doppler sensor, the Doppler sensor detects human behavior occurring within the range 31. If the sensor box 119 has a camera as a sensor, the camera captures images within the range 31.

[0084] The sensor box 119 is installed, for example, in a nursing home, a medical facility, a home, etc. In the example of Fig. 4, the sensor box 119 is attached to the ceiling and captures an image of the resident 111 and the bed 113 from the ceiling. The location where the sensor box 119 is attached is not limited to the ceiling, and it may be attached to a side wall of the room 110.

[0085] The monitoring system 100 detects danger to the resident 111 based on a series of images (i.e., video) obtained from the camera 105. As an example, detectable dangers include the resident 111 falling down, the resident 111 being in a dangerous location (such as a bed rail), and the like.

[0086] When the monitoring system 100 detects that the resident 111 is in danger, it notifies the caregivers 141, 142, etc. As an example of a notification method, the monitoring system 100 notifies the mobile terminals 161, 162 of the caregivers 141, 142 of the danger to the resident 111. When the mobile terminals 161, 162 receive the notification, they notify the caregivers 141, 142 of the danger to the resident 111 by a message, sound, vibration, etc. This allows the caregivers 141, 142 to immediately know that the resident 111 is in danger and to rush to the resident 111's aid quickly.

[0087] Furthermore, the watching system 100 can also notify the mobile terminals 163 and 164 of the caregivers 143 and 144 who are outside the facility of the danger via the wireless base station 195.

[0088] 4 shows an example in which the monitoring system 100 includes one sensor box 119, but in other aspects, the monitoring system 100 may include multiple sensor boxes 119. Also, while FIG. 4 shows an example in which the monitoring system 100 includes multiple mobile terminals 161, 162, in other aspects, the monitoring system 100 can also be realized with a single mobile terminal.

[0089] [Computer system configuration] The configuration of a computer system 400, which is one aspect of an information processing device, will be described with reference to Fig. 5. Fig. 5 is a block diagram showing the hardware configuration of the computer system 400. The computer system 400 functions as a gateway server 130, a cloud server 150, a push server 160, or a management server 200.

[0090] The computer system 400 mainly comprises the following components: a CPU 1 that executes programs; a mouse 2 and keyboard 3 that receive instructions input by the user of the computer system 400; a RAM 4 that volatilely stores data generated by the CPU 1 executing the programs or data input via the mouse 2 or keyboard 3; a hard disk 5 that nonvolatilely stores data; an optical disk drive 6; a communication interface (I / F) 7; and a monitor 8. The components are interconnected by a data bus. A CD-ROM 9 or other optical disk is inserted into the optical disk drive 6.

[0091] Processing in the computer system 400 is realized by software executed by each piece of hardware and the CPU 1. Such software may be pre-stored on the hard disk 5. Alternatively, the software may be stored on a CD-ROM 9 or other recording medium and distributed as a computer program. Alternatively, the software may be provided as a downloadable application program by an information provider connected to the Internet. Such software is read from the recording medium by an optical disk drive 6 or other reading device, or downloaded via the communication interface 7, and then temporarily stored on the hard disk 5. The software is read from the hard disk 5 by the CPU 1 and stored in the RAM 4 in the form of an executable program. The CPU 1 executes the program.

[0092] Each component constituting the computer system 400 shown in FIG. 5 is a general component. Therefore, one essential part of the technical idea of ​​the present disclosure can be said to be software stored in the RAM 4, hard disk 5, CD-ROM 9, or other recording medium, or software downloadable via a network. The recording medium may include a non-transitory computer-readable data recording medium. Note that the operation of each piece of hardware in the computer system 400 is well known, so detailed description will not be repeated.

[0093] The recording medium is not limited to a CD-ROM, a FD (Flexible Disk), or a hard disk, but may also be a medium that carries a program in a fixed manner, such as a magnetic tape, a cassette tape, an optical disk (MO (Magnetic Optical Disc) / MD (Mini Disc) / DVD (Digital Versatile Disc)), an IC (Integrated Circuit) card (including a memory card), an optical card, a mask ROM, an EPROM (Electronically Programmable Read-Only Memory), an EEPROM (Electronically Erasable Programmable Read-Only Memory), or a semiconductor memory such as a flash ROM.

[0094] The program referred to here includes not only a program that can be directly executed by a CPU, but also a source program, a compressed program, an encrypted program, and the like.

[0095] [Data Structure] The data structure of system 10 will be described with reference to Figs. 6 to 8. Fig. 6 is a diagram showing one mode of storage of attribute information on hard disk 5. The attribute information is information about residents (e.g., care recipients). This attribute information is used as reference data when assessing new residents. Hard disk 5 holds table 600 as a database. Table 600 includes areas 610, 620, 630, 640, 650, 660, and 670.

[0096] As shown in FIG. 6, area 610 stores information identifying each resident, such as the resident's name. Area 620 stores the resident's age. Area 630 stores the resident's gender. Area 640 stores the resident's medical history. The medical history may be reported by the resident's family when the resident enters the facility. If the resident receives a medical diagnosis after entering the facility, the medical history may be entered by a caregiver or other staff member at the facility based on the diagnosis.

[0097] Area 650 stores the hopes or motivations of the resident. The hopes or motivations are input based on the results of an interview conducted by a care manager or the like when the resident enters the facility.

[0098] Area 660 stores information indicating the degree of cognitive function assessed for the resident. In one aspect, the degree of cognitive function is assessed based on a test prepared in advance when the resident enters the facility. In another aspect, the degree of cognitive function may be the result of a test conducted again a predetermined period of time (e.g., six months, one year, etc.) after the resident enters the facility. The cognitive function test may be, for example, the Mini Mental State Examination (MMSE).

[0099] Area 670 stores the result of the ADL status determination. This determination result is derived, for example, from the movement speed acquired by the sensor box 119 of the monitoring system 100. In other aspects, the result of observation by a caregiver or the like may be used as the determination result.

[0100] 7 is a diagram showing an example of an ADL stored on the hard disk 5 according to an embodiment. The hard disk stores, as a database, a table 700 and a table 750. Table 700 includes areas 710, 720, 730, and 740. Table 750 includes areas 760, 770, and 780.

[0101] In table 700, field 710 stores information representing the resident's name. Field 720 stores indicators of activities of daily living. Field 730 stores specific measurement results of the activities of daily living. The measurement results are obtained by analyzing images acquired by sensor box 119 or by a caregiver measuring the movements of the care recipient. Field 740 stores the measurement date of the activities of daily living.

[0102] Each data record constituting table 700 is updated for each resident periodically or as needed. For example, when management server 200 derives values ​​for each resident's activities of daily living, the results are added to table 700. In another aspect, when a caregiver measures the activities of daily living of a care recipient, the measurement results are uploaded to management server 200, and table 700 adds a data record representing the measurement results.

[0103] In table 750, area 760 stores data pre-classified as attribute information. Attribute information includes age, gender, cognitive function, medical history, hopes / motivations, and ADL status. Area 770 stores the range of data that may be acquired by monitoring system 100 as observation data. This data is data actually obtained as data representing ADL activity levels. Area 780 stores evaluation comments prepared in advance to display the results of the assessment. In some aspects, the evaluation comments may be registered in advance by the manufacturer or user of system 100 as data specific to a combination of attributes and observation data.

[0104] For example, once the attributes (area 760) and observation data (area 770) of a new resident are identified, evaluation comments (area 780) about the resident can be determined, thereby making it easier for caregivers or family members of the new resident to understand the current status of the resident.

[0105] 8 is a diagram showing an example of a basic module used to create a care plan. Basic data is stored in advance on the hard disk 5. More specifically, the hard disk 5 includes areas 810, 820, 830, and 840 as a table 800. Areas 820 to 840 make up the basic module.

[0106] Area 810 holds a number that identifies the basic module. Area 820 stores the wishes of the care recipient or prospective resident. Area 830 stores the goals of the care recipient or prospective resident. The goals may include short-term goals or long-term goals. The goals may also include goals for the care recipient or prospective resident's family. Area 840 stores the contents of the service plan.

[0107] In one aspect, the care recipient, prospective resident, or their family members clarify their wishes (area 820) and goals (area 830), and the care manager or staff of the facility inputs the wishes and goals into the management server 200. The management server 200 searches for the entered wishes and goals and displays a service plan associated with the searched wishes and goals on the monitor 8. This service plan can be used as one module that constitutes the care plan for the care recipient or prospective resident. The care manager or staff can create a care plan by allocating the service plans displayed on the monitor 8 in this way as, for example, a weekly schedule.

[0108] [Control Structure] Therefore, the control structure of the management server 200 capable of deriving the basic modules that constitute the care plan will be described with reference to Fig. 9. Fig. 9 is a flowchart showing a part of the processing executed by the CPU 1 of the management server 200 to derive the basic modules according to an embodiment.

[0109] In step S910, the CPU 1 accesses the basic information (attribute information) of the person being evaluated stored on the hard disk 5, and reads each piece of data into the RAM 4. In step S915, the CPU 1 accesses a database that stores the values ​​(activity levels) of activities of daily living based on the detection results of the sensor box 119, and reads each piece of data into the RAM 4.

[0110] In step S920, the CPU 1 estimates the state of the person to be evaluated based on the basic information and the numerical value indicating the activity level of the activities of daily living. In step S925, the CPU 1 determines the level of care required based on the estimated state.

[0111] For example, in one aspect, the hard disk 5 of the management server 200 stores, as a database, survey results on the types of nursing care services (care) provided to a considerable number of elderly people (e.g., 3,000 or so people) and for how long. The survey results are associated with attribute information, ADL status, and other information for each elderly person. The CPU 1 extracts data on elderly people whose physical and mental conditions are most similar to those of the new resident to be assessed from the database. As an example, the CPU 1 uses the attribute information and ADL status information of the new resident as search keys to identify data on elderly people whose physical and mental conditions are most similar to those of the new resident. The CPU 1 estimates the reference time for nursing care certification, etc., from the data. More specifically, the CPU 1 calculates the reference time for nursing care certification, etc., for five categories (direct assistance for daily living, indirect assistance for daily living, BPSD (Behavioral and Psychological Symptoms of Dementia)-related activities, functional training-related activities, and medical-related activities). The CPU 1 determines whether the resident corresponds to Levels 1 to 5 of nursing care level, based on the reference time for nursing care certification, etc.

[0112] In step S930, the CPU 1 creates a care plan based on the requests, the estimated condition, and the basic data. In step S935, the CPU 1 displays the care plan on the monitor 8. For example, the monitor 8 presents a service plan (area 840) derived according to the ADL status, wishes, and goals of the care recipient as a candidate for the content of the care plan. At this point, it is not necessary to decide which service items will be provided and when. The days of the week and time periods when the service items will be provided can be determined by the care manager, caregiver, etc.

[0113] In step S940, the CPU 1 accepts input for editing the care plan. For example, a care manager, a caregiver, or other user can continue creating the care plan by arranging the service plan displayed on the monitor 8 for any time period for each day of the week.

[0114] In step S945, the CPU 1 detects an input to confirm the editing of the care plan. In response to the input of confirmation, in step S950, the CPU 1 saves the care plan.

[0115] In step S955, the CPU 1 creates a rehabilitation menu based on the desires, the estimated condition, and predetermined criteria. In step S960, the CPU 1 displays the rehabilitation menu on the monitor 8. In one aspect, the monitor 8 displays a recommended rehabilitation menu for each day of the week.

[0116] In step S965, the CPU 1 receives an input for editing the rehabilitation menu. For example, a care manager or a caregiver can change the day of the week and time period on which the rehabilitation menu is implemented to a desired day of the week and time period.

[0117] In step S970, the CPU 1 detects an input to confirm the editing of the rehabilitation menu. In step S975, the CPU 1 saves the rehabilitation menu in the hard disk 5.

[0118] When an appropriate care plan or rehabilitation menu for the care recipient is created through the above-described process, the care plan or rehabilitation menu is presented with reduced variations due to subjective opinions of the care manager or caregiver.

[0119] [Display example] An example of how a care plan is displayed will be described with reference to Figures 10 and 11. Figure 10 is a diagram illustrating an example of service items displayed on a monitor 8 connected to a management server 200 according to an embodiment. Figure 11 is a diagram illustrating an example of a care plan created according to an embodiment.

[0120] As shown in FIG. 10 , the management server 200 displays a table 1000 on the monitor 8. The table 1000 includes service plans (area 840) that make up the care plan. Each service plan is derived by the process shown in FIG. 9 . In one aspect, each service plan includes recommended items for each day of the week. For example, for Monday, the suggested service plans include wake-up assistance, bathing assistance, rehabilitation, social interaction, and bedtime assistance.

[0121] The service plans included in table 1000 are proposed for a designated care recipient or a person scheduled to enter a facility, and at the time they are proposed, the implementation date of each service plan is not specified. Therefore, the care manager or caregiver determines when each service plan will be implemented and creates a specific schedule. The schedule is created by the care manager or caregiver associating each service plan with a specific time period of the day by using a mouse, dragging on a touch panel, or other input operations.

[0122] As shown in FIG. 11 , when the service plans proposed as table 1000 are associated with the time periods selected by the care manager, caregiver, or the like, a care plan 1100 is displayed. The care plan 1100 indicates the time periods during which each service plan will be performed. In some aspects, the care manager, caregiver, or the like may input additional activity plans into the care plan 1100. In other aspects, the care plan 1100 may be shared by multiple caregivers with similar conditions.

[0123] As described above, according to this embodiment, when a care manager or caregiver inputs the attributes, wishes (area 820), and goals (area 830) of a resident, prospective resident, or other care recipient into the management server 200, the management server 200 proposes a service plan (area 840) as a module that constitutes a care plan. With this configuration, even if there is variation in the experience and subjectivity of the care manager or caregiver, it is possible to create a care plan that is appropriate for the care recipient.

[0124] Comments displayed according to users will be described with reference to Fig. 12. Fig. 12 is a diagram showing the evaluation results displayed on monitor 8 for a specified user.

[0125] Screen A displays an example of recommendations 1210 displayed regarding care. The recommendations 1210 include comments directed to the care recipient or their family. The recommendations 1210 are selected from a database of recommendations stored in advance on the hard disk 5 based on the ADL status of the care recipient. More specifically, each recommendation is associated with an ADL status. Therefore, by identifying the ADL status of the care recipient, the recommendation can also be identified.

[0126] Screen B displays a recommended rehabilitation menu 1220 (so-called recommendations) for the care recipient. This recommended menu 1220 includes suggestions for the care recipient or their family. The recommended menu 1220 is selected from a database of recommended menus pre-stored on the hard disk 5 based on the ADL status of the care recipient and the care recipient's wishes and goals. More specifically, each recommended menu is associated with the rate of change in the ADL status and the care recipient's wishes and goals, which have been prepared in advance. Therefore, once the rate of change in the ADL status of the care recipient, the wishes and goals are identified, the recommended menu can also be identified.

[0127] Another aspect of creating the recommendation menu 1220 (recommendations) will be described with reference to Figure 13. Figure 13 is a diagram illustrating criteria for generating rehabilitation recommendations according to one embodiment. The criteria are stored, for example, on hard disk 5 of management server 200. In one aspect, the criteria are defined as in table 1300.

[0128] Table 1300 includes four classes defined by two evaluation criteria. More specifically, table 1300 includes the evaluation criteria of the resident's condition and the degree of independence. The resident's condition includes maintenance / recovery and deterioration.

[0129] The management server 200 calculates the amount of indoor activity (activity time) from image data acquired by the monitoring system 100 as the resident's condition, and detects the condition of each resident based on the results of comparing the absolute value and fluctuation of the amount of indoor activity with a threshold value prepared in advance as an evaluation criterion. For example, if the amount of indoor activity of a certain resident is monotonically decreasing or is short (e.g., 10 minutes or less per day), the management server 200 determines that the resident's condition is in the "deterioration" phase. Otherwise, the management server 200 determines that the resident's condition is in the "maintenance / recovery" phase.

[0130] The management server 200 determines the degree of independence of a resident as "independent" and "not independent." Whether a resident is independent is determined, for example, based on whether the resident's basic behavior on the ICF corresponds to "5." In another aspect, the management server 200 may analyze images acquired by the monitoring system 100 to acquire information indicating the ADL status, and determine whether the resident is independent based on that information.

[0131] When the criteria in table 1300 are applied, management server 200 derives recommendations based on the table 750 stored in table 750. For example, management server 200 uses a combination of the resident's attributes and observation data as a search key to extract comments (area 780) associated with the search key. Management server 200 may display the extracted comments on monitor 8. If there are multiple combinations of attributes and observation data, management server 200 extracts comments using each combination as a search key.

[0132] For example, when a resident is in the "maintenance and recovery" phase and the class is "1" (independent), the management server 200 may output, as an example, a recommendation such as, "Promote active rehabilitation to enable the resident to move. Examples: walking training, muscle strengthening, etc." In another situation, when a resident is in the class "2" (not independent), the management server 200 may output, as an example, a recommendation such as, "Promote rehabilitation for the caregiver (to make care easier). For example, training to make assistance with excretion easier: range of motion training, maintaining an upright position, etc."

[0133] If a resident is in the "Deterioration" phase, the management server 200 outputs recommendations to manage the risk of rapid deterioration of the resident's condition, such as falls or aspiration pneumonia. In such cases, rehabilitation is implemented in consultation with the resident's doctor, nurse, or other medical professional.

[0134] For example, if a resident's class is "3," the management server 200 may output a recommendation such as, "Enhance monitoring to prevent falls and aspiration pneumonia." In another situation, if a resident's class is "4," the management server 200 may output a recommendation such as, "Maintain close contact with doctors and family members."

[0135] The detection of the ADL status of the resident is not limited to the detection based on predetermined criteria (so-called rule-based) as described above, but can also be realized using AI (Artificial Intelligence).

[0136] More specifically, when the detection is performed rule-based, the management server 200 may determine the ADL status based on the long-term average (e.g., monthly average) of the amount of daytime activity obtained from the image, or on a monotonically decreasing or increasing trend. If the management server 200 takes short-term fluctuations into account, it may be difficult to determine the ADL status. Therefore, in the rule-based determination, only the long-term average is used. In this case, the short-term fluctuations may include, for example, noise such as the inclusion of a caregiver's movements in the image to be detected, fluctuations due to the resident's illness, or other abnormalities.

[0137] In another aspect, the management server 200 may use AI to determine the ADL status. In this case, the management server 200 also pays attention to short-term fluctuations (e.g., several days to a week). Such fluctuations are assumed to be fluctuations in the ADL status of a resident who, for example, experiences a temporary decline in daytime activity due to poor health but subsequently recovers. The management server 200 may also combine walking speed and other indicators. In one aspect, the resident's condition evaluated by caregivers, administrators, and other facility staff is provided to the system used by the management server 200 as training data. The training data includes, for example, the resident's condition evaluated by the facility staff and observation data obtained by observing the resident using the monitoring system 100. The resident's condition includes data on three stages: recovery, maintenance, and deterioration. The observation data includes the amount of daytime activity, walking speed, and degree of unsteadiness.

[0138] As described above, the system 100 according to this embodiment can assess a new resident and output the results of the assessment. The results are not dependent on the subjective judgment of the facility staff. This reduces the variability in the assessment. Furthermore, even inexperienced staff can grasp the condition of a new resident.

[0139] Furthermore, the system 100 can propose a menu of care plans based on such assessments, so that a care plan suited to the care recipient can be created regardless of the experience of the care manager or caregiver.

[0140] The technical features disclosed above can be summarized as follows:

[0141] [Configuration 1] CPU1 accesses attribute information associated with a new user of a service. CPU1 accesses observation data obtained by observing the user's daily living activities. CPU1 accesses observation data obtained about other users of one or more services, attribute information of the previous users, and menus of services created for the other users. CPU1 selects a menu of services created for the other users based on the attribute information and observation data of the other users that match the attribute information and observation data of the new user. CPU1 outputs the selected menu as a candidate menu of services for the new user.

[0142] [Configuration 2] In one aspect, the attribute information includes the new user's desires and goals, and the CPU 1 selects a service associated with the new user's desires and goals from one or more services.

[0143] [Configuration 3] In one aspect, the attribute information includes the hopes and goals of the new user's family, and the CPU 1 selects a service associated with the hopes and goals of the family from one or more services.

[0144] [Configuration 4] In one aspect, the CPU 1 displays the selected menu on the monitor 8. The CPU 1 associates the displayed menu with a time period in which it will be performed, based on an input to a computer (e.g., the management server 200).

[0145] [Configuration 5] In one aspect, the menu of services includes either items that make up a care plan or a rehabilitation menu.

[0146] [Configuration 6] According to another embodiment, a computer-implemented method for assisting a user in evaluating one or more services is provided. More specifically, a CPU 1 acquires attribute information of a user of the service. The CPU 1 accesses observation data acquired by observing the user's daily living activities. The CPU 1 accesses a database having a plurality of pre-prepared evaluation comments. Each evaluation comment is associated with a pre-classified combination of attribute information and observation data. The CPU 1 searches the database for evaluation comments associated with the combination of attribute information and observation data based on the user's attribute information and observation data. The CPU 1 outputs the retrieved evaluation comments as the evaluation result of the user.

[0147] [Configuration 7] In one aspect, the attribute information includes the hopes and goals of the new user. Each of the multiple evaluation comments is associated with the hopes and goals. The CPU 1 searches for the evaluation comments associated with the hopes and goals.

[0148] [Configuration 8] In one aspect, the attribute information includes the hopes and goals of the new user's family. Each of the multiple evaluation comments is associated with the hopes and goals of the family. The CPU 1 searches for the evaluation comments associated with the hopes and goals.

[0149] [Configuration 9] In a certain situation, the CPU 1 determines the level of care required for a user based on predetermined criteria for determining the level of care required, the user's attribute information, and observation data. The CPU 1 outputs the determined level of care required. For example, the hard disk 5 of the management server 200 stores, as a database, survey results on what kind of care services (care) were provided and for how long for several thousand elderly people residing in facilities such as nursing homes for the elderly or long-term care medical facilities. The survey results are associated with information such as attribute information and ADL status for each elderly person. The CPU 1 extracts from the database data on elderly people whose physical and mental conditions are most similar to those of the new resident being assessed. More specifically, the CPU 1 uses the attribute information and ADL status information of the new resident as search keys to identify the data on elderly people whose physical and mental conditions are most similar to those of the new resident.

[0150] CPU1 estimates the standard time for nursing care certification, etc. from the data. More specifically, CPU1 calculates the standard time for nursing care certification, etc. for five categories (direct assistance for daily living, indirect assistance for daily living, BPSD-related activities, functional training-related activities, and medical-related activities). Based on the standard time for nursing care certification, etc., CPU1 determines whether the resident falls into one of the categories of support required 1 to nursing care required 5.

[0151] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the above description, and is intended to include all modifications within the meaning and scope of the claims. [Industrial Applicability]

[0152] The disclosed embodiments can be applied to computer systems used by businesses that create care plans. [Explanation of symbols]

[0153] 195 wireless base stations 16 External network, 31 Range, 101, 221 Control device, 105 Camera, 106 Doppler sensor, 107 Wireless communication device, 108, 228 Storage device, 110, 120 Room, 111, 121 Resident, 112 Furniture, 113 Bed, 114 Toilet, 115 Care call handset, 116 Toilet sensor, 117, ID sensor, 118 Door sensor, 119 Sensor box, 130 Gateway server, 135 Switching device, 140 Access point, 141, 142, 143, 144 Caregiver, 150 Cloud server, 160 Push server, 161, 162, 163, 164, 220 Mobile terminal, 180 Facility, 200 Management server, 226 Display, 229 Input device, 241 Care call button, 290 Vital sensors, 400 computer systems, 600,700,750,800,1000,1300 tables, 610,620,630,640,650,660,670,710,720,730,740,760,770,780,810,820,830,840 areas, 1100 care plans, 1210 recommendations, 1220 recommendation menus.

Claims

1. 1. A computer-implemented method for assisting in the development of a menu of one or more care services to be provided at a care facility, comprising: accessing attribute information associated with the new user of the care service; accessing observation data obtained by observing the user's activities of daily living in a room at the nursing home; accessing observation data acquired about the one or more other users of the care services, attribute information about the other users, and a menu of care services created for the other users; A step of selecting a menu of care services created for the other users based on the attribute information and observation data of the other users corresponding to the attribute information and observation data of the new user; and outputting the selected menu as a menu candidate for care services for the new user; the step of outputting the selected menu includes displaying the selected menu on a monitor of the computer, the selected menu being defined for each day of the week and for each time period; The method further includes associating the displayed menu with a time period based on an input to the computer.

2. The attribute information includes the new user's wishes and goals, The method of claim 1 , wherein the step of selecting a menu includes the step of selecting, from the one or more care services, a care service associated with the new user's desires and goals.

3. The attribute information includes the hopes and goals of the new user's family, The method according to claim 1 or 2, wherein the step of selecting a menu includes the step of selecting, from the one or more care services, a care service associated with the family's wishes and goals.

4. The method according to any one of claims 1 to 3, wherein the menu of care services includes either items constituting a care plan or a rehabilitation menu.

5. A program that causes a computer to execute the method according to any one of claims 1 to 4.

6. a memory storing the program according to claim 5; and a processor that executes the program.

Images