Information processing device, information processing system, information processing method, and program

Abstract

To appropriately carry out assessments of people who need support, care, etc. or who may need such support, care, etc. while reducing the required human resources. [Solution] The information processing device includes an acquisition unit that acquires sensing data obtained by continuously sensing the daily activities of one or more users, an extraction unit that refers to the sensing data and extracts one or more subjects from the one or more users, and a generation unit that generates assessment information regarding the one or more subjects.

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device, an information processing system, an information processing method, and a program. [Background technology]

[0002] There are known techniques for making various inferences related to support and care for people who need or may need support, care, etc. For example, Patent Document 1 discloses a technique for acquiring position data of a subject's body parts, including the toes, in chronological order, extracting feature values ​​based on the acquired position data, and inputting the feature values ​​into a learning model to infer whether the subject is frail or has mild cognitive impairment. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-92940 Summary of the Invention [Problem to be solved by the invention]

[0004] The condition of people who need or may need support or care, such as those described above, can change significantly over time and with changes in the environment. Therefore, in order to provide appropriate support and care to such people, it is preferable to carry out continuous monitoring and intervention before their condition worsens.

[0005] However, such continuous monitoring and intervention usually requires human resources for each monitoring or intervention. For example, in the technology described in Patent Document 1, in order to check the condition of the subject, it is necessary to guide the subject to an area where a camera is installed, have the subject walk in the area, and record the subject's movements.

[0006] The present disclosure has been made in consideration of the above-mentioned problems, and one exemplary purpose thereof is to provide technology that can appropriately assess people who need support, care, etc., or who may need such support, care, etc., while reducing the amount of human resources required. [Means for solving the problem]

[0007] An information processing device according to an exemplary aspect of the present disclosure includes an acquisition means for acquiring sensing data obtained by continuously sensing the daily activities of one or more users, an extraction means for extracting one or more subjects from the one or more users by referring to the sensing data, and a generation means for generating assessment information regarding the one or more subjects.

[0008] An information processing system according to an exemplary aspect of the present disclosure includes a sensing means for continuously sensing the daily activities of each of one or more users, an acquisition means for acquiring sensing data obtained by the sensing means, an extraction means for extracting one or more subjects from the one or more users by referring to the sensing data, and a generation means for generating assessment information regarding the one or more subjects.

[0009] An information processing method according to an exemplary aspect of the present disclosure includes one or more processors acquiring sensing data obtained by continuously sensing the daily activities of one or more users, extracting one or more subjects from the one or more users by referring to the sensing data, and generating assessment information regarding the one or more subjects.

[0010] A program according to an exemplary aspect of the present disclosure is a program that causes a computer to function as an information processing device, and causes the computer to function as an acquisition means that acquires sensing data obtained by continuously sensing the daily activities of one or more users, an extraction means that extracts one or more subjects from the one or more users by referring to the sensing data, and a generation means that generates assessment information regarding the one or more subjects. [Effects of the Invention]

[0011] According to an exemplary aspect of the present disclosure, it is possible to appropriately perform assessments of people who need support, care, etc., or who may need such support, care, etc., while reducing the amount of human resources required. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a block diagram illustrating a configuration of an information processing device according to the present disclosure. [Figure 2] FIG. 1 is a flow diagram showing the flow of an information processing method according to the present disclosure. [Figure 3] 1 is a block diagram illustrating a configuration of an information processing system according to the present disclosure. [Figure 4] 1 is a block diagram illustrating a configuration of an information processing system according to the present disclosure. [Figure 5] FIG. 1 is a diagram for explaining processing by an information processing system according to the present disclosure. [Figure 6] FIG. 1 is a diagram for explaining processing by an information processing system according to the present disclosure. [Figure 7] FIG. 1 is a diagram for explaining processing by an information processing system according to the present disclosure. [Figure 8] FIG. 1 is a diagram for explaining processing by an information processing system according to the present disclosure. [Figure 9] FIG. 1 is a block diagram illustrating a configuration of a computer that functions as an information processing device according to the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0013] The following are examples of embodiments of the present invention. However, the present invention is not limited to the exemplary embodiments shown below, and various modifications are possible within the scope of the claims. For example, embodiments obtained by appropriately combining the technologies (part or all of the products or methods) employed in the exemplary embodiments shown below may also be included in the scope of the present invention. Furthermore, embodiments obtained by appropriately omitting some of the technologies employed in the exemplary embodiments shown below may also be included in the scope of the present invention. Furthermore, the effects mentioned in the exemplary embodiments shown below are examples of effects expected in the exemplary embodiments, and do not define the scope of the present invention. In other words, embodiments that do not exhibit the effects mentioned in the exemplary embodiments shown below may also be included in the scope of the present invention.

[0014] First Exemplary Embodiment A first exemplary embodiment, which is an example of an embodiment of the present invention, will be described in detail with reference to the drawings. This exemplary embodiment is the basic form of each exemplary embodiment described later. The scope of application of each technology employed in this exemplary embodiment is not limited to this exemplary embodiment. That is, each technology employed in this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure, to the extent that no particular technical obstacles arise. Furthermore, each technology shown in the drawings referenced to explain this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure, to the extent that no particular technical obstacles arise.

[0015] (Configuration of information processing device) The configuration of an information processing device 1 according to this exemplary embodiment will be described with reference to FIG. 1. The information processing device 1 continuously senses the daily activities of users of services provided using the information processing device 1 and generates assessment information about the extracted subjects by referring to the sensing results. In the following description, a "user" refers to a user of a service provided using the information processing device 1 as described above. As an example, the "user" refers to people who need or may need support or care, but this does not limit this exemplary embodiment. Also, as an example, the "user" may be a person receiving care in a nursing home or care facility, but this does not limit this exemplary embodiment. As shown in FIG. 1, the information processing device 1 includes an acquisition unit 11, an extraction unit 12, and a generation unit 13.

[0016] (Acquisition part 11) The acquisition unit 11 acquires sensing data obtained by continuously sensing the daily activities of one or more users. Here, the daily activities of the users include, for example, movement such as walking, eating, changing clothes, excretion, bathing, grooming, etc., but these examples do not limit the present exemplary embodiment.

[0017] The sensing data may be, for example, data obtained by continuously sensing the user's daily activities using a wearable device worn by the user, but is not limited to this. The sensing data may include data obtained by continuously sensing at least one of the user's vital signs, activity level, posture, and walking characteristics (gait), but this does not limit the present exemplary embodiment. The sensing data may also include data acquired from an insole-type sensor that senses the user's walking characteristics (gait), but this does not limit the present exemplary embodiment. The sensing data may also include posture data or gait data captured by a camera included in a terminal device such as a smartphone.

[0018] (Extraction part 12) The extraction unit 12 extracts one or more subjects from the one or more users by referring to the sensing data acquired by the acquisition unit 11. While the specific extraction process by the extraction unit 12 does not limit this exemplary embodiment, for example, the extraction unit 12 may extract the subjects by applying predetermined extraction conditions to the sensing data, in other words, by determining whether the sensing data satisfies the predetermined extraction conditions. Alternatively, the extraction unit 12 may extract the subjects by applying a machine-learned extraction model to the sensing data, in other words, by inputting the sensing data into the machine-learned extraction model. Note that the term "subject" refers to, for example, the subject of assessment information described below. Alternatively, the "subject" may refer to a facility user who requires individual intervention for the purposes of nursing care or fall prevention. However, these examples do not limit this exemplary embodiment.

[0019] (Generation part 13) The generation unit 13 generates assessment information about the one or more subjects extracted by the extraction unit 12. As an example, the generation unit 13 generates the assessment information about the subject by referring to the sensing data about the subject. The specific configuration of the assessment information does not limit this exemplary embodiment, but as an example, the assessment information may be configured to include information indicating at least one of the subject's risk of falling and the degree of frailty. Furthermore, the assessment information may be configured to include information indicating the risk or degree of mild cognitive impairment (MCI).

[0020] The assessment information about the subject generated by the generation unit 13 is, for example, presented to the subject or a provider of a service to the subject. Here, the "provider of a service to the subject" is, for example, A business that provides a service using the information processing device 1 to the target person (or the user), Medical professionals (doctors, nurses, physical therapists, etc.) working at facilities that provide services using the information processing device 1 to the target persons (or the users), Caregivers (care workers, social workers, etc.) working at the above facilities, or Family members of the person in question These include, but are not limited to, the following. A "provider providing services to a subject" may be considered to be a provider that provides nursing care services, etc. to a subject. Furthermore, the term "service" may include the provision of support or care, whether paid or free. Therefore, the expression "a provider providing services to a subject" may also be expressed as "a person who supports or cares for a subject."

[0021] (Effects of information processing devices) As described above, the information processing device 1 is configured to acquire sensing data obtained by continuously sensing the daily activities of one or more users, refer to the sensing data to extract one or more subjects from the one or more users, and generate assessment information regarding the one or more subjects.

[0022] According to the above configuration, subjects are extracted by referring to sensing data obtained by continuously sensing the user's activities in their daily lives, and assessment information about the subjects is generated, thereby making it possible to appropriately assess people who require support, care, etc., or who may be in need of such support, care, etc., while minimizing the human resources required for involvement.

[0023] (Flow of information processing method) The flow of the information processing method S1 according to this exemplary embodiment will be described with reference to Fig. 2. Fig. 2 is a flow diagram showing the flow of the information processing method S1. As shown in Fig. 2, the information processing method S1 includes a process (process, step) S11 for acquiring sensing data, a process (process, step) S12 for extracting subjects, and a process (process, step) S13 for generating assessment information.

[0024] (Step S11) In step S11, the acquisition unit 11 acquires sensing data obtained by continuously sensing the daily activities of one or more users. The specific processing by the acquisition unit 11 has been described above, and therefore will not be described here.

[0025] (Step S12) In step S12, the extraction unit 12 extracts one or more target persons from the one or more users by referring to the sensing data acquired by the acquisition unit 11 in step S11. The specific processing by the extraction unit 12 has been described above, and therefore will not be described here.

[0026] (Step S13) In step S13, the generation unit 13 generates assessment information about the one or more subjects extracted by the extraction unit 12 in step S12. The specific processing by the generation unit 13 has been described above, and therefore will not be described here.

[0027] (Effects of information processing methods) As described above, the information processing method S1 employs a configuration in which sensing data is acquired by continuously sensing the daily activities of one or more users, the sensing data is referenced to extract one or more subjects from the one or more users, and assessment information regarding the one or more subjects is generated. The above configuration achieves the same effects as the information processing device 1.

[0028] (Configuration of information processing system) Next, the configuration of an information processing system 100 according to this exemplary embodiment will be described with reference to Fig. 3. As shown in Fig. 3, the information processing system 100 includes an acquisition unit 11, an extraction unit 12, a generation unit 13, and a sensing unit 14. Also, as shown in Fig. 3, the acquisition unit 11, the extraction unit 12, the generation unit 13, and the sensing unit 14 are configured to be able to communicate via a network N. Here, the specific configuration of the network N does not limit this exemplary embodiment, but as an example, a wireless LAN (Local Area Network), a wired LAN, a WAN (Wide Area Network), a public line network, a mobile data communication network, or a combination of these networks can be used.

[0029] (Acquisition unit 11, extraction unit 12, generation unit 13) The acquisition unit 11, extraction unit 12, and generation unit 13 included in the information processing system 100 are similar to the acquisition unit 11, extraction unit 12, and generation unit 13 included in the information processing device 1 described above, and therefore description thereof will be omitted here.

[0030] (Sensing unit 14) The sensing unit 14 continuously senses the daily activities of one or more users. The sensing unit 14 then supplies the sensing data obtained through the continuous sensing to the acquisition unit 11. For example, the sensing unit 14 may be configured as a wearable device worn by the user and continuously sense the daily activities of the user, but is not limited to this. For example, the sensing unit 14 may be configured to continuously sense at least one of the user's vital signs, activity level, posture, and gait characteristics, but this is not a limitation of the exemplary embodiment. For example, the sensing unit 14 may be an insole-type sensor that senses the user's gait characteristics, but this is not a limitation of the exemplary embodiment. The sensing unit 14 may also be a camera included in a terminal device such as a smartphone. The sensing unit 14 may be configured to provide posture data or gait data captured by the camera to the acquisition unit 11 as the sensing data.

[0031] (Effects of information processing systems) As described above, the information processing system 100 is configured to include a sensing unit 14 that continuously senses the daily activities of one or more users, an acquisition unit 11 that acquires sensing data obtained by the sensing unit 14, an extraction unit 12 that refers to the sensing data to extract one or more subjects from the one or more users, and a generation unit 13 that generates assessment information regarding the one or more subjects. The above configuration produces the same effects as the information processing device 1.

[0032] Second Exemplary Embodiment A second exemplary embodiment, which is one example of an embodiment of the present invention, will be described in detail with reference to the drawings. Components having the same functions as those described in the above exemplary embodiment will be assigned the same reference numerals, and their description will be omitted as appropriate. The scope of application of each technology employed in this exemplary embodiment is not limited to this exemplary embodiment. That is, each technology employed in this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure, to the extent that no particular technical hindrance occurs. Furthermore, each technology shown in each drawing referenced to explain this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure, to the extent that no particular technical hindrance occurs.

[0033] <Configuration of information processing system> The configuration of an information processing system 100A including an information processing device 1A according to this exemplary embodiment will be described with reference to Fig. 3. Fig. 3 is a block diagram showing the configuration of the information processing system 100A. As shown in Fig. 3, the information processing system 100A includes an information processing device 1A, one or more sensing devices 14, and one or more terminal devices 50. Here, as shown in Fig. 3, the information processing device 1A, the one or more sensing devices 14, and the one or more terminal devices 50 are configured to be able to communicate via a network N. Here, the specific configuration of the network N does not limit this exemplary embodiment, but as an example, a wireless local area network (LAN), a wired LAN, a wide area network (WAN), a public line network, a mobile data communication network, a short-range wireless communication, or a combination of these networks can be used.

[0034] When the information processing system 100A includes a plurality of sensing devices 14, each sensing device may be designated by a branch number such as 14-1, 14-2, etc., as shown in Fig. 3. Similarly, when the information processing system 100A includes a plurality of terminal devices 50, each terminal device may be designated by a branch number such as 50-1, 50-2, etc., as shown in Fig. 3.

[0035] (Sensing device 14) The sensing device 14 continuously senses the daily activities of a user of the information processing system 100A. The sensing device 14 then provides the information processing device 1A with sensing data obtained through the continuous sensing. For example, the sensing device 14 may be configured as a wearable device worn by the user and continuously sense the daily activities of the user, but is not limited to this. For example, the sensing device 14 may be configured to continuously sense at least one of the user's vital signs, activity level, posture, and gait characteristics, but this is not a limitation of this exemplary embodiment. For example, the sensing device 14 may be an insole-type sensor that senses the user's gait characteristics, but this is not a limitation of this exemplary embodiment. The sensing unit 14 may be a camera included in a terminal device such as a smartphone. For example, the sensing unit 14 may be configured as part of a terminal device 50. The sensing unit 14 may be configured to supply the posture data or gait data captured by the camera to the acquisition unit 11 as the sensing data.

[0036] In addition, when there are multiple users of the information processing system 100A, as an example, each user is individually provided with a sensing device 14. For example, a sensing device 14-1 is provided to a user U1, and a sensing device 14-2 is provided to a user U2.

[0037] Furthermore, when sensing device 14 is configured as a wearable device such as a wristband-type sensor or an insole-type sensor, sensing device 14 includes a battery that supplies power to the sensor. Sensing device 14 may also be configured with a power generation mechanism that generates power through the user's daily activities. For example, when sensing device 14 is configured as a wristband-type sensor, sensing device 14 may also be configured with a power generation mechanism that generates power through the movement of the user's arm. When sensing device 14 is configured as an insole-type sensor, sensing device 14 may also be configured with a power generation mechanism that generates power through the movement of the user's foot. Providing a power generation mechanism in sensing device 14 reduces the effort required for maintenance, such as charging, of sensing device 14, thereby enabling optimal and continuous sensing of the user's daily activities.

[0038] (Terminal device 50) The terminal device 50 includes a display unit 51 and displays assessment information generated by a generation unit 13 of the information processing device 1A (described later). When the information processing system 100A has multiple users, a terminal device 50 may be provided to each user individually. For example, a terminal device 50-1 may be provided to user U1 for use by that user U1, and a terminal device 50-2 may be provided to user U2 for use by that user U2. The terminal device 50 may also function as a relay device for supplying sensing data from the sensing device 14 to the information processing device 1A. For example, the terminal device 50-1 may receive sensing data from a sensing device 14-1 that continuously senses the daily activities of user U1 via short-range wireless communication, and the terminal device 50-1 may then supply the received sensing data to the information processing device 1A via a wireless LAN.

[0039] Furthermore, the one or more terminal devices 50 may include a terminal device used by a provider that provides a service to the user. Here, the "provider that provides a service to the user" may be, for example, a business that provides a service to the user using the information processing device 1A, a facility, an employee working at the facility, or a family member of the user, but is not limited to these. The "provider that provides a service to the user" may also be considered as a provider that provides nursing care services, etc. to the user. Furthermore, the term "service" may include the provision of support or care, whether paid or free of charge. Therefore, the expression "provider that provides a service to the user" may also be expressed as "someone who supports or cares for the user."

[0040] (Information processing device 1A) Next, the configuration of the information processing device 1A will be described. As shown in Fig. 3, the information processing device 1A includes a control unit 10A, a storage unit 20A, a communication unit 30, and an input / output unit 40.

[0041] (Communication unit 30) The communication unit 30 communicates with devices external to the information processing device 1A via the network N described above. The communication unit 30 transmits data supplied from the control unit 10A to other devices, and supplies data received from other devices to the control unit 10A. As an example, the communication unit 30 receives sensing data from the sensing device 14 and supplies the received sensing data to the control unit 10A or the storage unit 20A. In addition, the communication unit 30 transmits the assessment information generated by the generation unit 13 to the terminal device 50.

[0042] (Input / output section 40) Input / output devices such as a keyboard, a mouse, a display, a printer, and a touch panel are connected to the input / output unit 40. The input / output unit 40 receives various types of information input to the information processing device 1A from the connected input devices. Furthermore, the input / output unit 40 outputs various types of information to connected output devices under the control of the control unit 10A. An example of the input / output unit 40 is an interface such as a USB (Universal Serial Bus).

[0043] (Storage unit 20A) The storage unit 20A stores various data referenced by the control unit 10A and various data derived by the control unit 10A. Sensing Data Group SDG Assessment Information Group AIG Extraction model EM ·Extraction condition EC etc. are stored.

[0044] Here, the sensing data group SDG includes sensing data obtained by continuously sensing the daily activities of one or more users using one or more sensing devices 14. The assessment information group AIG is assessment information generated by the generation unit 13 (described later) and includes assessment information related to one or more subjects. The extraction model EM and extraction conditions EC are used by the extraction unit 12 (described later) to extract subjects. The extraction model EM and extraction conditions EC will be described in detail later.

[0045] (Control unit 10A) As shown in FIG. 3, the control unit 10A includes an acquisition unit 11, an extraction unit 12, and a generation unit 13.

[0046] (Acquisition part 11) The acquisition unit 11 acquires sensing data obtained by continuously sensing the daily activities of one or more users. As an example, the acquisition unit 11 acquires sensing data obtained by the sensing from each of the sensing devices 14-1 and 14-2 that continuously sense the daily activities of users U1, U2, .... Here, as in the exemplary embodiment 1, the daily activities of the users include, by way of example, movement such as walking, eating, changing clothes, excretion, bathing, grooming, etc., but these examples do not limit this exemplary embodiment. The details of the sensing data have been described above, so a description thereof will be omitted here.

[0047] (Extraction part 12) The extraction unit 12 extracts one or more subjects from the one or more users by referring to the sensing data acquired by the acquisition unit 11. Here, the term "subject" refers to a subject of assessment information, which will be described later as an example, as in the first exemplary embodiment. Alternatively, the "subject" may refer to a facility user who requires individual intervention for the purpose of nursing care or fall prevention. However, these examples do not limit this exemplary embodiment.

[0048] Although the specific extraction process by the extraction unit 12 does not limit this exemplary embodiment, as an example, the extraction unit 12 may be configured to extract the subject by applying extraction conditions EC to the sensing data, in other words, by determining whether the sensing data satisfies the extraction conditions EC. Here, the extraction conditions EC are conditions used to extract the subject, and as an example, are configured to include conditions that the subject satisfies. As an example, the extraction conditions EC are: - The average value of a predetermined index derived from sensing data, which is the average value of the index for multiple users; and The variance of the predetermined index derived from the sensing data, the variance of the index for a plurality of users The extraction condition EC is set by the extraction unit 12 with reference to at least one of the above. Here, the extraction condition EC may be set for each nursing home or each care facility, for example.

[0049] As another example, the extraction unit 12 may extract the subject by applying a machine-learned extraction model EM to the sensing data, in other words, by inputting the sensing data into the machine-learned extraction model EM. Here, the extraction model EM is a machine-learned extraction model used to extract the subject. For example, the extraction model EM receives sensing data as input and outputs information indicating whether the subject should be considered a subject. For example, the extraction model EM is trained with reference to training data including multiple pairs of sensing data and correct labels indicating whether the subject should be considered a subject. The specific configuration of the extraction model EM does not limit the present exemplary embodiment, and may include, for example, a convolutional neural network (CNN), a recurrent neural network (RNN), or a decision tree. However, these examples do not limit the present exemplary embodiment. For example, the extraction model EM may be trained for each nursing home or care facility.

[0050] Note that the subject extraction process by the extraction unit 12 is not limited to the above example. As an example, the extraction unit 12 may be configured to extract subjects by further referring to information other than the user's sensing data. For example, the extraction unit 12 may extract one or more subject candidates from multiple users by referring to the user's age, gender, work history, information input by the employee at the time of the previous assessment, etc., and may extract subjects using the extracted one or more subject candidates as a population using the extraction criteria EC and extraction model EM. Furthermore, the extraction unit 12 may extract a target person by referring to past sensing data of the user in addition to the latest sensing data of the user. As an example, if the difference between an index derived from the past sensing data of a certain user and an index derived from the latest sensing data of the user is equal to or greater than a predetermined value, the user may be extracted as a target person.

[0051] (Generation part 13) The generation unit 13 generates assessment information about the one or more subjects extracted by the extraction unit 12. As an example, the generation unit 13 generates the assessment information about the subject by referring to the sensing data about the subject. The specific configuration of the assessment information does not limit this exemplary embodiment, but as an example, the assessment information may be configured to include information indicating at least one of the subject's risk of falling and the degree of frailty. Furthermore, the assessment information may be configured to include information indicating the risk or degree of mild cognitive impairment (MCI).

[0052] The assessment information about the subject generated by the generation unit 13 is, for example, presented to the subject or a provider of a service to the subject. Here, the "provider of a service to the subject" is, for example, the same as in the first exemplary embodiment. A business that provides a service using the information processing device 1 to the target person (or the user), Medical professionals (doctors, nurses, physical therapists, etc.) working at facilities that provide services using the information processing device 1 to the target persons (or the users), Caregivers (care workers, social workers, etc.) working at the above facilities, or Family members of the person in question However, it is not limited to this. Furthermore, as in the first exemplary embodiment, the "provider providing a service to the subject" may be considered as a provider that provides nursing care services or the like to the subject. Furthermore, the term "service" may include the provision of support or nursing care, whether paid or free. Therefore, the expression "provider providing a service to the subject" may also be expressed as "a person who supports or cares for the subject." Specific examples of assessment information will be described later.

[0053] (Processing example 1) 5 is a diagram schematically illustrating a processing flow by the information processing system 100A. As shown in FIG. 5, as an example, multiple users U1, U2, U3, etc. wear sensing devices 14-1, 14-2, and 14-3, respectively. The sensing devices 14-1, 14-2, and 14-3 continuously sense the daily activities of each of the users U1, U2, U3, etc., and the acquiring unit 11 acquires the sensing data obtained by the sensing (S11 in FIG. 5). In the example shown in FIG. 5, the multiple users U1, U2, U3, etc. wear insole-type sensors as the sensing devices 14-1, 14-2, and 14-3, respectively, that sense the walking characteristics (gait) of the users, but this is not intended to limit the present example.

[0054] Next, the extraction unit 12 extracts one or more target persons from the one or more users by referring to the sensing data acquired by the acquisition unit 11 (S12 in FIG. 5). In the example shown in FIG. 5, a plurality of target persons T1, T2, ... are extracted from a plurality of users U1, U2, U3, ... by the extraction process by the extraction unit 12. Here, in the example shown in FIG. 5, the target person T1 is user U2, and the target person T2 is user U3, but this is not intended to limit the present example.

[0055] Next, the generation unit 13 generates assessment information regarding the one or more subjects extracted by the extraction unit 12 (S13A in FIG. 5), and then presents the generated assessment information (S13A in FIG. 5).

[0056] 6 shows an example of assessment information generated by the generation unit 13. As an example, the assessment information is generated by the generation unit 13 for "a provider of services to subjects" and is displayed via the input / output unit 40 of the information processing device 1A. As shown in FIG. 6, the assessment information includes information relating to a plurality of users (subjects). ·User ID ·full name Risk of falling Flail Level Advice information Links to more information etc. More specifically, the assessment information shown in FIG. 6 is composed of various information about subject T1 (U2) and various information about subject T2 (U3). In the example shown in FIG. 6, the various information about the subjects is highlighted by a frame or the like so that it can be distinguished from other users who were not extracted as subjects. A "provider providing services to subjects" can appropriately carry out assessments (monitoring, counseling, intervention, etc.) for each subject by referring to the assessment information.

[0057] The fall risk and frailty level included in the assessment information are, for example, derived by the generation unit 13 or the extraction unit 12 with reference to sensing data related to the subject. Also, the advice information included in the assessment information is, for example, selected by the generation unit 13 or the extraction unit 12 from a plurality of advice information candidates with reference to sensing data related to the subject.

[0058] 7 shows another example of assessment information generated by the generating unit 13. As an example, the assessment information is generated by the generating unit 13 for a "subject" and is displayed on the display unit (display unit 51-2 in the example of FIG. 7) of the terminal device 50 used by the subject. As an example, as shown in FIG. 7, the assessment information is Notification information N1 regarding the subject's fall risk or frailty level Advice information for the target person N2 Past history of fall risk or frailty level N3 The user can appropriately recognize his / her own condition and what he / she should do by referring to the assessment information.

[0059] 7 illustrates assessment information for the subject extracted by the extraction unit 12, the generation unit 13 may also generate assessment information for users who were not extracted as subjects. As an example, the generation unit 13 may generate assessment information for the subject U1 on the display unit of the terminal device 50-1 used by the user U1 shown in FIG. Both the risk of falling and the level of frailty were low. · Walking Menu A is recommended. - Past history of fall risk and frailty level The assessment information may be displayed.

[0060] In this way, the assessment information generated by the generating unit 13 may be configured to include information that supports the decision-making of the user or the provider of the service to the user.

[0061] (Processing example 2) Next, another example of the flow of processing by the information processing system 100A will be described with reference to Fig. 8. Fig. 8 is a diagram schematically showing another example of the flow of processing by the information processing system 100A. This processing example shown in Fig. 8 differs from Processing Example 1 shown in Fig. 5 in the following points. That is, in this processing example, after the information processing system 100A presents assessment information, the user to whom the assessment information was provided, or - A provider who has been provided with the assessment information and who provides services to the user The information processing system 100A may further acquire feedback information from the user to whom the assessment information has been provided (S15 in FIG. 8). As an example, the information processing system 100A may acquire feedback information from the user to whom the assessment information has been provided via the terminal device 50. The information processing system 100A may also acquire feedback information from the provider via the input / output unit 40.

[0062] Furthermore, in this processing example, as shown in FIG. 8, these pieces of feedback information are referred to in the next subject extraction processing (S12 in FIG. 8). As an example, the extraction unit 12 may be configured to update the extraction model EM or the extraction conditions EC by referring to the feedback information. As an example, when the feedback information regarding a certain subject indicates that the subject has a low fall risk and a low frailty level, the extraction unit 12 may be configured to update the extraction model EM or the extraction conditions EC so that the subject is less likely to be extracted as a subject in the next extraction processing.

[0063] (Effects of information processing system 100A) As described above, the information processing system 100A is configured to include a sensing unit 14 that continuously senses the daily activities of one or more users, an acquisition unit 11 that acquires sensing data obtained by the sensing unit 14, an extraction unit 12 that extracts one or more subjects from the one or more users by referring to the sensing data, and a generation unit 13 that generates assessment information regarding the one or more subjects.

[0064] According to the above configuration, subjects are extracted by referring to sensing data obtained by continuously sensing the user's activities in their daily lives, and assessment information about the subjects is generated, thereby making it possible to appropriately assess people who require support, care, etc., or who may be in need of such support, care, etc., while minimizing the human resources required for involvement.

[0065] Furthermore, as described above, by referring to the assessment information for the service provider generated by the generation unit 13, the service provider can appropriately carry out assessment (monitoring, counseling, intervention, etc.) for each subject.

[0066] Furthermore, as described above, by referring to the assessment information for the subject generated by the generating unit 13, the subject can appropriately recognize his or her own condition and what he or she should do.

[0067] [Software implementation example] Some or all of the functions of the information processing devices 1, 1A and terminal device 50 (hereinafter also referred to as "each of the above devices") may be realized by hardware such as an integrated circuit (IC chip), or by software.

[0068] In the latter case, each of the above devices is realized by, for example, a computer that executes instructions of a program, which is software that realizes each function. An example of such a computer (hereinafter referred to as computer C) is shown in Figure 9. Figure 9 is a block diagram showing the hardware configuration of computer C that functions as each of the above devices.

[0069] The computer C includes at least one processor C1 and at least one memory C2. The memory C2 stores a program P for causing the computer C to operate as each of the above-mentioned devices. In the computer C, the processor C1 reads and executes the program P from the memory C2, thereby realizing the functions of each of the above-mentioned devices.

[0070] The processor C1 may be, for example, a central processing unit (CPU), a graphic processing unit (GPU), a digital signal processor (DSP), a micro processing unit (MPU), a floating point number processing unit (FPU), a physics processing unit (PPU), a tensor processing unit (TPU), a quantum processor, a microcontroller, or a combination thereof. The memory C2 may be, for example, a flash memory, a hard disk drive (HDD), a solid state drive (SSD), or a combination thereof.

[0071] The computer C may further include a RAM (Random Access Memory) for expanding the program P during execution and for temporarily storing various data. The computer C may also include a communication interface for transmitting and receiving data to and from other devices. The computer C may also include an input / output interface for connecting input / output devices such as a keyboard, mouse, display, and printer.

[0072] Furthermore, the program P can be recorded on a non-transitory tangible recording medium M that can be read by the computer C. Such a recording medium M can be, for example, a tape, a disk, a card, a semiconductor memory, or a programmable logic circuit. The computer C can acquire the program P via such a recording medium M. The program P can also be transmitted via a transmission medium. Such a transmission medium can be, for example, a communication network or broadcast waves. The computer C can also acquire the program P via such a transmission medium.

[0073] Furthermore, the functions of each of the devices may be realized by a single processor provided in a single computer, by multiple processors provided in a single computer working in cooperation, or by multiple processors provided in each of multiple computers working in cooperation. Furthermore, the programs for causing each of the devices to realize the functions may be stored in a single memory provided in a single computer, or may be distributed and stored in multiple memories provided in a single computer, or may be distributed and stored in multiple memories provided in each of multiple computers.

[0074] [Appendix A] This disclosure includes the techniques described in the following appendices. However, the present invention is not limited to the techniques described in the following appendices, and various modifications are possible within the scope of the claims.

[0075] (Appendix A1) An acquisition means for acquiring sensing data obtained by continuously sensing the daily activities of one or more users; an extraction means for extracting one or more subjects from the one or more users by referring to the sensing data; generating means for generating assessment information regarding the one or more subjects; An information processing device comprising:

[0076] (Appendix A2) The sensing data includes data obtained by continuously sensing at least one of the user's vital signs, activity level, posture, and walking characteristics. 10. The information processing device according to claim 1,

[0077] (Appendix A3) The sensing data includes data acquired from an insole-type sensor that senses the walking characteristics of the user. 10. The information processing device according to claim 9, wherein the information processing device is a

[0078] (Appendix A4) The assessment information includes information indicating at least one of the subject's risk of falling and the degree of frailty. 10. The information processing device according to claim 9, wherein the information processing device is a

[0079] (Appendix A5) The extraction means by applying extraction conditions to the sensing data; or By applying a machine-learned extraction model to the sensing data, Extracting the one or more target persons from the one or more users An information processing device according to any one of appendices A1 to A4.

[0080] (Appendix A6) The acquisition means the user to whom the assessment information was provided; or A provider who has been provided with the assessment information and who provides a service to the user Get more feedback from The extraction means updates the extraction model or the extraction conditions by referring to the feedback information. 10. The information processing device according to claim 9, wherein the information processing device is a

[0081] (Appendix A7) The assessment information includes information that supports the decision-making of the user or a provider of services to the user. An information processing device according to any one of appendices A1 to A6.

[0082] (Appendix A8) A sensing means for continuously sensing the daily activities of each of one or more users; an acquisition means for acquiring sensing data obtained by the sensing means; an extraction means for extracting one or more subjects from the one or more users by referring to the sensing data; generating means for generating assessment information regarding the one or more subjects; An information processing system comprising:

[0083] (Appendix A9) The sensing means continuously senses at least one of the user's vital signs, activity level, posture, and walking characteristics. 1. An information processing system as described in Appendix A8.

[0084] (Appendix A10) The sensing means is an insole-type sensor that senses the walking characteristics of the user. 1. An information processing system as described in Appendix A9.

[0085] [Appendix B] This disclosure includes the techniques described in the following appendices. However, the present invention is not limited to the techniques described in the following appendices, and various modifications are possible within the scope of the claims.

[0086] (Appendix B1) an acquisition process in which at least one processor acquires sensing data obtained by continuously sensing the daily activities of one or more users; an extraction process in which the at least one processor extracts one or more target persons from the one or more users by referring to the sensing data; a generating process in which the at least one processor generates assessment information regarding the one or more subjects; An information processing method comprising:

[0087] (Appendix B2) The sensing data includes data obtained by continuously sensing at least one of the user's vital signs, activity level, posture, and walking characteristics. 1. The information processing method described in Appendix B1.

[0088] (Appendix B3) The sensing data includes data acquired from an insole-type sensor that senses the walking characteristics of the user. 1. The information processing method described in Appendix B2.

[0089] (Appendix B4) The assessment information includes information indicating at least one of the subject's risk of falling and the degree of frailty. The information processing method described in Appendix B3.

[0090] (Appendix B5) In the extraction process, the at least one processor by applying extraction conditions to the sensing data; or By applying a machine-learned extraction model to the sensing data, Extracting the one or more target persons from the one or more users 1. An information processing method according to any one of appendices B1 to B4.

[0091] (Appendix B6) In the acquisition process, the at least one processor: the user to whom the assessment information was provided; or A provider who has been provided with the assessment information and who provides a service to the user Get more feedback from In the extraction process, the at least one processor refers to the feedback information and updates the extraction model or the extraction conditions. The information processing method described in Appendix B5.

[0092] (Appendix B7) The assessment information includes information that supports the decision-making of the user or a provider of services to the user. 10. An information processing method according to any one of appendices B1 to B6.

[0093] [Appendix C] This disclosure includes the techniques described in the following appendices. However, the present invention is not limited to the techniques described in the following appendices, and various modifications are possible within the scope of the claims.

[0094] (Appendix C1) A program that causes a computer to function as an information processing device, The computer An acquisition means for acquiring sensing data obtained by continuously sensing the daily activities of one or more users; an extraction means for extracting one or more subjects from the one or more users by referring to the sensing data; generating means for generating assessment information regarding the one or more subjects; An information processing program that functions as a

[0095] (Appendix C2) The sensing data includes data obtained by continuously sensing at least one of the user's vital signs, activity level, posture, and walking characteristics. An information processing program as described in Appendix C1.

[0096] (Appendix C3) The sensing data includes data acquired from an insole-type sensor that senses the walking characteristics of the user. An information processing program as described in Appendix C2.

[0097] (Appendix C4) The assessment information includes information indicating at least one of the subject's risk of falling and the degree of frailty. An information processing program as described in Appendix C3.

[0098] (Appendix C5) The extraction means by applying extraction conditions to the sensing data; or By applying a machine-learned extraction model to the sensing data, Extracting the one or more target persons from the one or more users An information processing program according to any one of appendices C1 to C4.

[0099] (Appendix C6) The acquisition means the user to whom the assessment information was provided; or A provider who has been provided with the assessment information and who provides a service to the user Get more feedback from The extraction means updates the extraction model or the extraction conditions by referring to the feedback information. An information processing program as described in Appendix C5.

[0100] (Appendix C7) The assessment information includes information that supports the decision-making of the user or a provider of services to the user. An information processing program according to any one of appendices C1 to C6.

[0101] [Appendix D] This disclosure includes the techniques described in the following appendices. However, the present invention is not limited to the techniques described in the following appendices, and various modifications are possible within the scope of the claims.

[0102] (Appendix D1) at least one processor, An acquisition process for acquiring sensing data obtained by continuously sensing the daily activities of one or more users; an extraction process of extracting one or more target persons from the one or more users by referring to the sensing data; a generation process for generating assessment information regarding the one or more subjects; An information processing device that executes the above.

[0103] The information processing device may further include a memory, and the memory may store a program for causing the at least one processor to execute each of the processes.

[0104] (Appendix D2) The sensing data includes data obtained by continuously sensing at least one of the user's vital signs, activity level, posture, and walking characteristics. 10. The information processing device according to claim 9, wherein the information processing device is a device for processing information.

[0105] (Appendix D3) The sensing data includes data acquired from an insole-type sensor that senses the walking characteristics of the user. 10. The information processing device according to claim 9, wherein the information processing device is an information processing device according to claim 1, wherein

[0106] (Appendix D4) The assessment information includes information indicating at least one of the subject's risk of falling and the degree of frailty. 10. The information processing device according to claim 9, wherein the information processing device is an information processing device according to claim 1, wherein

[0107] (Appendix D5) In the extraction process, the at least one processor by applying extraction conditions to the sensing data; or By applying a machine-learned extraction model to the sensing data, Extracting the one or more target persons from the one or more users An information processing device according to any one of appendices D1 to D4.

[0108] (Appendix D6) In the acquisition process, the at least one processor: the user to whom the assessment information was provided; or A provider who has been provided with the assessment information and who provides a service to the user Get more feedback from In the extraction process, the at least one processor refers to the feedback information and updates the extraction model or the extraction conditions. 10. The information processing device according to claim 9, wherein said information processing device is a

[0109] (Appendix D7) The assessment information includes information that supports the decision-making of the user or a provider of services to the user. An information processing device according to any one of appendices D1 to D6.

[0110] [Appendix E] This disclosure includes the techniques described in the following appendices. However, the present invention is not limited to the techniques described in the following appendices, and various modifications are possible within the scope of the claims.

[0111] (Appendix E1) A program that causes a computer to function as an information processing device, The computer, An acquisition process for acquiring sensing data obtained by continuously sensing the daily activities of one or more users; an extraction process of extracting one or more target persons from the one or more users by referring to the sensing data; a generation process for generating assessment information regarding the one or more subjects; A non-transitory recording medium on which an information processing program for executing the above is recorded. [Explanation of symbols]

[0112] 100,100A ···Information Processing System 1,1A Information processing device 11...Acquisition part 12...Extraction part 13...Generation section

Claims

1. an acquisition means for acquiring sensing data obtained by continuously sensing the daily activities of one or more users; an extraction means for extracting one or more subjects from the one or more users by referring to the sensing data; generating means for generating assessment information regarding the one or more subjects; An information processing device comprising:

2. The sensing data includes data obtained by continuously sensing at least one of the user's vital signs, activity level, posture, and walking characteristics. The information processing device according to claim 1 .

3. The sensing data includes data acquired from an insole-type sensor that senses the walking characteristics of the user. The information processing device according to claim 2 .

4. The assessment information includes information indicating at least one of the subject's risk of falling and the degree of frailty. The information processing device according to claim 3 .

5. The extraction means by applying extraction conditions to the sensing data; or By applying a machine-learned extraction model to the sensing data, Extracting the one or more target persons from the one or more users. The information processing device according to claim 1 .

6. The acquisition means the user to whom the assessment information was provided; or A provider who has been provided with the assessment information and who provides a service to the user Get more feedback from The extraction means updates the extraction model or the extraction conditions by referring to the feedback information. The information processing device according to claim 5 .

7. The assessment information includes information that supports the decision-making of the user or a provider of services to the user. The information processing device according to claim 1 .

8. a sensing means for continuously sensing the daily activities of each of one or more users; an acquisition means for acquiring sensing data obtained by the sensing means; an extraction means for extracting one or more subjects from the one or more users by referring to the sensing data; generating means for generating assessment information regarding the one or more subjects; An information processing system comprising:

9. one or more processors Acquiring sensing data obtained by continuously sensing the daily activities of one or more users; extracting one or more subjects from the one or more users by referring to the sensing data; generating assessment information regarding the one or more subjects; An information processing method comprising:

10. A program that causes a computer to function as an information processing device, the program comprising: an acquisition means for acquiring sensing data obtained by continuously sensing the daily activities of one or more users; an extraction means for extracting one or more subjects from the one or more users by referring to the sensing data; generating means for generating assessment information regarding the one or more subjects; A program that functions as a

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