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

Abstract

An information processing system, an information processing device, an information processing program, and an information processing method for easily evaluating a user's psychological state are provided. [Solution] In an information processing system in which a server device is communicatively connected to a user terminal and a sensor terminal via a communication network, the server device comprises a psychological state information acquisition unit that acquires at least one of a user's objective psychological state information and subjective psychological state information, a biosignal information acquisition unit that acquires the user's biosignal information, and a prediction unit that predicts the user's psychological state using a prediction model that uses the biosignal information as input information and the psychological state information as output information.

Description

[Technical field]

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

[0002] In recent years, psychological states have been evaluated by various methods. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Special Publication No. 2018-524750 Summary of the Invention [Problem to be solved by the invention]

[0004] For example, Patent Document 1 proposes a method for monitoring stress conditions.

[0005] However, this requires evaluation by an expert and is not a simple method.

[0006] The present invention has been made in view of the above background, and has an object to easily evaluate the psychological state of a user. [Means for solving the problem]

[0007] a psychological state information acquisition unit that acquires at least one of objective psychological state information and subjective psychological state information of a user; a biosignal information acquisition unit that acquires biosignal information of the user; and a prediction unit that predicts the psychological state of the user by a prediction model that uses at least the biosignal information as input information and the psychological state information as output information; Equipped with.

[0008] Other problems and solutions disclosed in this application will be made clear in the description of the preferred embodiments of the invention and the drawings. Effect of the Invention

[0009] According to the present invention, the psychological state of a user can be easily evaluated. [Brief description of the drawings]

[0010] [Figure 1] 1 is a diagram showing an example of the overall configuration of an evaluation system according to an embodiment of the present invention; [Diagram 2] 2 is a diagram illustrating an example of a hardware configuration of a server device 1 according to the embodiment. FIG. [Diagram 3] 2 is a diagram illustrating an example of a functional configuration of a server device 1 according to the embodiment. FIG. [Figure 4] 10 is a diagram showing an example of user information stored in a user information storage unit 131. FIG. [Diagram 5] FIG. 11 is a diagram illustrating an example of a process of the server device 1 according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] <Summary of the Invention> [Item 1] a psychological state information acquisition unit that acquires at least one of objective psychological state information and subjective psychological state information of a user; A biosignal information acquisition unit that acquires biosignal information of the user; A prediction unit that predicts the psychological state of the user using a prediction model in which the biological signal information is input information and the psychological state information is output information; An information processing system comprising: [Item 2] The objective psychological state information is information on the amount of a substance contained in hair. Item 1. An information processing system according to item 1. [Item 3] The substance is at least one of a stress hormone. Item 3. An information processing system according to item 2. [Item 4] The biological information is heart rate information during sleep. 4. An information processing system according to any one of items 1 to 3. [Item 5] the prediction unit predicts an amount of a substance contained in the hair of the user in the future when the psychological state information includes information on an amount of a substance contained in the hair, and predicts the psychological state of the user based on the information on the amount of a substance contained in the hair. 5. An information processing system according to any one of items 2 to 4. [Item 6] acquiring at least one of objective psychological state information and subjective psychological state information of a user; A biosignal information acquisition unit that acquires biosignal information of the user; A prediction unit that predicts the psychological state of the user using a prediction model in which the biological signal information is input information and the psychological state information is output information; An information processing device comprising: [Item 7] On the computer, A psychological state information acquisition step of acquiring at least one of objective psychological state information and subjective psychological state information of a user; A biosignal information acquiring step of acquiring biosignal information of the user; a prediction step of predicting the psychological state of the user using a prediction model in which the biological signal information is input information and the psychological state information is output information; An information processing program that executes the above. [Item 8] The computer A psychological state information acquisition step of acquiring at least one of objective psychological state information and subjective psychological state information of a user; A biosignal information acquiring step of acquiring biosignal information of the user; a prediction step of predicting the psychological state of the user using a prediction model in which the biological signal information is input information and the psychological state information is output information; An information processing method.

[0012] 1 is a diagram showing an example of the overall configuration of an information processing system according to an embodiment of the present invention. The information processing system of this embodiment includes a server device 1, a user terminal 3, and a sensor terminal 4. The server device 1 is communicatively connected to the user terminal 3 and the sensor terminal 4 via a communication network 2. The communication network 2 is, for example, the Internet, and is constructed by a public telephone line network, a mobile phone line network, a wireless communication path, Ethernet (registered trademark), or the like.

[0013] ==Server device 1== The server device 1 may be, for example, a general-purpose computer such as a workstation or a personal computer, or may be logically realized by cloud computing. In this embodiment, one server device is illustrated for convenience of explanation, but the present invention is not limited to this and may be multiple servers.

[0014] ==User terminal 3== The user terminal 3 is a computer operated by a user who is to be evaluated for his / her psychological state. The user terminal 3 is, for example, a smartphone, a tablet computer, a personal computer, a wearable computer, etc. The user can access the server device 1 by, for example, an application or a web browser executed on the user terminal 3.

[0015] ==Sensor terminal 4== The sensor terminal 4 is a computer equipped with a sensor that acquires a user's biosignal. The sensor terminal 4 is, for example, a wearable computer. The sensor may be a biosignal sensor that acquires biodata such as heart rate, blood pressure, blood lineage value, and body temperature. The sensor terminal 4 may be, for example, a wearable device such as FitBit (registered trademark), but is not limited thereto.

[0016] The sensor terminal 4 may be communicatively connected to the user terminal 3 via the network 2. In this case, the user terminal 3 may acquire the biometric data acquired by the sensor terminal 4 through communication or the like, and further transmit the data to the server device 1 via the network 2.

[0017] FIG. 2 is a diagram showing an example of the hardware configuration of the server device 1. Note that the illustrated configuration is an example, and other configurations may be used. The server device 1 includes a processor 101, a memory 102, a storage device 103, a communication interface 104, an input device 105, and an output device 106. The storage device 103 is, for example, a hard disk drive, a solid state drive, or a flash memory that stores various data and programs. The communication interface 104 is an interface for connecting to the communication network 2, and is, for example, an adapter for connecting to Ethernet (registered trademark), a modem for connecting to a public telephone line network, a wireless communication device for wireless communication, a USB (Universal Serial Bus) connector or an RS232C connector for serial communication, etc. The input device 105 is, for example, a keyboard, a mouse, a touch panel, a button, a microphone, etc. that input data. The output device 106 is, for example, a display, a printer, a speaker, etc. that output data. Each functional unit of the server device 1, which will be described later, is realized by the processor 101 reading a program stored in the storage device 103 into the memory 102 and executing it, and each storage unit of the server device 1 is realized as part of the storage area provided by the memory 102 and the storage device 103.

[0018] Fig. 3 shows a functional configuration of the server device 1. As shown in Fig. 3, the server device 1 includes storage units, namely, a user information storage unit 131 and a model storage unit 132, and processing units, namely, a user information acquisition unit 111, a psychological state information acquisition unit 112, a biological signal information acquisition unit 113, a model generation unit 114, a prediction unit 115, and a presentation unit 116.

[0019] The user information storage unit 131 and the model storage unit 132 will be described below.

[0020] The user information storage unit 131 stores information about the user, as shown in Fig. 4. The information stored in the user information storage unit 131 includes, but is not limited to, user information (e.g., name, age, sex, etc.) linked to a user ID, psychological state information (e.g., objective psychological state information, subjective psychological state information, etc.), and biological signals (heart rate, blood pressure, etc.).

[0021] The model storage unit 132 stores a prediction model generated by a model generation unit, which will be described later.

[0022] The following describes each of the processing units, namely, the user information acquiring unit 111, the psychological state information acquiring unit 112, the biological signal information acquiring unit 113, the model generating unit 114, the predicting unit 115, and the presenting unit 116.

[0023] As an example, the user information acquisition unit 111 acquires or receives data of user information from the user terminal 3 via the communication network 2, and stores the data in the user information storage unit 131. The communication in the transmission and reception may be either wired or wireless, and any communication protocol may be used as long as the communication between the two devices can be performed.

[0024] As an example, the psychological state information acquiring section 112 acquires psychological state information relating to the psychological state, and stores it in the user information storage section 131 .

[0025] In this embodiment, the psychological state refers to a person's state of mind, and includes various states such as stress, perception, pain and pleasure experiences, beliefs, desires, intentions, emotions, memories, etc. In this embodiment, the psychological state information representing the psychological state includes two types: a subjective psychological state and an objective psychological state.

[0026] As an example, the psychological state information acquisition section 112 acquires subjective psychological state information relating to the user's subjective psychological state from the user terminal 3 via the communication network 2 and stores it in the user information storage section 131.

[0027] The psychological state information acquiring section 112 presents the psychological scale to the user terminal 3. The psychological state information acquiring section 112 may accept an input or selection operation of answer information to the psychological scale by the user, and acquire subjective psychological state information.

[0028] In this embodiment, the psychological scale is a method for measuring a psychological state, and the psychological state of an individual can be grasped by scoring answers to several questions. Examples of the psychological scale include, but are not limited to, mindset scales such as the Occupational Stress Brief Questionnaire, the GHQ Mental Health Survey World Health Organization version, WHO SUBI, and the PHRF Stress Checklist Short Form, Stress Coping Inventory, PSS (Perceived Stress Scale), SSQ (Stress Symptoms Questionnaire), DASS (Depression Anxiety Stress Scales), and SRRS (Social Readjustment Rating Scale).

[0029] As an example, the psychological state information acquiring unit 112 acquires objective psychological state information related to the objective psychological state, and stores it in the user information storage unit 131. The psychological state information acquiring unit 112 may acquire the objective psychological state information from the user terminal 3, or may acquire it via the network 2 from a business terminal used by a business that tests and measures the objective psychological state, but is not limited to these methods.

[0030] In this embodiment, the objective psychological state information includes, for example, information about components obtained by analyzing a biological sample obtained from the user, and is composed of information such as the type of sample, the date of sample acquisition, the analysis site, the components contained, the component content, the type of damage, and the degree of damage.

[0031] In this embodiment, the biological sample is, for example, a structure mainly composed of protein that occurs on the body surface of the user, and examples include, but are not limited to, hair, body hair, nails, keratin, etc. In addition, the biological sample may be a body fluid such as saliva, urine, sweat, or blood.

[0032] In this embodiment, components contained in a biological sample may include, by way of example, proteins, hormones, lipids, steroids, pigments, minerals, nucleic acids, and the like, but are not limited to these.

[0033] The component may be, for example, a hormone known as a stress hormone, and examples thereof may include, but are not limited to, cortisol (COR), dehydroepiandrosterone (DHEA), testosterone (TTE), estradiol (E2), oxytocin (OT), serotonin (5-HT), and the like.

[0034] As one example, the analysis site may be defined in stages from a site close to the skin when the biological sample is present on the body surface to a site distant from the skin.

[0035] As an example, when the sample is hair, the analysis site may be defined by the distance from the root of the hair, but is not limited thereto.

[0036] As an example, when the sample is hair, the analysis area may be determined based on the distance from the hair root area and how long it has been since the area was created, since hair grows about 1 cm per month on average, but is not limited to this.

[0037] The objective psychological state information may be, for example, when the biological sample is hair and the component is a stress hormone, information on the amount of stress hormone extracted from the sample by a known pretreatment method and analyzed by a known method such as ELISA (Enzyme-Linked Immunosorbent Assay).

[0038] The biosignal information acquiring unit 113 acquires biosignal information of the user. The biosignal information acquiring unit 113 may acquire the biosignal acquired by the sensor terminal 4 as the biosignal information.

[0039] The biosignal in this embodiment may be, for example, heart rate information. The biosignal in this embodiment may be, for example, heart rate information during sleep. The biosignal in this embodiment may be, for example, the minimum heart rate among the heart rate information during sleep. The heart rate indicates the number of times the heart beats within a certain period of time, for example, the number of beats per minute, but is not limited thereto. In this case, the biosignal information acquisition unit 113 may group the heart rate data acquired from the sensor terminal 4, for example, every 10 minutes, calculate the median value of each group, and acquire the heart rate obtained by smoothing the median value every minute as the heart rate information. The biosignal information acquisition unit 113 may extract the heart rate during sleep from the heart rates smoothed by the above-mentioned method, and further acquire the minimum value as the heart rate information.

[0040] The biosignal in this embodiment may be a numerical value obtained by indexing the heart rate information according to a predetermined rule. In this case, the biosignal information acquiring unit 113 may acquire information on the minimum heart rate during sleep during a predetermined period, and if the minimum heart rate of the day is greater than the average or median, the value is set to 1, otherwise, the total of the numerical values ​​during the period is divided by the number of days in the predetermined period (hereinafter, referred to as a stress index), and the resulting numerical value may be used as the biosignal.

[0041] The model generation unit 114 generates a prediction model for predicting the user's future psychological state based on the information stored in the user information storage unit 131 by a statistical method such as learning, and stores the model in the model storage unit 132. The method for generating the prediction model used by the model generation unit 114 may include classification, regression, correlation analysis, feature importance calculation, clustering, etc., and these statistical models may be implemented in a manner generally used in statistics, and detailed explanations thereof will be omitted here.

[0042] The input data for the prediction model that can derive relationships generated by the model generation unit 114 using these techniques is at least either psychological state information or biological signal information.

[0043] Furthermore, as described above, the model generation unit 114 may generate the prediction model by a statistical method such as learning, but as an example, a specific machine learning model will be described. The prediction model generated by the model generation unit 114 may predict objective psychological state information, in which case, input data for the machine learning model are subjective psychological state information and biosignal information, and output data is objective psychological state information. Specifically, the prediction model generated by the model generation unit 114 may predict the amount of stress hormone in hair, in which case, input data for the machine learning model are subjective psychological state information and heart rate information, and output data is information on the amount of stress hormone in hair.

[0044] The model generating unit 114 may generate a prediction model that predicts past psychological state information using input information corresponding to a predetermined period. For example, the model generating unit 114 may use the objective psychological state information acquired on the Nth day (information on the amount of stress hormone in hair, which is information on the amount of stress hormone from the root of the hair sample to about 1 cm, i.e., the amount of stress hormone from the Nth day to the (N-30th) day when the hair sample was acquired), the objective psychological state information acquired on the (N+30th) day, and the biological signal information from the Nth day to the (N+30th) day (e.g., stress index) as learning data, and generate a model in which the objective psychological state information acquired on the (N+30th) day and the biological signal information from the Nth day to the (N+30th) day (e.g., stress index) are input information, and the amount of stress hormone from the Nth day to the (N-30th) day is output information.

[0045] The model generating unit 114 may generate a prediction model that predicts psychological state information for a predetermined period using input information corresponding to the predetermined period. For example, the model generating unit 114 may use the objective psychological state information acquired on the Nth day (information on the amount of stress hormone in hair, which is information on the amount of stress hormone from the root of the hair sample to about 1 cm, i.e., the amount of stress hormone from the Nth day to the (N-30)th day when the hair sample was acquired), the objective psychological state information acquired on the Nth day, and biological signal information (e.g., stress index) from (N-30) days ago to the Nth day as learning data, and generate a model in which the objective psychological state information acquired on the Nth day and the biological signal information (e.g., stress index) from the (N-30)th day to the Nth day are input information, and the amount of stress hormone from the Nth day to the (N-30)th day is output information.

[0046] The model generating unit 114 may generate a prediction model that predicts future psychological state information using input information corresponding to a predetermined period. For example, the model generating unit 114 may use the objective psychological state information acquired on the (N+30)th day (information on the amount of stress hormone in hair, from the root of the hair sample to about 1 cm, i.e., the amount of stress hormone from the N+30th day when the hair sample was acquired to the Nth day) acquired on the (N+30)th day, the objective psychological state information acquired on the Nth day, and the biological signal information (e.g., stress index) from (N-30) days ago to the Nth day as learning data, and generate a model in which the objective psychological state information acquired on the Nth day and the biological signal information (e.g., stress index) from (N-30) days ago to the Nth day are input information, and the amount of stress hormone from the Nth day to the (N+30)th day is output information.

[0047] In the above example, the predetermined period is not limited to 30 days, and any period may be set.

[0048] In addition, in the above example, an example was described in which objective psychological state information and bio-signal information were used as input information, but for example, a prediction model may be generated in which subjective psychological state information and objective psychological state information are used as input information and bio-signal information is used as output information, or a prediction model may be generated in which subjective psychological state information and bio-signal information are used as input information and objective psychological state information is used as output information.

[0049] The prediction unit 115 uses the prediction model generated by the model generation unit 114 to predict the psychological state of the user.

[0050] As an example, the prediction unit 115 inputs predetermined input information into the prediction model generated by the model generation unit 114, and predicts the user's psychological state based on the output information. The prediction unit 115 may, for example, predict the amount of stress hormones in the hair using a prediction model that predicts objective psychological state information (for example, the amount of stress hormones in the hair) generated by the model generation unit 114, and predict the user's psychological state from the amount of stress hormones.

[0051] The presentation unit 116 presents the information on the psychological state predicted by the prediction unit 115 to the user terminal 3.

[0052] FIG. 5 is a diagram illustrating an example of the processing of the evaluation device of this embodiment.

[0053] The server device 1 acquires user information (1001). The server device 1 acquires psychological state information (1002). The server device 1 acquires biological signal information (1003). The server device 1 generates a prediction model (1004). The server device 1 predicts the psychological state (1005). The server device 1 presents the predicted psychological state to the user.

[0054] Although the preferred embodiment of the present disclosure has been described in detail above with reference to the attached drawings, the technical scope of the present disclosure is not limited to such examples. It is clear that a person having ordinary knowledge in the technical field of the present disclosure can conceive of various modified or amended examples within the scope of the technical ideas described in the claims, and it is understood that these also naturally belong to the technical scope of the present disclosure.

[0055] The device described in this specification may be realized as a single device, or may be realized by a plurality of devices (e.g., cloud servers) partially or entirely connected by a communication network. For example, the CPU and storage device of the server device 1 may be realized by different servers connected to each other by a communication network.

[0056] The series of processes performed by the device described in this specification may be realized using any of software, hardware, and a combination of software and hardware. It is possible to create a computer program for realizing each function of the server device 1 according to this embodiment and install it in a PC or the like. It is also possible to provide a computer-readable recording medium in which such a computer program is stored. The recording medium is, for example, a magnetic disk, an optical disk, a magneto-optical disk, a flash memory, etc. The above computer program may also be distributed, for example, via a communication network, without using a recording medium.

[0057] Additionally, the processes described herein do not necessarily have to be performed in the order described, some process steps may be performed in parallel, additional process steps may be employed, and some process steps may be omitted.

[0058] In addition, the effects described in this specification are merely descriptive or exemplary and are not limiting. In other words, the technology according to the present disclosure may achieve other effects that are apparent to a person skilled in the art from the description of this specification, in addition to or in place of the above effects. [Explanation of symbols]

[0059] 1. Server device 2. Communication Network 3. User terminal 101 CPU 102 Memory 103 Storage device 104 Communication Interface 105 Input Device 106 Output Device 111 User information acquisition unit 112 Psychological state information acquisition unit 113 Biological signal acquisition unit 114 Model Generation Unit 115 Prediction Department 116 Presentation section 131 User information storage unit 132 Model Memory Section

Claims

1. a psychological state information acquiring unit that acquires psychological state information including objective psychological state information and subjective psychological state information acquired from a portion of a biological sample of a user; A biosignal information acquisition unit that acquires biosignal information of the user; a prediction unit that predicts the user's future psychological state from the biosignal information during a period corresponding to the formation period of a portion of the user's biological sample, using a prediction model generated by machine learning using the psychological state information and the biosignal information during a period corresponding to the formation period of a portion of the user's biological sample as learning data, the prediction model having the biosignal information during a period corresponding to the formation period of a portion of the user's biological sample as input information and the psychological state information as output information; An information processing system comprising:

2. The biological sample is hair, The objective psychological state information is information on the amount of a substance contained in the hair. The information processing system according to claim 1 .

3. The substance is at least one of a stress hormone. The information processing system according to claim 2 .

4. The biological signal information is the minimum heart rate of the user during sleep.

4. An information processing system according to claim 1.

5. The prediction unit acquires information on an amount of a substance contained in the user's hair as the psychological state information, Using the predictive model to predict the amount of material contained in the user's future hair; determining a future state of mind of the user based on the predicted amount of the substance; 4. The information processing system according to claim 2 or 3.

6. a psychological state information acquiring unit that acquires psychological state information including objective psychological state information and subjective psychological state information acquired from a portion of a biological sample of a user; A biosignal information acquisition unit that acquires biosignal information of the user; a prediction unit that predicts the user's future psychological state from the biosignal information during a period corresponding to the formation period of a portion of the user's biological sample, using a prediction model generated by machine learning using the psychological state information and the biosignal information during a period corresponding to the formation period of a portion of the user's biological sample as learning data, the prediction model having the biosignal information during a period corresponding to the formation period of a portion of the user's biological sample as input information and the psychological state information as output information; An information processing device comprising:

7. On the computer, a psychological state information acquiring step of acquiring psychological state information including objective psychological state information and subjective psychological state information acquired from a portion of a biological sample of the user; A biosignal information acquiring step of acquiring biosignal information of the user; a prediction step of predicting the future psychological state of the user from the biosignal information during a period corresponding to the formation period of a portion of the user's biological sample, using a prediction model generated by machine learning using the psychological state information and the biosignal information during a period corresponding to the formation period of a portion of the user's biological sample as learning data, the prediction model having the biosignal information during a period corresponding to the formation period of a portion of the user's biological sample as input information and the psychological state information as output information; An information processing program that executes the above.

8. The computer a psychological state information acquiring step of acquiring psychological state information including objective psychological state information and subjective psychological state information acquired from a portion of a biological sample of the user; A biosignal information acquiring step of acquiring biosignal information of the user; a prediction step of predicting the future psychological state of the user from the biosignal information during a period corresponding to the formation period of a portion of the user's biological sample, using a prediction model generated by machine learning using the psychological state information and the biosignal information during a period corresponding to the formation period of a portion of the user's biological sample as learning data, the prediction model having the biosignal information during a period corresponding to the formation period of a portion of the user's biological sample as input information and the psychological state information as output information; An information processing method.

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