Information processing systems, information processing devices, information processing programs, information processing methods

Abstract

This invention provides an information processing system, information processing device, information processing program, and information processing method for easily evaluating a user's psychological state. [Solution] In an information processing system in which a server device is 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 the 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 takes 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 apparatus, an information processing program, and an information processing method.

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

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

[0005] However, it requires evaluation by an expert and cannot be said to be a simple method.

[0006] The present invention has been made in view of such a background, and an object thereof is to simply evaluate the psychological state of a user.

Means for Solving the Problems

[0007] a mental state information acquisition unit that acquires at least one of objective mental state information and subjective mental state information of a user; a biological signal information acquisition unit that acquires biological signal information of the user; and a prediction unit that predicts the mental state of the user by using a prediction model that uses at least the biological signal information as input information and the mental state information as output information. is provided.

[0008] Further issues and solutions disclosed in this application will be made clear in the section on embodiments of the invention and in the drawings. [Effects of the Invention]

[0009] According to the present invention, the user's psychological state can be easily evaluated. [Brief explanation of the drawing]

[0010] [Figure 1] This figure shows an example of the overall configuration of an evaluation system according to one embodiment of the present invention. [Figure 2] This figure shows an example of the hardware configuration of the server device 1 according to the same embodiment. [Figure 3] This figure shows an example of the functional configuration of the server device 1 according to the same embodiment. [Figure 4] This figure shows an example of user information stored in the user information storage unit 131. [Figure 5] This figure shows an example of processing by the server device 1 according to the same embodiment. [Modes for carrying out the invention]

[0011] <Summary of the Invention> [Item 1] A psychological state information acquisition unit that acquires at least one of the user's objective psychological state information and subjective psychological state information, A biosignal information acquisition unit that acquires the user's biosignal information, A prediction unit predicts the user's psychological state using a prediction model that takes the aforementioned biosignal information as input information and the aforementioned psychological state information as output information. An information processing system equipped with the following features. [Item 2] The aforementioned objective psychological state information is information about the amount of substances contained in the hair. The information processing system described in item 1. [Item 3] The substance is at least one of the stress hormones. The information processing system according to item 2. [Item 4] The biological information is heartbeat information during sleep. The information processing system according to any one of items 1 to 3. [Item 5] When the prediction unit includes information on the amount of substances contained in the hair in the mental state information, the prediction unit predicts the amount of substances contained in the future hair of the user, and based on the information on the amount of substances contained in the hair, predicts the mental state of the user. The information processing system according to any one of items 2 to 4. [Item 6] Mental state information acquisition that acquires at least one of the mental state information of the user, including at least objective mental state information and subjective mental state information, A biological signal information acquisition unit that acquires the biological signal information of the user, A prediction unit that predicts the mental state of the user by using a prediction model that takes the biological signal information as input information and the mental state information as output information, An information processing apparatus comprising: [Item 7] Causing a computer to Execute a mental state information acquisition step of acquiring at least one of the mental state information of the user, including at least objective mental state information and subjective mental state information, A biological signal information acquisition step of acquiring the biological signal information of the user, A prediction step of predicting the mental state of the user by using a prediction model that takes the biological signal information as input information and the mental state information as output information, An information processing program. [Item 8] When a computer Executes a mental state information acquisition step of acquiring at least one of the mental state information of the user, including at least objective mental state information and subjective mental state information, A biological signal information acquisition step of acquiring the biological signal information of the user, A prediction step in which the user's psychological state is predicted using a prediction model that takes the aforementioned biosignal information as input information and the aforementioned psychological state information as output information, An information processing method that performs [this action].

[0012] Figure 1 is a diagram showing an example of the overall configuration of an information processing system according to one embodiment of the present invention. The information processing system of this embodiment comprises a server device 1, a user terminal 3, and a sensor terminal 4. The server device 1 is connected to the user terminal 3 and the sensor terminal 4 so as to be able to communicate via a communication network 2. The communication network 2 is, for example, the internet and is constructed using public telephone networks, mobile phone networks, wireless communication channels, Ethernet (registered trademark), etc.

[0013] ==Server Device 1== Server device 1 may be a general-purpose computer such as a workstation or personal computer, or it may be logically implemented through cloud computing. In this embodiment, one unit is shown as an example for the sake of explanation, but it is not limited to this, and there may be multiple units.

[0014] ==User Terminal 3== User terminal 3 is a computer used by the user whose psychological state is being evaluated. User terminal 3 can be, for example, a smartphone, tablet computer, personal computer, or wearable computer. The user can access server device 1 through applications or a web browser running on user terminal 3.

[0015] ==Sensor Terminal 4== Sensor terminal 4 is a computer equipped with a sensor that acquires the user's biosignals. Sensor terminal 4 is, for example, a wearable computer. The sensor may be a biosignal sensor that acquires biometric data such as heart rate, blood pressure, blood glucose levels, and body temperature. Sensor terminal 4 may be, but is not limited to, a wearable device such as Fitbit®.

[0016] The sensor terminal 4 may be connected to the user terminal 3 via the network 2 so as to be able to communicate with it. In this case, the user terminal 3 may acquire the biometric data acquired by the sensor terminal 4 by communicating with it, and further transmit it to the server device 1 via the network 2.

[0017] Figure 2 shows an example of the hardware configuration of server device 1. Note that the illustrated configuration is just one example, and other configurations are also possible. Server device 1 includes a processor 101, memory 102, storage device 103, communication interface 104, input device 105, and output device 106. Storage device 103 stores various data and programs, such as a hard disk drive, solid state drive, or flash memory. Communication interface 104 is an interface for connecting to the communication network 2, such as an adapter for connecting to Ethernet®, a modem for connecting to a public telephone network, a wireless communication device for wireless communication, or a USB (Universal Serial Bus) connector or RS232C connector for serial communication. Input device 105 is for inputting data, such as a keyboard, mouse, touch panel, button, or microphone. Output device 106 is for outputting data, such as a display, printer, or speaker. Furthermore, each functional unit of the server device 1, as 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] Figure 3 shows the functional configuration of the server device 1. As shown in Figure 3, the server device 1 comprises a user information storage unit 131 and a model storage unit 132, as well as processing units 111, 112, 113, 114, 115, and 116.

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

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

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

[0022] The following describes the processing units for the user information acquisition unit 111, the psychological state information acquisition unit 112, the biosignal information acquisition unit 113, the model generation unit 114, the prediction unit 115, and the presentation unit 116.

[0023] The user information acquisition unit 111, for example, acquires or receives user information data from the user terminal 3 via the communication network 2 and stores it in the user information storage unit 131. The communication in this transmission and reception can be wired or wireless, and any communication protocol can be used as long as communication between the two devices is possible.

[0024] The psychological state information acquisition unit 112 acquires psychological state information related to the user's psychological state, as an example, and stores it in the user information storage unit 131.

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

[0026] As an example, the psychological state information acquisition unit 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 unit 131.

[0027] The psychological state information acquisition unit 112 presents the psychological scale to the user terminal 3. The psychological state information acquisition unit 112 accepts the user's input or selection of response information to the psychological scale and acquires subjective psychological state information.

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

[0029] The psychological state information acquisition unit 112, as an example, acquires objective psychological state information relating to the objective psychological state and stores it in the user information storage unit 131. The psychological state information acquisition unit 112 may acquire objective psychological state information from the user terminal 3, or it 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, objective psychological state information includes, for example, information about components obtained by analyzing a biological sample acquired from the user. The objective psychological state information consists of information such as sample type, sample acquisition date, analysis site, contained components, component content, type of pain, and degree of pain.

[0031] In this embodiment, the biological sample is, for example, a protein-based structure that occurs on the user's body surface, and includes, but is not limited to, hair, scalp hair, body hair, nails, and keratin. The biological sample may also be a bodily fluid such as saliva, urine, sweat, or blood.

[0032] In this embodiment, the components contained in the biological sample may include, but are not limited to, proteins, hormones, lipids, steroids, pigments, minerals, nucleic acids, etc.

[0033] The aforementioned components may be, for example, hormones known as stress hormones, and may include, but are not limited to, cortisol (COR), dehydroepiandrosterone (DHEA), testosterone (TTE), estradiol (E2), oxytocin (OT), and serotonin (5-HT).

[0034] The aforementioned analysis sites may, for example, be defined in stages, from the part closest to the skin to the part further away when the biological sample was present on the body surface.

[0035] The analysis site may, for example, be defined by the distance from the hair root when the sample is hair, but is not limited to this.

[0036] For example, if the sample is hair, the analysis site may be defined based on how long it has been since the site was formed, considering that hair grows approximately 1 cm per month on average, based on its distance from the hair root, but it is not limited to this.

[0037] Objective psychological state information may, for example, be information on the amount obtained by extracting stress hormones from the sample using a known pretreatment method and analyzing them using a known method such as ELISA (Enzyme-Linked Immunosorbent Assay) if the biological sample is hair and the component is a stress hormone.

[0038] The biosignal information acquisition unit 113 acquires the user's biosignal information. The biosignal information acquisition unit 113 only needs to acquire the biosignals acquired by the sensor terminal 4 as biosignal information.

[0039] In this embodiment, the biosignal may, for example, be heart rate information. Alternatively, the biosignal may, for example, be heart rate information during sleep. Furthermore, the biosignal may, for example, be the lowest heart rate among the heart rate information during sleep. The heart rate refers to the number of times the heart beats in a certain period of time, and for example, it refers to the number of beats per minute, but is not limited to this. In this case, the biosignal information acquisition unit 113 can group the heart rate data acquired from the sensor terminal 4 into, for example, 10-minute intervals, calculate the median value of each group, and acquire the heart rate obtained by smoothing the median value every minute as heart rate information. Alternatively, the biosignal information acquisition unit 113 may extract the heart rate during sleep from the heart rates smoothed in the manner described above, and further use its lowest value as heart rate information.

[0040] Furthermore, the biosignal in this embodiment may be a numerical value that indexes heart rate information according to a predetermined rule. In this case, the biosignal information acquisition unit 113 acquires information on the lowest heart rate during sleep over a predetermined period, assigns 1 if the lowest heart rate for that day is greater than the average or median, and 0 otherwise, sums the values ​​within the period and divides by the number of days in the predetermined period (hereinafter referred to as the stress index) as the biosignal.

[0041] The model generation unit 114 generates a predictive model that predicts the user's future psychological state based on the information stored in the user information storage unit 131, using statistical methods such as learning, and stores it in the model storage unit 132. The methods used by the model generation unit 114 for generating the predictive model may include classification, regression, correlation analysis, feature importance calculation, and clustering. Furthermore, these statistical models can be implemented using methods commonly used in statistics, and a detailed explanation is omitted here.

[0042] The input data for the predictive model from which relationships can be derived, generated by the model generation unit 114 using these methods, is at least one of either psychological state information or biosignal information.

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

[0044] The model generation unit 114 may generate a predictive model that predicts past psychological state information using input information corresponding to a predetermined period. For example, the model generation unit 114 may use objective psychological state information acquired on day N (information on the amount of stress hormones in the hair, from the root of the hair sample to about 1 cm, i.e., the amount of stress hormones from day N to day (N-30) when the hair sample was acquired), objective psychological state information acquired on day (N+30), and biological signal information from day N to day (N+30) (e.g., a stress index) as training data, and generate a model that takes objective psychological state information acquired on day (N+30) and biological signal information from day N to day (N+30) (e.g., a stress index) as input information, and outputs the amount of stress hormones from day N to day (N-30).

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

[0046] The model generation unit 114 may generate a predictive model that predicts future psychological state information using input information corresponding to a predetermined period. For example, the model generation unit 114 may use objective psychological state information acquired on day (N+30) (information on the amount of stress hormones in the hair, from the root of the hair sample to about 1 cm, i.e., the amount of stress hormones from day N+30 when the hair sample was acquired to day N), objective psychological state information acquired on day N, and biological signal information from (N-30) days prior to day N (e.g., a stress index) as training data, and generate a model that uses objective psychological state information acquired on day N and biological signal information from (N-30) days prior to day N (e.g., a stress index) as input information, and outputs the amount of stress hormones from day N to day (N+30).

[0047] In the example above, the specified period is not limited to 30 days; any period can be set.

[0048] Furthermore, while the above example describes an example where objective psychological state information and biosignal information are used as input information, for example, a predictive model may be generated that uses subjective psychological state information and objective psychological state information as input information and biosignal information as output information, or a predictive model may be generated that uses subjective psychological state information and biosignal information as input information and objective psychological state information as output information.

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

[0050] For 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 can, for example, use a prediction model generated by the model generation unit 114 that predicts objective psychological state information (for example, the amount of stress hormones in the hair) to predict the amount of stress hormones in the hair, and then predict the user's psychological state from that 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] Figure 5 illustrates an example of the processing performed by the evaluation apparatus of this embodiment.

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

[0054] While preferred embodiments of the present disclosure have 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 to any person with ordinary skill in the art of the present disclosure that various modifications or alterations may be conceived within the scope of the technical idea set forth in the claims, and these will naturally also fall within the technical scope of the present disclosure.

[0055] The devices described herein may be implemented as a single device, or they may be implemented by multiple devices (e.g., cloud servers) that are partially or entirely connected by a communication network. For example, the CPU and storage device of server device 1 may be implemented by different servers that are connected to each other by a communication network.

[0056] The series of processes performed by the apparatus described herein may be implemented using software, hardware, or a combination of software and hardware. Computer programs for implementing each function of the server device 1 according to this embodiment can be created and implemented on a PC or the like. Furthermore, a computer-readable recording medium containing such a computer program can also be provided. Examples of recording media include magnetic disks, optical disks, magneto-optical disks, and flash memory. Alternatively, the computer program may be distributed without using a recording medium, for example, via a communication network.

[0057] Furthermore, the processes described herein do not necessarily have to be performed in the order described. Some processing steps may be performed in parallel. Additional processing steps may be employed, and some processing steps may be omitted.

[0058] Furthermore, the effects described herein are merely descriptive or illustrative and not limiting. In other words, the technology relating to this disclosure may produce other effects that will be apparent to those skilled in the art from the description herein, in addition to or in lieu of the effects described herein. [Explanation of Symbols]

[0059] 1 Server device 2. Communication Network 3. User terminals 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 Biosignal Acquisition Unit 114 Model Generation Unit 115 Prediction Section 116 Presentation section 131 User Information Storage Unit 132 Model Memory Unit

Claims

1. A psychological state information acquisition unit that acquires at least one of the user's objective psychological state information and subjective psychological state information, A biosignal information acquisition unit that acquires the user's biosignal information, A prediction unit that predicts the user's psychological state using a prediction model that takes at least the aforementioned biosignal information as input information and the aforementioned psychological state information as output information, An information processing system equipped with the following features.

2. The aforementioned objective psychological state information is information about the amount of substances contained in the hair. The information processing system according to claim 1.

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

4. The aforementioned biosignal information is heart rate information. An information processing system according to any one of claims 1 to 3.

5. The prediction unit predicts the amount of substance in the user's hair in the future when the psychological state information includes information on the amount of substance in the hair, and predicts the user's psychological state based on the information on the amount of substance in the hair. An information processing system according to claim 2 or 3.

6. Psychological state information acquisition, which acquires at least one of the user's objective psychological state information and subjective psychological state information, A biosignal information acquisition unit that acquires the user's biosignal information, A prediction unit predicts the user's psychological state using a prediction model that takes the aforementioned biosignal information as input information and the aforementioned psychological state information as output information. An information processing device equipped with the following features.

7. On the computer, A psychological state information acquisition step that acquires at least one of the user's objective psychological state information and subjective psychological state information, A biosignal information acquisition step for acquiring the biosignal information of the user, A prediction step in which the user's psychological state is predicted using a prediction model that takes the aforementioned biosignal information as input information and the aforementioned psychological state information as output information, An information processing program that executes [something].

8. Computers A psychological state information acquisition step that acquires at least one of the user's objective psychological state information and subjective psychological state information, A biosignal information acquisition step for acquiring the biosignal information of the user, A prediction step in which the user's psychological state is predicted using a prediction model that takes the aforementioned biosignal information as input information and the aforementioned psychological state information as output information, An information processing method that performs [this action].

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