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

Abstract

To provide a wearable device promoting input of information about a subjective emotion.SOLUTION: A wearable device prompts a user wearing the wearable device to input information about a subjective emotion on the basis of a prescribed condition. The information about the subjective emotion is used for labelling related to machine learning of biological data of the user.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

[0002] Patent Document 1 discloses the following techniques 1 and 2. 1. Learning data is generated that represents the association between the acquired information representing the subject's emotions and the information representing the subject's activity state, and is stored in memory. 2. In this state, the subject's current emotion is estimated based on the acquired information representing the subject's current activity state and the learning data stored in the memory. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2019-208576 A Summary of the Invention [Problem to be solved by the invention]

[0004] When generating learning data showing the association between subjective emotions and biometric data, a labeling task is required to assign correct subjective emotions to the biometric data. Patent Document 1 does not disclose how to input the subjective emotions involved in labeling. [Means for solving the problem]

[0005] According to one aspect of the present invention, there is provided a wearable device that prompts a user wearing the wearable device to input information about a subjective emotion based on a predetermined condition, and the information about the subjective emotion is used for labeling the biometric data of the user in machine learning. [Brief description of the drawings]

[0006] [Figure 1] FIG. 1 is a diagram illustrating an example of a wearable device. [Diagram 2] FIG. 2 is a diagram illustrating an example of the hardware configuration of the smart watch 100. [Diagram 3] FIG. 3 is a flowchart showing an example of information processing in the smart watch 100. [Figure 4] FIG. 4 shows an example of screen transition related to input of subjective emotion information displayed on input / output section 250. As shown in FIG. [Diagram 5] FIG. 5 is a diagram showing an example of the timing of recording of subjective emotion information superimposed on a time series graph of acceleration data of the smart watch 100. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described with reference to the drawings. Various characteristic features shown in the following embodiments can be combined with each other.

[0008] In this specification, the term "unit" may include, for example, a combination of hardware resources implemented by a circuit in the broad sense and software information processing that can be specifically realized by these hardware resources. In addition, various information is handled in this embodiment, and communication and calculation can be performed on a circuit in the broad sense regardless of whether this information is represented by a high or low signal value as a binary bit collection consisting of 0 or 1, represented by a physical numerical value of a signal value, or represented by quantum superposition.

[0009] In addition, a circuit in the broad sense is a circuit realized by at least appropriately combining a circuit, circuitry, a processor, a memory, etc. In other words, it includes an application specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)), etc.

[0010] In addition, the program for realizing the software appearing in the embodiments may be implemented in a form that is downloadable from a server, the program may be executed on a cloud computer, or the program may be stored in a non-volatile or volatile non-transitory storage medium and distributed.

[0011] <Embodiment 1> 1. System Configuration Fig. 1 is a diagram showing an example of a wearable device. As shown in Fig. 1, in this specification, a smart watch 100 is taken as an example of a wearable device. However, a smart watch is only an example of a wearable device, and other examples of the wearable device may be, for example, a fitness tracker, smart glasses, a vital sign monitor, a smart ring, a badge-type wearable device, and the like. As will be described later, any wearable device may be used as long as it can prompt a user to input information related to subjective emotions (hereinafter, referred to as subjective emotion information).

[0012] Here, the information processing system described in the claims may be composed of multiple devices or may be composed of one device. When the information processing system described in the claims is composed of one device, an example of the device is the smart watch 100. When the information processing system described in the claims is composed of multiple devices, an example of the multiple devices is the smart watch 100 and a server device capable of communicating with the smart watch 100, or the smart watch 100 and a cloud system capable of communicating with the smart watch 100, etc.

[0013] 2. Hardware Configuration 2 is a diagram showing an example of the hardware configuration of the smartwatch 100. The smartwatch 100 includes, as its hardware configuration, a control unit 210, a storage unit 220, a biological data measurement unit 230, an acceleration measurement unit 240, an input / output unit 250, and a communication unit 260.

[0014] The control unit 210 is a CPU (Central Processing Unit) or the like, and controls the smart watch 100 as a whole.

[0015] The storage unit 220 is any one of a ROM (Read Only Memory), a RAM (Random Access Memory), and an SSD (Solid State Drive), or any combination thereof, and stores a program and data used when the control unit 210 executes processing based on the program. The control unit 210 executes processing based on the program stored in the storage unit 220, thereby realizing the functions of the smartwatch 100 and the processing of the flowchart shown in FIG. 3 described later. The storage unit 220 is an example of a storage medium. Note that in this embodiment, the data used when the control unit 210 executes processing based on the program is described as being stored in the storage unit 220, but the data may be stored in a storage unit of another device that can communicate with the smartwatch 100. In other words, the data may be stored in a storage unit of any device as long as the control unit 210 can refer to the data.

[0016] The biological data measurement unit 230 measures biological data of the user of the smart watch 100. Examples of biological data measured by the biological data measurement unit 230 include heart rate, pulse, blood pressure, oxygen concentration, skin temperature, and skin potential. The acceleration measurement unit 240 measures the acceleration of the smart watch 100.

[0017] The input / output unit 250 is a touch panel display or the like, which displays information, accepts user operations, and selects or inputs information in response to the user operations. The communication unit 260 connects the smartwatch 100 to a network or the like, and is responsible for communication with other devices and the like.

[0018] 3. Information Processing The information processing according to this embodiment will be described below.

[0019] FIG. 3 is a flowchart showing an example of information processing in the smart watch 100. In step S301, the control unit 210 acquires biometric data of the user who is wearing the smart watch 100. It is assumed that the process of step S301 is always executed while the smart watch 100 is activated.

[0020] In step S302, the control unit 210 determines whether or not a predetermined condition is satisfied. For example, the control unit 210 determines whether or not the biometric data satisfies a predetermined condition. For example, the control unit 210 determines whether or not the heart rate is 60 to 100 beats / minute. If the heart rate is 60 to 100 beats / minute, the control unit 210 determines that the biometric data satisfies the predetermined condition. If the heart rate is not 60 to 100 beats / minute, the control unit 210 determines that the biometric data does not satisfy the predetermined condition. If the control unit 210 determines that the biometric data satisfies the predetermined condition, the control unit 210 advances the process to step S303. If the control unit 210 determines that the biometric data does not satisfy the predetermined condition, the control unit 210 returns the process to step S301. The heart rate is an example, and it may be determined whether or not the predetermined condition is satisfied based on the pulse, blood pressure, oxygen concentration, skin temperature, skin potential, etc.

[0021] In step S303, the control unit 210 controls the input / output unit 250 to display a screen that prompts the input of subjective emotion information. The control unit 210 also controls the transition of the screen displayed on the input / output unit 250. That is, the control unit 210 prompts the user wearing the smart watch 100 to input information related to subjective emotion based on a predetermined condition. As described later, the information related to subjective emotion is used for labeling related to machine learning of the user's biometric data. The subjective emotion information described later is an example of information related to subjective emotion. More specifically, the control unit 210 prompts the user to input information related to subjective emotion based on the fact that the biometric data satisfies a predetermined condition. The control unit 210 prompts the user to input information related to subjective emotion by displaying a screen related to the input of subjective emotion information (for example, FIG. 4(b), FIG. 4(c), and FIG. 4(d)) on the wearable device. Fig. 4 is a diagram showing an example of a screen transition related to the input of subjective emotion information displayed on the input / output unit 250. Fig. 4(a) is a diagram showing an example of a screen displayed on the input / output unit 250 when the smart watch 100 is operating in watch mode. The screen shown in Fig. 4(a) is displayed on the input / output unit 250 as a main screen. Most of the time when the smart watch 100 is running, the main screen is displayed on the input / output unit 250. In steps S301 and S302, the screen shown in Fig. 4(a) is displayed on the input / output unit 250.

[0022] Fig. 4(b) is a diagram showing an example of a joy, anger, sadness, and happiness selection screen. The screen in Fig. 4(b) is a screen displayed on the input / output unit 250 in step S303. On the joy, anger, sadness, and happiness selection screen, the user can select one of the four categories of joy, anger, sadness, and happiness as a category of subjective emotions. Note that the types of categories are merely an example and are not limited to four. Furthermore, the way of dividing the categories is not limited to joy, anger, sadness, and happiness.

[0023] When the user selects one of the four categories on the screen of Fig. 4(b), the control unit 210 transitions the screen displayed on the input / output unit 250 from Fig. 4(b) to Fig. 4(c). Fig. 4(c) is a diagram showing an example of an emotion type selection screen. On the emotion type selection screen, the user can select one emotion type from multiple emotion types included in the category selected on the joy, anger, sadness, and pleasure selection screen.

[0024] When joy is selected as the category on the screen of FIG. 4(b), the control unit 210 displays a selection item on the screen of FIG. 4(c) so that one emotion type can be selected from four emotion types: happiness, energy, excitement, and caution. When anger is selected as the category on the screen of FIG. 4(b), the control unit 210 displays a selection item on the screen of FIG. 4(c) so that one emotion type can be selected from four emotion types: tension, nervousness, pressure, and worry. When sadness is selected as the category on the screen of FIG. 4(b), the control unit 210 displays a selection item on the screen of FIG. 4(c) so that one emotion type can be selected from four emotion types: sadness, depression, lethargy, and fatigue. When comfort is selected as the category on the screen of FIG. 4(b), the control unit 210 displays a selection item on the screen of FIG. 4(c) so that one emotion type can be selected from four emotion types: calm, relaxation, tranquility, and satisfaction. The emotion types included in each category are examples.

[0025] When the user selects an emotion type on the screen of FIG. 4(c), the control unit 210 transitions the screen displayed on the input / output unit 250 from FIG. 4(c) to FIG. 4(d). FIG. 4(d) is a diagram showing an example of an emotion level selection screen. On the emotion level selection screen, the user can select the level of the emotion selected on the emotion type selection screen. For example, the user can select emotion level 1 to emotion level 4 via the screen shown in FIG. 4(d). Emotion level 1 is the lowest emotion level, and emotion level 4 is the highest emotion level.

[0026] When the registration button is selected on the screen shown in Fig. 4(d) and an emotion level is registered, the control unit 210 controls the screen transition to return the screen to Fig. 4(b). Then, if there is no input for M seconds (e.g., 30 seconds) after returning to the screen of Fig. 4(b), the control unit 210 controls the screen transition to return the screen to the clock mode display of Fig. 4(a). The control unit 210 may not transition from the screen of Fig. 4(a) to the screen of Fig. 4(b) for a certain period of time (e.g., 600 seconds) after the screen returns to the display of Fig. 4(a). By performing such processing, the load of inputting information related to subjective emotions can be reduced.

[0027] The control unit 210 may allow the selection of no emotion in addition to joy, anger, sadness, and happiness on the screen shown in Fig. 4(b). When no emotion is selected, the control unit 210 does not transition the screen from Fig. 4(b) to Fig. 4(c) or Fig. 4(d), etc., but automatically selects and sets emotion level 1. However, for the sake of simplicity, the following description will be given assuming that the screen transitions from Fig. 4(b) → Fig. 4(c) → Fig. 4(d) and that the category, emotion type, and emotion level are selected.

[0028] In step S304 in Fig. 3, the control unit 210 determines whether or not a category, emotion type, and emotion level have been selected (or input) on a screen such as that shown in Fig. 4. If the control unit 210 determines that a category, emotion type, and emotion level have been selected, it advances the process to step S305. If the control unit 210 determines that a category, emotion type, and emotion level have not been selected, it returns the process to step S303.

[0029] In step S305, the control unit 210 sets the category, emotion type, and emotion level selected via the screen as shown in FIG. 4 as subjective emotion information. In step S306, control unit 210 generates learning data by associating the input subjective emotion information with biometric data of the user wearing the wearable device. The biometric data associated with the subjective emotion information is data related to the timing at which the subjective emotion information was input (for example, the timing at which a category was selected in FIG. 4(b), or the timing at which an emotion level was selected in FIG. 4(d)). In step S307, the control unit 210 stores the generated learning data in the storage unit 220 or the like.

[0030] In step S308, control unit 210 determines whether or not to end the process of the flowchart shown in Fig. 3. When control unit 210 determines to end the process of the flowchart shown in Fig. 3, it ends the process of the flowchart shown in Fig. 3. When control unit 210 determines not to end the process of the flowchart shown in Fig. 3, it returns the process to step S301.

[0031] According to the process of this embodiment, the smartwatch 100 prompts the user to input information related to subjective emotions, so that the user can input information related to subjective emotions to the smartwatch 100 at an appropriate time. The input information related to subjective emotions is then labeled as a correct answer label related to the biometric data of the user measured by the smartwatch 100. The subjective emotion information to which the correct answer label has been assigned is used for supervised machine learning of the biometric data.

[0032] (Variation 1) A first modification of the first embodiment will be described. In the first embodiment, an example of the predetermined condition in step S302 is described in terms of whether the biometric data of the user satisfies the predetermined condition. In the first modification, as another example of the predetermined condition, a description will be given of whether or not biometric data arranged in chronological order satisfies a predetermined condition.

[0033] The control unit 210 of the first modification (hereinafter, simply referred to as the control unit 210) prompts the user to input information related to subjective feelings based on the fact that the first biometric data and the second biometric data of the user acquired at different times satisfy a predetermined condition. For example, if the blood pressure measured at the first time is 115 / 75 mmHg or less and the blood pressure measured at the second time after the first time is also 115 / 75 mmHg or less after a predetermined number of seconds (e.g., 15 seconds) have elapsed, the control unit 210 determines that the biometric data satisfies the predetermined condition. If the blood pressure measured at the first time is not 115 / 75 mmHg or less or the blood pressure measured at the second time is not 115 / 75 mmHg or less, the control unit 210 determines that the biometric data does not satisfy the predetermined condition.

[0034] That is, in the first modification, the control unit 210 may prompt the user to input information related to a subjective feeling when the biological data arranged in chronological order satisfies a predetermined condition.

[0035] According to the first modification, when the biometric data satisfies a predetermined condition for a certain period of time, the user can be prompted to input information related to subjective feelings.

[0036] (Variation 2) A second modification of the first embodiment will now be described. In the first embodiment, an example of the predetermined condition in step S302 is described in terms of whether the biometric data of the user satisfies the predetermined condition. In the second modification, as another example of the predetermined condition, a description will be given of whether the acceleration of the smart watch 100 measured by the acceleration measuring unit 240 satisfies the predetermined condition.

[0037] The control unit 210 of the second modification (hereinafter, simply referred to as the control unit 210) acquires the acceleration of the smart watch 100 measured by the acceleration measuring unit 240. Then, the control unit 210 determines whether or not the acceleration satisfies a predetermined condition. If the acceleration satisfies the predetermined condition (for example, the acceleration value is within a set range), the control unit 210 prompts the user to input information related to a subjective feeling.

[0038] According to the second modification, when the acceleration satisfies a predetermined condition, the user can be prompted to input information related to the subjective feeling.

[0039] (Variation 3) A third modification of the first embodiment will now be described. In the first embodiment, an example of the predetermined condition in step S302 is described in terms of whether the biometric data of the user satisfies the predetermined condition. In the third modification, as another example of the predetermined condition, an explanation will be given of whether the acceleration of the smart watch 100 measured by the acceleration measuring unit 240 and arranged in order of time satisfies the predetermined condition.

[0040] The control unit 210 of the third modified example (hereinafter, simply referred to as the control unit 210) prompts the user to input information related to a subjective feeling based on the fact that the first acceleration data and the second acceleration data related to the smart watch 100 acquired at different timings satisfy a predetermined condition. For example, when the acceleration value measured at the first timing is within a set range, and the acceleration value measured at the second timing after a predetermined number of seconds (e.g., 10 seconds) have elapsed since the first timing is also within the set range, the control unit 210 determines that the acceleration satisfies the predetermined condition.

[0041] Fig. 5 is a diagram showing an example of the timing of recording subjective emotion information superimposed on a time-series graph of acceleration data of the smart watch 100. In the example of Fig. 5, when it is determined based on the acceleration data of the smart watch 100 that the stationary state of the smart watch 100 has continued for a certain period of time (e.g., 50 seconds), the user is prompted to input information related to the subjective emotion, and the information related to the subjective emotion is recorded.

[0042] According to the third modification, when the acceleration satisfies a predetermined condition for a certain period of time, the user can be prompted to input information related to a subjective feeling.

[0043] (Variation 4) A fourth modification of the first embodiment will now be described. In the first embodiment, the smart watch 100 is described as performing the processing. However, the information processing system acquires biometric data of the user wearing the smart watch 100. Then, the information processing system prompts the user wearing the smart watch 100 to input information related to subjective emotions based on a predetermined condition. Then, the information processing system may associate the input information related to subjective emotions with the biometric data of the user wearing the smart watch 100 and store them as learning data in a predetermined storage unit or the like. The biometric data associated with the information related to subjective emotions and stored as learning data is data related to the timing at which the information related to subjective emotions was input. As described above, the information processing system may be composed of multiple devices or may be composed of one device. When the information processing system is composed of one device, an example of the device is the smart watch 100. In such a configuration, variant example 4 is the same as embodiment 1. When the information processing system is composed of multiple devices, an example of the multiple devices is the smart watch 100 and a server device capable of communicating with the smart watch 100, or the smart watch 100 and a cloud system capable of communicating with the smart watch 100, etc.

[0044] The fourth modification can achieve the same effects as the first embodiment described above.

[0045] Furthermore, it may be provided in the following aspects:

[0046] (1) A wearable device that prompts a user wearing the wearable device to input information regarding subjective emotions based on predetermined conditions, and the information regarding the subjective emotions is used for labeling the user's biometric data for machine learning.

[0047] (2) A wearable device as described in (1) above, which acquires biometric data of a user wearing the wearable device, and prompts the user to input information regarding subjective emotions based on the biometric data satisfying a specified condition.

[0048] (3) A wearable device as described in (2) above, which prompts the user to input information regarding subjective emotions based on the first biometric data and second biometric data of the user acquired at different times satisfying the specified condition.

[0049] (4) A wearable device as described in (1) above, which acquires acceleration data relating to the wearable device, and prompts the user to input information relating to a subjective emotion based on the acceleration data satisfying the specified condition.

[0050] (5) A wearable device as described in (4) above, which prompts the user to input information regarding subjective emotions based on first acceleration data and second acceleration data regarding the wearable device acquired at different times satisfying the specified condition.

[0051] (6) A wearable device according to any one of (1) to (5) above, which prompts the user to input information regarding the subjective emotion by displaying a screen for inputting information regarding the subjective emotion on the wearable device.

[0052] (7) A wearable device according to any one of (1) to (6) above, which acquires biometric data of a user wearing the wearable device, associates the input information relating to the subjective emotion with the biometric data of the user wearing the wearable device and stores the associated information as learning data, and the biometric data associated with the information relating to the subjective emotion and stored as the learning data is data relating to the timing at which the information relating to the subjective emotion was input.

[0053] (8) An information processing system which acquires biometric data of a user wearing a wearable device, prompts the user wearing the wearable device to input information related to subjective feelings based on predetermined conditions, associates the input information related to the subjective feelings with the biometric data of the user wearing the wearable device and stores it as learning data, and the biometric data associated with the information related to the subjective feelings and stored as the learning data is data related to the timing when the information related to the subjective feelings was input.

[0054] (9) An information processing method executed by a wearable device, which prompts a user wearing the wearable device to input information regarding subjective emotions based on predetermined conditions, and the information regarding the subjective emotions is used for labeling related to machine learning of the user's biometric data.

[0055] (10) A program for causing a computer to function as a wearable device according to any one of (1) to (7) above. Of course, this is not the case.

[0056] For example, the above-described embodiments and modifications may be implemented in any combination. In the above-mentioned first embodiment and the modified examples, the device for acquiring biometric data and the device for prompting the input of information related to subjective feelings may be separate devices.

[0057] Finally, although various embodiments of the present invention have been described, these are presented as examples and are not intended to limit the scope of the invention. The new embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. The embodiments and their modifications are within the scope and spirit of the invention, and are included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0058] 100: Smartwatch 210: Control section 220: Storage section 230: Biological data measurement section 240: Acceleration measurement unit 250: Input / output section 260: Communications Department

Claims

1. A wearable device, Prompting a user wearing the wearable device to input information regarding a subjective emotion based on a predetermined condition; The information regarding the subjective emotions is used for machine learning labeling of the biometric data of the user. Wearable devices.

2. The wearable device according to claim 1 , Collect biometric data from the user wearing the wearable device, prompting the user to input information regarding a subjective emotion based on the biometric data satisfying the predetermined condition; Wearable devices.

3. The wearable device according to claim 2, prompting the user to input information regarding a subjective feeling based on the first biometric data and the second biometric data of the user acquired at different times satisfying the predetermined condition; Wearable devices.

4. The wearable device according to claim 1 , acquiring acceleration data relating to the wearable device; prompting the user to input information regarding a subjective feeling based on the acceleration data satisfying the predetermined condition; Wearable devices.

5. The wearable device according to claim 4, prompting the user to input information regarding a subjective feeling based on the first acceleration data and the second acceleration data regarding the wearable device acquired at different times satisfying the predetermined condition; Wearable devices.

6. The wearable device according to claim 1 , prompting the user to input information regarding the subjective feeling by displaying a screen related to input of information regarding the subjective feeling on the wearable device; Wearable devices.

7. The wearable device according to claim 1 , Collect biometric data from the user wearing the wearable device, The input information regarding the subjective emotion is associated with biometric data of a user wearing the wearable device and stored as learning data; The biometric data associated with the information on the subjective emotion and stored as the learning data is data related to a timing at which the information on the subjective emotion was input. Wearable devices.

8. An information processing system, Collect biometric data from the user wearing the wearable device, Prompting a user wearing the wearable device to input information regarding a subjective emotion based on a predetermined condition; The input information regarding the subjective emotion is associated with biometric data of a user wearing the wearable device and stored as learning data; The biometric data associated with the information on the subjective emotion and stored as the learning data is data related to a timing at which the information on the subjective emotion was input. Information processing system.

9. An information processing method executed by a wearable device, comprising: Prompting a user wearing the wearable device to input information regarding subjective emotions based on a predetermined condition; The information regarding the subjective emotions is used for machine learning labeling of the biometric data of the user. Information processing methods.

10. A program, Computer, A program for causing a wearable device to function as the wearable device according to any one of claims 1 to 7.

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