Environmental control system and program

Abstract

This environment control system (200) comprises: a biological information acquisition unit (101) which acquires biological information; a mental estimation unit (102) which estimates a mental estimation value of a user (99) on the basis of the biological information; an intervention stimulus unit (a stimulus condition determination unit (104) and a stimulus device (400)) which imparts an intervention stimulus according to stimulus conditions; and an intervention stimulus effect database (103) which is referenced when the stimulus conditions are determined, wherein, in the intervention stimulus effect database (103), variation information, which represents a variation in the estimation value after the intervention stimuli are respectively imparted according to two or more stimulus conditions, is stored in association with the stimulus condition when the corresponding intervention stimulus is imparted, and the stimulus condition includes the intensity of the intervention stimulus and a prescribed threshold value which is set for the estimation value, the intervention stimulus being imparted at the timing when the estimation value crosses over the prescribed threshold value.

Description

[Technical field]

[0001] The present invention relates to an environmental control system, an environmental control method, and a program. [Background technology]

[0002] Patent Document 1 discloses a psychological state evaluation device that can accurately evaluate the psychological state (in other words, a certain mental state) of a target person. Patent Document 2 discloses an air conditioner that can further improve the effect of improving the feeling of heating and cooling when the feeling of heating and cooling is given as an intervention stimulus. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 5828111 [Patent Document 2] Patent No. 4986670 Summary of the Invention [Problem to be solved by the invention]

[0004] By the way, when estimating a mental state and providing an intervention stimulus to improve the estimated value, it is known that the improvement effect varies from person to person even if the conditions of the intervention stimulus (stimulation conditions) are the same. Therefore, the present invention provides an environmental control system and the like for providing an intervention stimulus that is more optimized for each individual. [Means for solving the problem]

[0005] An environmental control system according to one embodiment of the present invention comprises a bioinformation acquisition unit that acquires bioinformation regarding a user's bioactivity, a mental estimation unit that estimates an estimated value indicating the mental state of the user at the time the bioinformation was acquired based on the acquired bioinformation, an intervention stimulation unit that gives an intervention stimulus to the user according to stimulation conditions, and an intervention stimulation effect database that is referenced when the intervention stimulation unit determines the stimulation conditions for giving the intervention stimulus, wherein the intervention stimulation effect database stores change information indicating changes in the estimated value after the intervention stimulus is given according to each of two or more stimulation conditions, at least one of which is different from the other stimulation conditions, in association with the stimulation condition at the time the intervention stimulus was given, and the stimulation condition includes the intensity of the intervention stimulus and a predetermined threshold value set for the estimated value, where the intervention stimulus is given when the estimated value changes and crosses the predetermined threshold value.

[0006] An environmental control method according to one embodiment of the present invention is an environmental control method executed using a computer, which acquires bioinformation regarding a user's bioactivity, estimates an estimated value indicating the mental state of the user at the time the bioinformation was acquired based on the acquired bioinformation, and provides the user with an intervention stimulus according to stimulation conditions determined by referring to an intervention stimulation effect database, in which change information indicating changes in the estimated value after the intervention stimulus was provided according to each of two or more stimulation conditions, at least one of which is different from the other stimulation conditions, is stored in the intervention stimulation effect database in association with the stimulation condition at the time the intervention stimulus was provided, and the stimulation conditions include the intensity of the intervention stimulus and a predetermined threshold set for the estimated value, at which the intervention stimulus is provided when the estimated value changes and crosses the predetermined threshold.

[0007] A program according to one aspect of the present invention is a program for causing a computer to execute the above-described environmental control method. Effect of the Invention

[0008] According to the environmental control system etc. of the present invention, it is possible to provide intervention stimuli that are more optimized for each individual. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram for explaining a use case of an environmental control system according to an embodiment. [Diagram 2] FIG. 2 is a graph for explaining the effect of maintaining the alertness in a space provided with the environmental control system according to the embodiment and in a space according to a comparative example. [Diagram 3] FIG. 3 is a block diagram showing a functional configuration of the environmental control system according to the embodiment. [Figure 4] FIG. 4 is a first diagram for explaining the intervention stimulus effect database according to the embodiment. [Diagram 5] FIG. 5 is a second diagram for explaining the intervention stimulus effect database according to the embodiment. [Figure 6] FIG. 6 is a diagram showing an example of comparison information output in the embodiment. [Figure 7] FIG. 7 is a flowchart of an operation example of the environmental control system according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] (Findings on which the present invention is based) Improving employee productivity has become an issue due to factors such as a decline in the working population and work style reforms. Increasing employee motivation and improving office space are also important factors in improving productivity. A comfortable office space helps to reduce stress, maintain health, and maintain motivation, which are thought to lead to improved productivity. In other words, attention is being paid to improving the mental state of the user, including one or more of the user's comfort, alertness, concentration, relaxation, communication, and creativity, as described above.

[0011] On the other hand, to create a comfortable space, it is not enough to simply use air conditioning to control the temperature and lighting to ensure the brightness required for work. There are many factors related to air conditioning alone that affect the environment. To create a good space, it is necessary to control the stimuli for employees' five senses, including hearing, touch, smell, and even taste in some cases.

[0012] Incidentally, in order to improve the mental state of a user, it is necessary to provide the above-mentioned intervention stimulus, but the provision of the intervention stimulus may be effective for some users but not others, and depending on the situation, an intervention stimulus that can improve the mental state of one user may have an adverse effect on another user. Therefore, in the present invention, an environmental control system for providing an appropriate intervention stimulus for each user will be described. In other words, according to the environmental control system of the present invention, an intervention stimulus that is more optimized for each individual can be provided.

[0013] Hereinafter, embodiments based on such findings will be specifically described with reference to the drawings. Note that the embodiments described below are all comprehensive or specific examples. The numerical values, shapes, materials, components, component arrangement and connection forms, steps, and order of steps shown in the following embodiments are merely examples and are not intended to limit the present invention. Furthermore, among the components in the following embodiments, components that are not described in the independent claims will be described as optional components.

[0014] In addition, each drawing is a schematic diagram and is not necessarily a precise illustration. In addition, in each drawing, the same reference numerals are used for substantially the same configuration, and duplicated explanations may be omitted or simplified.

[0015] (Embodiment) [composition] First, a use case of the environmental control system according to the embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram for explaining a use case of the environmental control system according to the embodiment.

[0016] With the recent diversification of work styles, an increasing number of companies are adopting individual work booths (private booths), as shown in Figure 1. In such private booths, users 99 can work on their own tasks. In such private booths, it is possible to control the spatial environment according to each user 99 using the booth, making it possible to provide a space suitable for each individual.

[0017] Here, Fig. 2 is a graph for explaining the effect of maintaining the alertness in a space equipped with an environmental control system according to the embodiment and a space according to a comparative example. In Fig. 2, the solid line indicates the transition of the alertness of the user 99 in the space equipped with the environmental control system, and the dashed line indicates the transition of the alertness of the user 99 in a space according to a comparative example (a space in which an intervention stimulus tailored to the user is not given in particular). Note that, before the timing indicated by the circle at which the first intervention stimulus is given, the alertness of the user 99 transitions in the same way (overlaps) in both spaces.

[0018] For example, in the space according to the comparative example, since no intervention stimulus is given to improve the user 99's level of alertness at the timing of the circle, it is expected that the level of alertness will continue to decrease without increasing. On the other hand, in the space equipped with the environmental control system, an intervention stimulus is given to improve the level of alertness when the level of alertness of the user 99 crosses a preset threshold, so that the level of alertness then starts to increase. Even if the level of alertness decreases again thereafter, an intervention stimulus is given to improve the level of alertness each time the threshold is crossed, so that the user 99 can maintain a state in which the level of alertness is high on average. As a result, it is expected that the productivity of the user 99's tasks will be increased compared to the case of the space according to the comparative example.

[0019] Examples of intervention stimuli for improving the level of alertness include changing the brightness of lighting and releasing a mint scent into the space. Incidentally, with regard to the threshold value for the system to determine that the level of alertness has decreased, for example, depending on the user 99, the timing of providing the intervention stimulus may be delayed, and the expected effect of improving the level of alertness may not be obtained. Similarly, releasing a mint scent into the space as a type of intervention stimulus may wake the user 99 in an unpleasant direction, due to the user's dislike of mint scent in the first place, and may have a counterproductive effect in terms of the user's productivity. Furthermore, as for the intensity of the intervention stimulus, some users 99 experience an increase in their level of alertness with high-intensity lighting, while others experience an increase in their level of alertness with soft lighting, so the intensity of the intervention stimulus cannot be determined in general.

[0020] In this way, even if the mental state of the user 99 is simply improved by an intervention stimulus, it is presumed that three elements, namely, the timing of providing the intervention stimulus (in other words, the threshold value for the estimated mental state), the strength of the intervention stimulus, and the type of intervention stimulus, differ from person to person. In the environmental control system of the present invention, it is possible to provide an intervention stimulus that is optimized for an individual with respect to these three elements. Note that, although an example of optimizing these three elements will be described below, for example, it is also possible to optimize only two elements, the timing of providing the intervention stimulus and the strength of the intervention stimulus, for an individual.

[0021] In the above example, the mental state is described using the level of alertness as an example of the mental state, but the mental state may include at least one of the comfort level, alertness level, concentration level, relaxation level, communication level, and creativity of the user 99. The estimation of the mental state for each of these mental examples will be described later.

[0022] Hereinafter, the functional configuration of the environmental control system will be described with reference to Fig. 3. Fig. 3 is a block diagram showing the functional configuration of the environmental control system according to the embodiment. As shown in Fig. 3, the environmental control system 200 includes an environmental control device 100, a measuring device 300, a stimulating device 400, and a display device 500.

[0023] The environmental control device 100 is a device that acquires bioinformation to estimate the mental state of the user 99, estimates an estimated mental value from the acquired bioinformation, and determines the timing of providing an intervention stimulus according to the estimated mental value. Furthermore, the environmental control device 100 determines information including the intensity of the intervention stimulus to be provided and the type of intervention stimulus as a stimulus condition in addition to the timing of providing the intervention stimulus described above, and generates and outputs control information so that the intervention stimulus according to the stimulus condition is provided. The environmental control device 100 also has a function for explaining that the intervention stimulus is individually optimized, and for the user 99 to confirm the individually optimized information and then edit the information.

[0024] The following describes the detailed configuration of the environmental control device 100. The environmental control device 100 is implemented and realized in a computer device including, for example, a cloud server or an edge server. More specifically, the environmental control device 100 is realized by executing a predetermined program using a processor and memory provided in the computer device.

[0025] The environment control device 100 includes a biological information acquisition unit 101 , a mental state estimation unit 102 , an intervention stimulus effect database 103 , a stimulus condition determination unit 104 , and an output unit 105 .

[0026] The biometric information acquisition unit 101 is a processing unit that is connected to the measurement device 300 and acquires the biometric information of the user 99 measured by the measurement device 300 via a communication line. The biometric information acquisition unit 101 outputs the acquired biometric information to the mental state estimation unit 102. Therefore, the biometric information acquisition unit 101 also has a function of converting the acquired biometric information into a format that can be processed by the mental state estimation unit 102.

[0027] The measuring device 300 is a wristband-type sensing device for measuring pulse waves, blood pressure, heart rate, etc., an ear-hook-type sensing device for measuring brain waves and pulse waves near the auricle, and a non-contact sensing device such as a microphone for picking up sound or a camera for capturing images. In addition, the measuring device 300 can be used in the present invention without any particular limitations as long as it is a device configured to be able to measure all kinds of biological information that can be used to estimate the mental state described below.

[0028] The mental state estimation unit 102 is a processing unit that estimates an estimated value indicating a mental state based on biological information. Some examples of the mental state estimation by the mental state estimation unit 102 will be described.

[0029] The alertness and concentration of the user 99 are estimated as numerical values ​​through bioindicators such as sympathetic nerve activity index, hypothalamic activity, brain waves (particularly β waves), and cerebral blood flow. For this purpose, for example, heart rate, blood pressure, blood vessel diameter (blood flow), respiratory rate, bronchi contraction degree, pupil constriction degree, blood glucose level, insulin amount, digestive juice secretion promotion degree in the digestive tract such as the stomach, saliva amount, voice tone, voice speed, nasal temperature, and brain waves (β waves) are acquired as bioinformation from the measurement device 300. Then, the above bioindicators are calculated using a calculation function obtained empirically or experimentally.

[0030] The comfort level and relaxation level of the user 99 are estimated as numerical values ​​through bioindicators such as parasympathetic nerve activity index, hypothalamic activity (autonomic nervous system activity), insula (meditation), brain waves (particularly alpha waves), and cerebral blood flow. For this purpose, for example, heart rate, blood pressure, blood vessel diameter (blood flow), respiratory rate, bronchi contraction degree, pupil constriction degree, blood glucose level, insulin amount, digestive juice secretion promotion degree in the digestive tract such as the stomach, saliva amount, fingertip temperature, voice tone, voice speed, nasal temperature, and brain waves (alpha waves) are acquired as bioinformation from the measurement device 300. Then, the above bioindicators are calculated using a calculation function obtained empirically or experimentally.

[0031] The communication level of the user 99 is estimated as a numerical value through bioindicators such as the number of utterances and the activity of facial muscles. For this purpose, for example, tone of voice, speed of voice, facial expression image, and facial myoelectric potential are acquired as bioinformation from the measurement device 300. Then, the bioindicators are calculated using a calculation function obtained empirically or experimentally.

[0032] The creativity of the user 99 is estimated as a numerical value through bioindicators such as facial muscle activity and cerebral blood flow. For this purpose, for example, facial expression images, facial myoelectric potential, and blood vessel diameter (blood flow rate) are acquired as bioinformation from the measurement device 300. Then, the above bioindicators are calculated using a calculation function obtained empirically or experimentally.

[0033] In addition, since the estimated mental state used below is used to compare the effectiveness of the intervention stimulation between two or more stimulation conditions, any estimation method by the mental estimation unit 102 may be used as long as it has a certain degree of reproducibility.

[0034] The intervention stimulus effect database 103 is a storage device that stores information to be referenced when determining the stimulus conditions. The intervention stimulus effect database 103 stores change information indicating a change in the estimated value of the mental state after each intervention stimulus is given according to two or more stimulus conditions, at least one of which is different from the other stimulus conditions, in association with the stimulus condition when the intervention stimulus was given.

[0035] Fig. 4 is a first diagram for explaining the intervention stimulus effect database according to the embodiment. Fig. 5 is a second diagram for explaining the intervention stimulus effect database according to the embodiment. Fig. 4 illustrates an example in which the mental state is the alertness of a user 99. Fig. 4 illustrates the relationship between the intensity of the intervention stimulus and the effect of improving the alertness by providing the intervention stimulus in a combination of a predetermined threshold value which is the timing at which the intervention stimulus is provided.

[0036] In the example of Fig. 4, when the timing of providing the intervention stimulus is changed within a range of plus or minus α around the standard threshold, it is shown that it is effective to provide the intervention stimulus at a threshold lower than the standard threshold, that is, in a situation where the arousal level is lower than the standard case (white arrow in the figure). In addition, it is shown that it is effective to provide a relatively strong intervention stimulus as the strength of the intervention stimulus.

[0037] The information stored in this intervention stimulus effect database 103 is constructed from records (past estimated values) of intervention stimuli given to the user 99 in the past and how the estimated mental value changed at that time. Therefore, if a sufficient amount of information is stored in this intervention stimulus effect database 103, it is possible to estimate a more appropriate intervention stimulus strength and timing (predetermined threshold value) for the user 99, and it becomes possible to give a more individually optimized intervention stimulus.

[0038] A method for estimating the improvement effect of the mental state of the user 99 with respect to an intervention stimulus given to the user 99 in the past will be described. As shown in FIG. 5, when the estimated mental value (here, the degree of awakening) of the user 99 falls from a value higher than the standard threshold plus α to a value lower than the standard threshold plus α (in this case, the higher the estimated value, the better the mental state), the intervention stimulus is given at the timing (circle in the figure) when the estimated value becomes a random estimated value (first estimated value) selected within the range of the standard threshold plus minus α. Note that at this time, the intervention stimulus is given according to the stimulus condition in which the intensity of the intervention stimulus is set randomly. The intervention stimulus is given with such random timing and intensity, and the estimated mental value (second estimated value) of the user 99 when a predetermined period has passed from the timing when the intervention stimulus was given (diamond in the figure) is estimated and recorded in association with the stimulus condition. By repeating this, the stimulus condition and the first and second estimated values ​​are accumulated. In this case, it can be said that the higher the second estimated value is than the first estimated value, the higher the effect of improving the mental state by the intervention stimulus.

[0039] Switching between a mode of providing a random intervention stimulus for updating the information stored in the intervention stimulus effect database 103 and a mode of providing an intervention stimulus more optimized for the user 99 based on the information stored in the intervention stimulus effect database 103 may be performed at predetermined intervals or may be performed by the user 99. For example, the mode may be changed to a mode of providing a random intervention stimulus every time a predetermined period such as one month, half a year, or one year passes until the required information is obtained. Also, for example, when the user 99 feels that the effect of the intervention stimulus is low, the mode may be switched to a mode of providing a random intervention stimulus until the required information is obtained.

[0040] In addition, although the above description has been given as a mode in which a random intervention stimulus is given, in order to obtain the necessary information in the shortest time possible, the stimulus conditions after switching to the mode may not be randomly determined, but a combination of the intensity of the intervention stimulus and the timing of the intervention stimulus may be selected in a round-robin manner. In other words, a stimulus condition that is at least partially different from a previously selected stimulus condition may be selected next time.

[0041] FIG. 5 shows an example in which the predetermined period between the first estimated value and the second estimated value is constant, but the effect of improving the mental state by the intervention stimulus varies depending on how the predetermined period is set. It is estimated that the predetermined period requires different periods from when the intervention stimulus is perceived until the effect appears depending on the type of stimulus, etc. Therefore, in order to optimize the predetermined period, a condition for specifying the predetermined period may be included in the stimulus conditions.

[0042] Returning to the explanation of Fig. 4, Fig. 4 shows the relationship between the intensity of the intervention stimulus and the timing of providing the intervention stimulus, and does not mention the type of intervention stimulus. However, in order to further optimize the type of intervention stimulus for an individual, in the present invention, for different types of intervention stimuli, information indicating the relationship between the intensity of the intervention stimulus and the timing of providing the intervention stimulus is stored in the intervention stimulus effect database 103 in the same manner as in Fig. 4. That is, the stimulus conditions include the type of intervention stimulus as well as the intensity of the intervention stimulus and the timing of providing the intervention stimulus.

[0043] 3 again, the stimulation condition determination unit 104 is a processing unit that refers to the intervention stimulation effect database 103, determines optimal stimulation conditions (optimal stimulation conditions) for the user 99, and outputs the optimal stimulation conditions to the stimulation device 400. The optimal stimulation conditions are the above-mentioned stimulation conditions that are a combination in which the second estimated value is higher than the first estimated value and the difference between the first estimated value and the second estimated value (also called change information) is maximized. However, while information is being stored in the intervention stimulation effect database 103, the stimulation condition determination unit 104 determines random or efficient stimulation conditions as described above and outputs the same to the stimulation device 400.

[0044] The stimulation device 400 is a device that provides an intervention stimulus to the user 99 according to the determined stimulation conditions. A plurality of devices are prepared for the stimulation device 400 according to the type of stimulation. For example, if the type of stimulation is a visual stimulation that changes the brightness of the lighting, the stimulation device 400 is realized by a lighting device and its control device. Similarly, if the type of stimulation is an olfactory stimulation that releases a mint scent into a space, the stimulation device 400 is realized by a spray device for aromatic components and its control device. In this way, the stimulation device 400 may be any device that can provide an appropriate intervention stimulus according to the type of stimulation. The stimulation condition determination unit 104 and the stimulation device 400 are collectively referred to as an intervention stimulation unit.

[0045] The output unit 105 is a processing unit that outputs information to the display device 500. For example, the output unit 105 generates and outputs, as an image, a correlation map (i.e., the graph shown in FIG. 4) showing the correlation between the difference (change information) between the first estimated value and the second estimated value stored in the intervention stimulation effect database 103 and the stimulation condition. The display device 500 is, for example, a terminal device equipped with a display such as a tablet terminal, a smartphone, or a PC owned by the user 99. The display device 500 can display the image output from the output unit 105 on the display.

[0046] For example, the user 99 can view an image of the correlation map and confirm the stimulation conditions estimated to be optimal for the user 99. Furthermore, it is possible to configure the correlation map so that it is possible to accept input of correction information from the user 99. In this way, it is possible to provide an intervention stimulation that matches the user's 99 recognition and causes little discomfort.

[0047] The output unit 105 may output an image as shown in FIG. 6, for example. FIG. 6 is a diagram showing an example of comparison information output in the embodiment. In the graph shown in FIG. 6, the effect of improving the level of awakening when an intervention stimulus is given under standard stimulation conditions (i.e., the difference between the second estimated value and the first estimated value under the central stimulation condition in FIG. 4) is compared with the effect of improving the level of awakening when an intervention stimulus is given under optimal stimulation conditions (i.e., the difference between the second estimated value and the first estimated value under the stimulation condition indicated by the white arrow in FIG. 4). This makes it possible to visualize the difference in user experience between a case where the intervention stimulus is individually optimized by the environmental control system 200 and a case where it is not.

[0048] Next, an operation example of the environmental control system 200 will be described with reference to Fig. 7. Fig. 7 is a flowchart of an operation example of the environmental control system according to the embodiment.

[0049] First, the user 99 enters one of the private booths. Then, the user 99 logs in using biometric authentication such as face authentication or fingerprint authentication, or a terminal device in the private booth. Then, the environmental control system 200 reads out information from the intervention stimulus effect database 103 in which information on the user 99 is stored. At this time, the stimulus condition determination unit 104 determines the stimulus condition of the intervention stimulus to be given to the user 99 next time by referring to the intervention stimulus effect database 103 (S101).

[0050] Next, the biometric information acquisition unit 101 acquires biometric information of the user 99 from various measuring devices 300 installed in the private booth or worn by the user 99 (S102). The acquired biometric information is output to the mental state estimation unit 102.

[0051] The mental state estimation unit 102 estimates an estimated value indicating the mental state of the user 99 at the time the biological information was acquired based on the acquired biological information (S103). Steps S102 and S103 are continuously performed, and the estimated mental state value is estimated substantially continuously. Here, the stimulation condition determination unit 104 judges whether the estimated value crosses a predetermined threshold included in the determined stimulation condition (S104). If the stimulation condition determination unit 104 judges that the estimated value does not cross a predetermined threshold included in the determined stimulation condition (No in S104), the process returns to step S102, and the acquisition of biological information and the estimation of the estimated mental state value are continued again. On the other hand, if the stimulation condition determination unit 104 judges that the estimated value crosses a predetermined threshold included in the determined stimulation condition (Yes in S104), the stimulation condition determination unit 104 transmits the determined stimulation condition to the stimulation device 400. Then, the stimulation device 400 gives an intervention stimulus to the user 99 according to the stimulation condition (S105). At this time, the optimal stimulation conditions at that time are determined as the stimulation conditions, so that an intervention stimulation that is more optimized in terms of the effect of improving the mental state of the user 99 is provided.

[0052] In addition, the environmental control method of the present disclosure can also be realized in a form in which, based on the data of a large number of users, a stimulus condition suitable for the user 99 is determined by inference from the tendency shown in the data of the large number of users by utilizing machine learning, and an intervention stimulus is given to the user 99 under the determined stimulus condition. Specifically, in the environmental control method according to this alternative example, the following steps are performed by one or more processors. First, a step of acquiring bioinformation related to the user's bioactivity and a step of estimating an estimated value indicating the mental state of the user at the time the bioinformation was acquired based on the acquired bioinformation are performed. Up to this point, it is the same as step S102 and step S103 of the operation example of the environmental control system 200 in the embodiment described above.

[0053] In the environmental control method according to the other example, a step is further carried out in which an estimated value indicating the mental state of the user 99 is input to a model trained using an estimated value (hereinafter referred to as a third estimated value) indicating the mental state of a large number of users and a stimulus condition of the intervention stimulus under which a change in the third estimated value after the intervention stimulus is given to the large number of users at that time satisfies a specific condition, and the estimated value indicating the mental state of the user 99 is output as a stimulus condition. Then, a step is carried out in which an intervention stimulus is given to the user 99 based on the output stimulus condition. This step is similar to step S105 in the operation example of the environmental control system 200 in the embodiment described above.

[0054] Thus, the environmental control method according to the other example differs in that, instead of steps S101 and S104 in the operational example of the environmental control system 200, a step is carried out in which an estimated value indicating the mental state of the user 99 is input into a model and stimulation conditions are output.

[0055] Here, the above-mentioned large number of users includes many others other than the user 99 (hereinafter also referred to as the target user) to whom the intervention stimulus is given by the environmental control system 200. The large number of users may include the target user in addition to many others. The above-mentioned model is, for example, a neural network model, and is a trained model that has completed learning using an estimated value indicating the mental state of each of the large number of users, i.e., a third estimated value, and a stimulus condition of the intervention stimulus under which a change in the third estimated value after the intervention stimulus is given to each of the large number of users satisfies a specific condition.

[0056] If an estimated value indicating the mental state of the target user is input into the above model, a certain stimulation condition is output. If an intervention stimulus is given to the target user according to the stimulation condition output here, it is expected that the estimated mental state of the target user will change to satisfy the above specific condition. In other words, by setting the specific condition as a condition corresponding to a mental change that is desired to be caused as a result of the intervention stimulus given to the target user, it is considered that the stimulation condition output from the model acts on the target user so as to cause the mental change that is desired to be caused by the intervention stimulus given to the target user according to the stimulation condition. In other words, the specific condition is determined according to the mental change of the target user that is desired to be caused by the intervention stimulus given to the target user. The specific condition is, for example, changing the estimated mental state value to a certain high value or higher within a predetermined period after the intervention stimulus.

[0057] Incidentally, it is known that such a trained model can improve the accuracy of its inference by re-learning. In order to apply this to the present example, after the trained model is used to output a stimulation condition for the target user from the estimated mental value as described above, the change in the estimated mental value is linked to the stimulation condition at that time by the intervention stimulation according to the stimulation condition and stored in a storage unit or the like. By picking up a stimulation condition where the change in the estimated mental value stored in the past satisfies the above-mentioned specific condition and performing a step of re-learning the model, it is possible to improve the accuracy of inference by a model specialized for the target user. In other words, if the re-learned model is used in determining future stimulation conditions, it is possible to output a stimulation condition that is more suitable for the target user, that is, a stimulation condition where a change in the estimated mental value that satisfies the specific condition is likely to occur in the target user.

[0058] From the viewpoint of specialization to the target user, all of the many users may be the target users. Specifically, a model may be trained using the third estimated mental state value estimated at many different points in the past of the target user and the stimulus condition of the intervention stimulus in which the change in the third estimated value after the intervention stimulus is given to the target user at each time satisfies a specific condition. In this way, since all of the many users are the target users, a trained model that performs inference specialized for the target user can be generated. However, such a model is not suitable for use in estimating stimulus conditions other than the target user. Therefore, in an example in which a model specialized for this target user (including a retrained model) is used, an operation of identifying the target user, such as logging in the target user, and reading out the model specialized for the target user for use in estimation may be performed. Conversely, if a model specialized for the target user is not used, the generated model can be diverted to another user, so there is no need to perform an operation to identify the target user, and there is also the advantage that the environmental control system can be shared by an unspecified number of users in public facilities, etc.

[0059] [Effects, etc.] As described above, the environmental control system 200 of the first embodiment includes a bioinformation acquisition unit 101 that acquires bioinformation related to the bioactivity of a user 99, a mental estimation unit 102 that estimates an estimated value indicating the mental state of the user 99 at the time the bioinformation was acquired based on the acquired bioinformation, an intervention stimulation unit (stimulation condition determination unit 104 and stimulation device 400) that gives an intervention stimulus to the user 99 according to the stimulation conditions, and an intervention stimulation effect database 103 that is referenced when the stimulation condition determination unit 104 determines the stimulation conditions for giving the intervention stimulus. The intervention stimulation effect database 103 stores change information indicating changes in the estimated value after an intervention stimulus is given according to each of two or more stimulation conditions, at least one of which is different from the other stimulation conditions, in association with the stimulation condition when the intervention stimulus was given, and the stimulation condition includes the intensity of the intervention stimulus and a predetermined threshold value set for the estimated value, where the intervention stimulus is given when the estimated value changes across the predetermined threshold value.

[0060] Such an environmental control system 200 can refer to the intervention stimulus database, identify change information indicating that a change in an estimated value indicating a mental state is more appropriate for the user 99, and determine the stimulus condition linked to the identified change information as the stimulus condition for the intervention stimulus to be provided. Since the stimulus condition includes a predetermined threshold value set for the estimated value so as to correspond to the intensity of the intervention stimulus and the timing of providing the intervention stimulus, it is possible to determine a stimulus condition in which at least the intensity of the intervention stimulus and the timing of providing the intervention stimulus are appropriate for the user 99 in terms of the change information. Thus, the environmental control system 200 can provide an intervention stimulus that is more optimized for an individual.

[0061] Also, for example, the environmental control system 200 according to the second aspect is the environmental control system 200 described in the first aspect, and the mental state may include at least one of the user 99's comfort level, the user 99's alertness level, the user 99's concentration level, the user 99's relaxation level, the user 99's communication level, and the user 99's creativity.

[0062] According to this, change information indicating that a change in an estimated value indicating a mental state including at least one of the user 99's comfort level, the user 99's alertness level, the user 99's concentration level, the user 99's relaxation level, the user 99's communication level, and the user 99's creativity is more appropriate can be identified, and the stimulation condition linked to the identified change information can be determined as the stimulation condition for the intervention stimulation to be given.

[0063] Also, for example, the environmental control system 200 according to the third aspect is the environmental control system 200 described in the first or second aspect, and the stimulation condition may be a type of intervention stimulus, which may include a type of intervention stimulus selectively selected from among the five sensory stimuli.

[0064] According to this, it is possible to determine a stimulation condition including a type of intervention stimulation selectively selected from among the five sense stimulations. Therefore, in addition to the intensity of the intervention stimulation and the timing of providing the intervention stimulation, it is possible to determine a stimulation condition in which the type of intervention stimulation is suitable for the user 99 in terms of change information.

[0065] Also, for example, an environmental control system 200 according to a fourth aspect is an environmental control system 200 according to any one of the first to third aspects, and the intervention stimulus effect database 103 stores, as change information, a first estimated value and a second estimated value for calculating a change in the estimated value after the intervention stimulus is given, linked to the respective stimulus conditions when the intervention stimulus is given, and the first estimated value may be an estimated value when the intervention stimulus is given, and the second estimated value may be an estimated value after a predetermined period has elapsed since the intervention stimulus was given.

[0066] According to this, change information indicating the change in the estimated value after the intervention stimulus is given can be calculated from the first estimated value when the intervention stimulus is given and the second estimated value after a predetermined period of time has elapsed since the intervention stimulus was given.

[0067] Also, for example, the environmental control system 200 of the fifth aspect is the environmental control system 200 described in the fourth aspect, in which the higher the estimated value, the better the mental state, and the stimulation device 400 may prohibit the provision of an intervention stimulus to the user 99 in accordance with the stimulation condition determined as the stimulation condition for a combination of a first estimated value, a second estimated value, and a stimulation condition that are linked to each other, when the second estimated value is lower than the first estimated value by the stimulation condition determination unit 104 referring to the intervention stimulation effect database 103.

[0068] This makes it possible to prohibit the intervention stimulus from being given to the user 99 under stimulus conditions in which the second estimated value is lower than the first estimated value, that is, in which the mental state tends to deteriorate.

[0069] Also, for example, the environmental control system 200 of the sixth aspect is the environmental control system 200 described in the fourth or fifth aspect, in which the higher the estimated value, the better the mental state, and the stimulation device 400 may provide an intervention stimulus to the user 99 in accordance with the stimulation condition determined as the stimulation condition for a combination of a first estimated value, a second estimated value, and a stimulation condition that are linked to each other, when the second estimated value is higher than the first estimated value, by the stimulation condition determination unit 104 referring to the intervention stimulation effect database 103.

[0070] According to this, it is possible to provide the user 99 with an intervention stimulus under a stimulus condition in which the second estimated value is higher than the first estimated value, that is, in which the mental state tends to improve.

[0071] Also, for example, the environmental control system 200 according to the seventh aspect is the environmental control system 200 according to any one of the fourth to sixth aspects, and includes an output unit 105, and the higher the estimated value, the better the mental state. The stimulation device 400 provides an intervention stimulus to the user 99 according to optimal stimulation conditions determined by the stimulation condition determination unit 104 with reference to the intervention stimulation effect database 103 as a combination of a first estimated value, a second estimated value, and a stimulation condition that are linked to each other, in which the second estimated value is higher than the first estimated value and the difference between the first estimated value and the second estimated value is the largest. The output unit 105 may compare the second estimated value estimated by the mental estimation unit 102 when the intervention stimulus is provided according to the optimal stimulation condition with a virtual second estimated value when it is assumed that the intervention stimulus is provided according to a standard stimulation condition, which is a standard stimulation condition, and output the second estimated value linked to the stimulation condition corresponding to the standard stimulation condition with reference to the intervention stimulation effect database 103.

[0072] According to this, when an intervention stimulus is given according to optimal stimulus conditions, the second estimated value estimated by the mentality estimation unit 102 can be output in comparison with the second estimated value associated with the stimulus conditions corresponding to the standard stimulus conditions. In other words, the difference in the change in the estimated value between when the stimulus conditions are optimized for the user 99 and when the stimulus conditions are standard stimulus conditions that are not optimized can be output as a comparison.

[0073] Furthermore, for example, the environmental control system 200 according to the eighth aspect may be an environmental control system 200 according to any one of the first to seventh aspects, and may include an output unit 105 that generates and outputs a correlation map showing the correlation between the change information stored in the intervention stimulation effect database 103 and the stimulation conditions.

[0074] This makes it possible to generate and output a correlation map showing the correlation between the change information stored in the intervention stimulus effect database 103 and the stimulus conditions.

[0075] In addition, an environmental control method according to a ninth aspect is an environmental control method executed using a computer, which acquires bioinformation regarding the bioactivity of a user 99, estimates an estimated value indicating the mental state of the user 99 at the time the bioinformation was acquired based on the acquired bioinformation, and provides an intervention stimulus to the user 99 according to stimulation conditions determined by referring to an intervention stimulation effect database 103, in which change information indicating changes in the estimated value after an intervention stimulation is provided according to each of two or more stimulation conditions, at least one of which is different from the other stimulation conditions, is stored in association with the stimulation conditions at the time the intervention stimulation was provided, and the stimulation conditions include the intensity of the intervention stimulation and a predetermined threshold set for the estimated value, at which the intervention stimulation is provided when the estimated value changes and crosses the predetermined threshold.

[0076] According to such an environmental control method, it is possible to achieve the same effects as those achieved by the environmental control system 200 described above.

[0077] Further, an environmental control method according to a tenth aspect is an environmental control method executed using a computer, and includes the steps of acquiring bioinformation regarding the bioactivity of a user (target user), estimating an estimated value indicating the mental state of the target user at the time the bioinformation was acquired based on the acquired bioinformation, inputting the estimated value indicating the mental state of the target user into a model trained using a third estimated value indicating the mental states of a large number of users and a stimulation condition for the intervention stimulation under which a change in the third estimated value after the intervention stimulation is administered to each of the large number of users satisfies a specific condition, and outputting the stimulation condition, and providing an intervention stimulation to the target user based on the output stimulation condition, wherein the stimulation condition includes an intensity of the intervention stimulation and a predetermined threshold value set for the estimated value, where the intervention stimulation is provided when the estimated value changes across the predetermined threshold.

[0078] According to such an environmental control method, a stimulus condition for providing intervention control to a target user can be estimated from the mental state of the target user by using a model based on the third estimated value indicating the mental state of many users and the third estimated value after the intervention stimulus is provided to many users. Therefore, the environmental control method of the present disclosure can quickly provide the user with an intervention stimulus that is more optimized in terms of the effect of improving the mental state of the target user.

[0079] Also, for example, an environmental control method according to an 11th aspect is an environmental control method according to the 10th aspect, and further includes a step of re-learning a model using past estimated values ​​indicating the mental state of the target user and stimulation conditions of the intervention stimulation such that a change in the estimated value of the target user since the intervention stimulation was given to the target user in the past satisfies a specific condition, and in the step of estimating future stimulation conditions, the estimated values ​​indicating the mental state of the target user are input into the re-learned model to estimate the stimulation conditions.

[0080] According to this, the generated model can be re-learned using past estimated values ​​indicating the mental state of the target user and the stimulus conditions of the intervention stimulus where the change in the estimated value of the target user since the intervention stimulus was given to the target user in the past satisfies certain conditions, thereby regenerating a model specialized for the target user.

[0081] Also, for example, an environmental control method according to a twelfth aspect is the environmental control method according to the tenth or eleventh aspect, in which the model is a neural network.

[0082] According to this, it is possible to estimate the stimulus conditions for providing intervention control to the target user from the mental state of the target user, not only through supervised learning but also through unsupervised learning.

[0083] A program according to a thirteenth aspect is a program for causing a computer to execute the environment control method according to any one of the ninth to twelfth aspects.

[0084] Such a program can achieve the same effects as the above-described environmental control system 200 by using a computer.

[0085] (Other embodiments) Although the embodiment has been described above, the present invention is not limited to the above embodiment.

[0086] For example, in the above embodiment, the environmental control device includes a mental state estimation unit, and the mental state estimation unit's calculation function is used to estimate an estimated mental state of the user. However, the mental state estimation unit may be implemented by a machine learning model learned using machine learning. That is, instead of the function of the mental state estimation unit in the above embodiment to calculate a biomarker from the acquired bioinformation using a calculation function and to mathematically calculate an estimated mental state, the mental state estimation unit in this example incorporates a machine learning model that can input the acquired bioinformation and obtain an estimated mental state as a corresponding output.

[0087] In this way, the machine learning model may be stored (embedded) in the environmental control device according to the modified example. The machine learning model stored in the environmental control device is used to estimate an estimated value indicating the mental state. For example, the machine learning model can directly output only the estimated value by omitting a calculation function of calculating a biometric indicator from the acquired biometric information by inputting the biometric information of the user and outputting an estimated value indicating the mental state of the user from the calculated biometric indicator. The machine learning model may have a convolution layer, and may be, for example, a convolutional neural network (CNN), but is not limited thereto. The machine learning model may be trained, for example, using teacher data. The teacher data may be, for example, a data set including a pair of the biometric information of the user as input data and an estimated value indicating the mental state of the user as output data. The machine learning model is a trained machine learning model trained in advance by machine learning, and includes trained parameters adjusted by machine learning. The machine learning model may be generated, for example, by a model generation unit (not shown) built into the environmental control device as a part of the function of the environmental control device, or may be generated by an external device such as a cloud server and then transmitted to the environmental control device and incorporated therein.

[0088] Also, for example, in the above embodiment, stimuli were presented to the user by controlling the environment of the space in which the subject was located, but it is also possible to construct an environmentally controlled space in advance and provide stimuli to the user by the user entering this space.

[0089] Furthermore, the communication method between the components in the above-described embodiment is not particularly limited. In addition, a relay device (not shown) may be involved in the communication between the components.

[0090] In the above embodiment, the processes executed by a specific processing unit may be executed by another processing unit. The order of multiple processes may be changed, or multiple processes may be executed in parallel.

[0091] In the above embodiment, each component may be realized by executing a software program suitable for each component. Each component may be realized by a program execution unit such as a CPU or a processor reading and executing a software program recorded on a recording medium such as a hard disk or a semiconductor memory.

[0092] Furthermore, each component may be realized by hardware. For example, each component may be a circuit (or an integrated circuit). These circuits may form a single circuit as a whole, or each may be a separate circuit. Furthermore, each of these circuits may be a general-purpose circuit, or a dedicated circuit.

[0093] Furthermore, the general or specific aspects of the present invention may be realized as a system, an apparatus, a method, an integrated circuit, a computer program, or a computer-readable recording medium such as a CD-ROM, or may be realized as any combination of a system, an apparatus, a method, an integrated circuit, a computer program, and a recording medium.

[0094] For example, the present invention may be realized as an environmental control method executed by a computer such as an environmental control system, or as a program for causing a computer to execute such an environmental control method. Furthermore, the present invention may be realized as a computer-readable non-transitory recording medium on which such a program is recorded.

[0095] In addition, the present invention also includes forms obtained by applying various modifications to each embodiment that a person skilled in the art may think of, or forms realized by arbitrarily combining the components and functions of each embodiment within the scope that does not deviate from the spirit of the present invention. [Explanation of symbols]

[0096] 99 users 100 Environmental control device 101 Biometric information acquisition unit 102 Mental Identification Department 103 Intervention Stimulus Effect Database 104 Stimulus condition determination unit 105 Output section 200 Environmental Control System 300 Measuring Equipment 400 Stimulator 500 display device

Claims

1. A biological information acquisition unit that acquires biological information related to a biological activity of a user; a mental state estimation unit that estimates an estimated value indicating a mental state of the user at the time when the biometric information was acquired based on the acquired biometric information; An intervention stimulation unit that provides an intervention stimulation to the user according to a stimulation condition; An intervention stimulus effect database to be referred to when the intervention stimulus unit determines the stimulus condition for providing the intervention stimulus; An output unit, The intervention stimulus effect database stores change information indicating a change in the estimated value after the intervention stimulus is given according to each of two or more stimulus conditions, at least one of which is different from the other stimulus conditions, in association with the stimulus condition when the intervention stimulus is given; The stimulus condition includes an intensity of the intervention stimulus and a predetermined threshold value set for the estimated value, the intervention stimulus being provided at a timing when the estimated value changes across the predetermined threshold value; In the intervention stimulus effect database, a first estimated value and a second estimated value for calculating a change in the estimated value after the intervention stimulus is given are stored as the change information in association with the respective stimulation conditions when the intervention stimulus is given, the first estimate is the estimate when the intervention stimulus is provided; the second estimate is the estimate after a predetermined period of time has elapsed since the intervention stimulus was given; A higher estimated value indicates a better mental state, the intervention stimulation unit refers to the intervention stimulation effect database, and provides the intervention stimulation to the user according to optimal stimulation conditions, which are the stimulation conditions of a combination of the first estimated value, the second estimated value, and the stimulation condition that are linked to each other, in which the second estimated value is higher than the first estimated value and a difference between the first estimated value and the second estimated value is maximized; The output unit is When the intervention stimulus is given according to the optimal stimulus condition, the mental state estimation unit The second estimated value; The second estimated value is a hypothetical value obtained on the assumption that the intervention stimulus is given according to a standard stimulus condition, which is a standard stimulus condition. The second estimated value is compared with the second estimated value associated with the stimulus condition corresponding to the standard stimulus condition by referring to the intervention stimulus effect database. Environmental control system.

2. The mental state includes at least one of a comfort level of the user, a wakefulness level of the user, a concentration level of the user, and a relaxation level of the user. The environmental control system of claim 1 .

3. The stimulation condition includes a type of the intervention stimulation, the type of the intervention stimulation being selectively selected from among five sensory stimulations. The environmental control system of claim 1 .

4. A higher estimated value indicates a better mental state, The intervention stimulation unit refers to the intervention stimulation effect database, and when the second estimated value is lower than the first estimated value in a combination of the first estimated value, the second estimated value, and the stimulation condition that are linked to each other, prohibits the intervention stimulation from being given to the user according to the stimulation condition of the combination. The environmental control system of claim 1 .

5. A higher estimated value indicates a better mental state, The intervention stimulation unit refers to the intervention stimulation effect database, and when the second estimated value is higher than the first estimated value in a combination of the first estimated value, the second estimated value, and the stimulation condition that are linked to each other, provides the intervention stimulation to the user according to the stimulation condition of the combination. The environmental control system of claim 1 .

6. The output unit further generates and outputs a correlation map showing a correlation between the change information stored in the intervention stimulation effect database and the stimulation condition. The environmental control system according to any one of claims 1 to 5.

7. A program for causing a computer to execute the program, acquiring biometric information relating to a bioactivity of a user; estimating an estimated value indicating a mental state of the user at the time when the biometric information was acquired based on the acquired biometric information; providing an intervention stimulus to the user according to a stimulus condition determined by referring to an intervention stimulus effect database; and outputting the result. The intervention stimulus effect database stores change information indicating a change in the estimated value after the intervention stimulus is provided under each of two or more stimulation conditions, at least one of which is different from the other stimulation conditions, in association with the stimulation condition when the intervention stimulus is provided; The stimulus condition includes an intensity of the intervention stimulus and a predetermined threshold value set for the estimated value, the intervention stimulus being provided at a timing when the estimated value changes across the predetermined threshold value; In the intervention stimulus effect database, a first estimated value and a second estimated value for calculating a change in the estimated value after the intervention stimulus is given are stored as the change information in association with the respective stimulation conditions when the intervention stimulus is given, the first estimate is the estimate when the intervention stimulus is provided; the second estimate is the estimate after a predetermined period of time has elapsed since the intervention stimulus was given; A higher estimated value indicates a better mental state, In the providing step, the intervention stimulus is provided to the user according to optimal stimulation conditions, which are combinations of the first estimated value, the second estimated value, and the stimulation conditions that are linked to each other, in which the second estimated value is higher than the first estimated value and the difference between the first estimated value and the second estimated value is the largest, by referring to the intervention stimulus effect database; In the outputting step, The second estimated value estimated in the estimating step when the interventional stimulus is given according to the optimal stimulus condition; The second estimated value is a hypothetical value obtained on the assumption that the intervention stimulus is given according to a standard stimulus condition, which is a standard stimulus condition. The second estimated value is compared with the second estimated value associated with the stimulus condition corresponding to the standard stimulus condition by referring to the intervention stimulus effect database. program.

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