Index calculation device and index calculation method

Abstract

To calculate, when a person carries out a behavior of movement, an index of the behavior including not only physical fatigue but mental fatigue.SOLUTION: An index calculation device 1 according to the present disclosure comprises a motion quantity calculation unit, an event information acquisition unit, and an index calculation unit. The motion quantity calculation unit calculates the quantity of motion occurring in a user on the basis of movement information indicating the movement of the user. The event information acquisition unit acquires event information indicating an event occurring during the movement of the user. The index calculation unit calculates a behavior index indicating the behavior of the user on the basis of the quantity of motion and event information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to an index calculation device and an index calculation method. [Background technology]

[0002] Patent Document 1 discloses a technique for searching for travel routes based on an allowable travel time that is within a user's tolerance range, and calculating and displaying the calories burned by walking for each travel route. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2018-031699 A Summary of the Invention [Problem to be solved by the invention]

[0004] Meanwhile, since people may encounter various events while moving, the sense of accomplishment or fatigue of the action changes depending on the event encountered, not only the amount of physical exercise that can be expressed by calories burned, which can be calculated by the technology described in Patent Document 1, but also mental elation, discomfort, or fatigue. Therefore, if an index indicating a person's action of moving can be calculated by taking into account not only the amount of physical exercise but also mental elation, discomfort, or fatigue, it can be said that the value of the index increases, and there is a demand for technology to calculate such an index. [Means for solving the problem]

[0005] The index calculation device according to the present disclosure includes an exercise amount calculation unit that calculates an amount of exercise caused by a user based on movement information indicating the user's movement, an event information acquisition unit that acquires event information indicating an event that occurred during the user's movement, and an index calculation unit that calculates a behavior index indicating the user's behavior based on the amount of exercise and the event information.

[0006] The index calculation method disclosed herein involves a computer calculating an amount of exercise performed by a user based on movement information indicating the user's movement, acquiring event information indicating events that occurred during the user's movement, and calculating a behavior index indicating the user's behavior based on the amount of exercise and the event information. Effect of the Invention

[0007] According to the present disclosure, when a person performs a movement behavior, an index of the behavior can be calculated that takes into account not only physical fatigue but also mental fatigue. [Brief description of the drawings]

[0008] [Figure 1] 1 is a block diagram showing a configuration example of an index calculation device according to a first embodiment. [Diagram 2] 2 is a flow diagram for explaining an example of an index calculation process executed by the index calculation device of FIG. 1. [Diagram 3] FIG. 2 is a schematic diagram showing an example of an environment in which the index calculation device of FIG. 1 is used. [Figure 4] 2 is a schematic diagram showing an example of a destination proposal image displayed in the index calculation device of FIG. 1. [Diagram 5] 2 is a schematic diagram showing an example of an index display image displayed in the index calculation device of FIG. 1. [Figure 6] FIG. 11 is a block diagram showing a configuration example of an index calculation system including an index calculation device according to a second embodiment. [Figure 7] 7 is a flow chart for explaining an example of an index calculation process executed by the index calculation device of FIG. 6. [Figure 8] FIG. 11 is a block diagram showing a configuration example of an index calculation system including an index calculation device according to a third embodiment. [Figure 9] 9 is a flow chart for explaining an example of an index calculation process executed by the index calculation device of FIG. 8. FIG. [Figure 10]9 is a schematic diagram showing an example of the location of an event detected in an index calculation process in an example of an environment in which the index calculation device of FIG. 8 is used. [Figure 11] 9 is a schematic diagram showing an example of an exercise suggestion image displayed in the index calculation device of FIG. 8. FIG. [Figure 12] 12 is a schematic diagram showing an example of an exercise suggestion image displayed when an event history display operation is performed from the exercise suggestion image of FIG. 11 in the index calculation device of FIG. 8. FIG. [Figure 13] 9 is a schematic diagram showing an example of an index display image displayed in the index calculation device of FIG. 8. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] The following describes an embodiment of the invention, but the invention according to the claims is not limited to the following embodiment. Also, not all of the configurations described in the embodiment are necessarily essential as means for solving the problem. For clarity of explanation, the following description and drawings have been omitted and simplified as appropriate.

[0010] <Embodiment 1> A configuration example of an index calculation device according to the first embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing a configuration example of an index calculation device according to the first embodiment.

[0011] 1, the index calculation device 1 according to the present embodiment may include a control unit 10, a storage unit 16, an operation unit 17, a display unit 18, a position information acquisition unit 19, a communication unit 20, a voice input unit 21, and an imaging unit 22. The index calculation device 1 has a function of calculating a behavior index indicating a user's behavior, the details of which will be described later. The index calculation device 1 may be configured by installing the functions of the index calculation device 1 in a general-purpose information processing device such as a smartphone, a smartwatch, or a PC (Personal Computer), but may also be configured as a dedicated device.

[0012] The control unit 10 controls the entire index calculation device 1. The control unit 10 may be realized, for example, by a processor such as a CPU (Central Processing Unit), a working memory, and a non-volatile storage device storing a control program. This program may include a program that realizes the functions of the index calculation device 1 by being executed by the processor. The control unit 10 may also be realized using a user-programmable integrated circuit such as an FPGA (field-programmable gate array) or a microcomputer.

[0013] The storage unit 16 is a storage device such as an SSD (Solid State Drive) or an HDD (Hard Disk Drive) that stores various information used in the index calculation device 1. The operation unit 17 is a part that accepts operations by a user, and the contents of the operation are transmitted to the control unit 10, and the control unit 10 executes control according to the contents. The operation unit 17 may be composed of at least one of physical keys and software keys, or may be composed of a voice input unit and a voice recognition unit, or may be composed of both of them.

[0014] The display unit 18 may be configured with a display device such as a liquid crystal panel, an organic electroluminescence panel, etc. The operation unit 17 may include a touch sensor incorporated in the display unit 18. In that case, the index calculation device 1 includes a touch panel as an example of the display unit 18 and the operation unit 17.

[0015] The position information acquisition unit 19 acquires position information by a Global Navigation Satellite System (GNSS). The position information acquisition unit 19 is, for example, a receiver in the GNSS. The position information acquisition unit 19 can also acquire time information indicating the time at which the position information is acquired, in addition to acquiring the position information.

[0016] The communication unit 20 communicates with an external device. The communication unit 20 may be, for example, a communication unit that communicates in accordance with a short-range wireless communication standard such as Bluetooth (registered trademark; the same applies below) LE (Low Energy), or a communication unit that communicates in accordance with a wireless communication standard such as WiFi (registered trademark; the same applies below).

[0017] The audio input unit 21 is composed of a microphone or the like that inputs the voice of the user or the surroundings. The arrangement of the audio input unit 21 is not important, but it can be arranged, for example, on the display screen side of the display unit 18, that is, at one or more locations on the front side, or at one or more locations on the opposite side, that is, the rear side, or on both the front and rear sides.

[0018] The imaging unit 22 may be configured with a camera or the like, and captures an image. The imaging unit 22 may be disposed, for example, on at least one of the front side and the rear side.

[0019] Next, a detailed description will be given of the control unit 10 which is responsible for the main part of the function of the index calculation device 1. The control unit 10 can include an information acquisition processing unit 11, an exercise amount calculation processing unit 12, and an index calculation processing unit 13, as shown in FIG.

[0020] The behavior indicated by the behavior index calculated by the index calculation device 1 can include movement performed by the user without using a moving object, that is, exercise, or can include movement performed by the user using a moving object, that is, the user boarding the moving object. Of course, the above behavior can include both exercise performed by the user and movement performed by the user boarding the moving object. In addition, one or more types of moving objects among various types of moving objects can be applied. In this way, the behavior indicated by the behavior index can be one or more predetermined types of behavior performed in various types of moving forms.

[0021] Here, the moving body can be a mobility that allows a user to sit down and move by driving it manually, automatically, or both manually and automatically, such as a senior car, also called a handle-type electric wheelchair. Although a senior car is an electric cart, the driving source of the moving body is not limited to electricity. The following description is mainly based on the assumption that the moving body is a senior car, but the same applies to other types of moving bodies. Other types of moving bodies include, for example, bicycles, automobiles, motorcycles, airplanes, trains, ships, etc., and are not limited to single-seater moving bodies. If the moving body is not a single-seater moving body, it may be a moving body driven by the user himself, or may be a car driven by another person such as a family member, or a moving body of public transportation such as a bus or taxi. Also, as can be seen from this example, the moving body is not limited to a moving body that is treated as a pedestrian under laws such as the Road Traffic Act.

[0022] The information acquisition processing unit 11 can acquire movement information from the moving object via the communication unit 20. The index calculation device 1 may be included in the moving object. The information acquisition processing unit 11 can acquire movement information via the communication unit 20 from, for example, a portable device carried by a user, a wearable device worn by a user, or a photographing device (not shown) installed indoors or outdoors that photographs the user. The information acquisition processing unit 11 passes the acquired movement information to the exercise amount calculation processing unit 12.

[0023] Here, the travel information can be information indicating at least one of the travel distance and travel time to the destination by the user. The travel information preferably includes information regarding the type of travel means. The travel information is information including the travel means and the travel distance or travel time, such as "walked 3 km" or "ridden a bicycle for 20 minutes". The travel information more preferably includes information indicating the intensity of exercise, such as walking speed, stride length, and number of steps (pitch) per unit time. For example, when the travel means is boarding a moving body such as a car, the travel information may include information such as the driving condition of the moving body and the comfort of the seat of the moving body. This travel information can be said to be information indicating the amount of travel. The travel distance and travel time to the destination can respectively refer to the travel distance and travel time from the departure point to the destination, but may also respectively refer to the travel distance and travel time from a position designated by the user to the destination. Note that the destination may actually be a stopover, and for example, when there is an interruption in travel for a certain period of time, the destination may be considered to have been reached at that point and processing may be performed.

[0024] The information acquisition processing unit 11 can also detect the movement of the index calculation device 1 itself using the position information acquisition unit 19 mounted on the mobile body or mobile device and acquire the movement information without using the communication unit 20. The information acquisition processing unit 11 can calculate the movement distance and movement time of the mobile body based on the position information and time information acquired by the position information acquisition unit 19. In this example, movement information indicating the movement of the user can be acquired even when the user is exercising without using a mobile body. The movement time can also be obtained by measuring the time from departure to arrival using a separately provided timer. In addition, the index calculation device 1 or the mobile body is equipped with an acceleration sensor (not shown), and the information acquisition processing unit 11 may acquire information on the acceleration and movement speed generated in the user's body or the mobile body from the acceleration sensor and calculate the movement distance and movement time.

[0025] The information acquisition processing unit 11 may also store the acquired movement information as history in the storage unit 16. The information acquisition processing unit 11 may also store, as history, movement information in the storage unit 16, movement information in the case where a moving object is used and movement information regarding exercise without using a moving object, separately.

[0026] The index calculation device 1 includes an exercise amount calculation unit that calculates the amount of exercise caused by the user based on movement information indicating the user's movement. The exercise amount calculation unit can be exemplified by the exercise amount calculation processing unit 12 and the storage unit 16, for example.

[0027] The exercise amount calculation processing unit 12 can calculate the amount of exercise caused by the movement from the movement information according to a correspondence table or a calculation formula stored in advance in the storage unit 16. The exercise amount calculation processing unit 12 may calculate the amount of exercise caused by the movement, for example, based on the exercise intensity in units of METs and the time spent exercising. The amount of exercise may be defined as any value indicating the degree of exercise, and may be, for example, calories burned. Alternatively, the amount of exercise may be a value calculated by a predetermined calculation formula for at least one of the movement distance and movement time indicated by the movement information, or may simply be a value multiplied by a predetermined coefficient, or may be a value of a rank obtained by ranking. The ranking may also be called a level division.

[0028] The motion amount calculation processing unit 12 may also calculate the following moving body motion amount and non-moving body motion amount, and calculate the motion amount based on them. The moving body motion amount refers to the motion amount generated by the user due to movement on a moving body, based on information indicating at least one of the distance and time traveled by the user by riding on the moving body, as the movement information. The non-moving body motion amount refers to the motion amount generated by the user due to the movement, based on information indicating at least one of the distance and time traveled by the user without using the moving body, as the movement information. For example, the motion amount calculation processing unit 12 calculates the motion amount by adding the moving body motion amount and the non-moving body motion amount with a predetermined weight. For example, the motion amount calculation processing unit 12 calculates the total motion amount by adding multiple types and times of exercise, such as when the user drives a senior car for 20 minutes and then walks for 10 minutes, taking into consideration the weighting of each type of exercise. In a similar way, the moving body motion amount can also be calculated by calculating the motion amount for each moving body used by the user and adding them with a predetermined weight.

[0029] In addition, the amount of exercise can be considered to change not only depending on at least one of the distance traveled and the time traveled, but also depending on the environment in which the user is moving. The environment in which the user is moving refers to the conditions during the exercise when the user is not using a mobile object, and refers to the driving conditions of the mobile object when the user is using a mobile object to move. Hereinafter, the conditions during the exercise are referred to as the exercise conditions.

[0030] In fact, moving on a mobile object has an aspect of psychological activity, but since it is connected to health, it can also be considered as exercise. Specifically, by moving on a mobile object, a user can experience things such as being exposed to the outside air, feeling the wind, being exposed to the sun, and feeling the temperature difference on their skin, and it can be said that these experiences are connected to mental and physical health.

[0031] Therefore, the driving conditions may include one or more of the following: time of day, sunshine hours, amount of sunlight, amount of ultraviolet rays, wind volume, wind direction, temperature, road undulation, and step. Note that the sunshine hours, amount of sunlight, amount of ultraviolet rays, wind volume, wind direction, temperature, road undulation, and step can be detected by a sensor provided in the moving object or the index calculation device 1. Among these, the sunshine hours, amount of sunlight, amount of ultraviolet rays, wind volume, wind direction, and temperature may be acquired by the exercise amount calculation processing unit 12 from an external server device via the communication unit 20 as weather information.

[0032] In this way, the motion amount calculation processing unit 12 may quantify the motion amount by converting the movement information and driving conditions when the user moves on a moving body such as a senior car into the motion amount due to the user's movement. In addition, the influence of road undulations, etc. on the moving body differs depending on the moving body, and the vibration received by the user also differs depending on the moving body. In addition, the user's perception of sunlight, wind, temperature, etc. differs depending on the shape of the moving body, such as the presence or absence of a roof. Therefore, the motion amount calculation processing unit 12 may calculate the motion amount so that the calculation result differs depending on the moving body used or the type of moving body used.

[0033] In addition, for exercise in which the user does not use a moving object, the same exercise conditions as the driving conditions can be used to calculate the amount of exercise. That is, the exercise amount calculation processing unit 12 can calculate the amount of exercise in which the user does not use a moving object based on the movement information and the exercise conditions including one or more of the time period, sunshine hours, amount of sunlight, amount of ultraviolet rays, wind volume, wind direction, temperature, road undulation, and step. In particular, the amount of exercise in which the user does not use a moving object varies depending on the wind volume, wind direction, sunshine, temperature, road undulation, step, etc., even when only looking at the physical aspect. Therefore, it can be said that it is particularly useful to calculate the amount of exercise based on the exercise conditions for the user's exercise.

[0034] For example, the user can perceive that the better the driving or exercise situation is, the more beneficial it is for the user's health. Therefore, the exercise amount calculation processing unit 12 may calculate the exercise amount higher as the driving or exercise situation indicates a good environment. More specifically, the exercise amount calculation processing unit 12 may calculate the exercise amount lower as the information indicating the situation differs from a reference value, such as calculating the exercise amount lower as the difference from a comfortable temperature increases. However, for information directly related to the user's exercise amount, the exercise amount calculation processing unit 12 may calculate the exercise amount higher as the fluctuation in the exercise situation increases, so that the exercise amount is a value corresponding to the exercise, regardless of the difference from the reference value.

[0035] The exercise amount calculation processing unit 12 may store the calculated exercise amount in the storage unit 16 as history. The exercise amount calculation processing unit 12 may store the history in the storage unit 16 by distinguishing between moving body exercise amount and non-moving body exercise amount. When storing the exercise amount, for example, the start and end times of movement, the movement distance, the movement time, the road surface sensation index, the outdoor air bathing index, etc. can be stored as the exercise amount. Here, the road surface sensation index can be a value that ranks the degree of undulation. The outdoor air bathing index can be a value that quantifies environmental information such as sunshine hours, amount of sunlight, amount of ultraviolet rays, wind volume, wind direction, and temperature using a predetermined conversion formula.

[0036] Moreover, the index calculation device 1 includes an event information acquisition unit that acquires event information. Here, the event information is information indicating an event that occurs while the user is moving. The case where the user is moving can include the case where the user is moving by a moving object and the case where the user is moving without using a moving object. Note that whether the user is moving or not can be determined, for example, by a change in the location information acquired by the location information acquisition unit 19.

[0037] Examples of events include, but are not limited to, conversations with other people such as neighbors, meeting a dog, meeting a cat, meeting a rare animal, discovering a plant such as a flower, discovering something beautiful, using stairs or a slope, etc. Furthermore, events for which information is acquired as event information may be limited to, for example, events that occur while the user is moving and that are predetermined as events that affect the user's mind and body.

[0038] This event information acquisition unit can be exemplified by, for example, the audio input unit 21, the imaging unit 22, and the information acquisition processing unit 11. In order to acquire event information, the information acquisition processing unit 11 requests the audio input unit 21 and the imaging unit 22 to acquire audio and images, respectively, when the user is moving.

[0039] The voice input unit 21 acquires the voice of the user while moving, and passes the acquired voice to the information acquisition processing unit 11. The imaging unit 22 captures an image of the user while moving, and passes it to the information acquisition processing unit 11. The imaging unit 22 arranged on the front side can capture events including changes in the user's facial expression. As an example of detecting an event from a facial expression, for example, it is possible to detect an encounter with a person or an animal by detecting the movement of the line of sight. Alternatively, it is possible to detect a conversation with another person by detecting the movement of the mouth. Alternatively, it is possible to detect the smell of trees or plants by detecting the flaring of the nose or sneezing. The imaging unit 22 arranged on the rear side can capture events including the environment around the user. For example, an index calculation device 1 having an imaging unit 22 on the rear side is installed on a moving body so that the imaging unit 22 faces the front of the moving body, and an event occurring in front of the moving body can be captured and the event can be detected from the captured image.

[0040] The information acquisition processing unit 11 detects, for example, from the voice acquired by the voice input unit 21, that the user has spoken, detects the voice of another person, and determines whether these are alternately continuing, thereby detecting that the user has had a conversation with another person as an event that gives the user a sense of elation. For example, the information acquisition processing unit 11 recognizes a dog or a cat from an image captured by the imaging unit 22 using an image recognition technology, and detects an encounter with a dog or a cat as an event that gives the user a sense of elation. The information acquisition processing unit 11 may detect an event that gives the user a sense of elation or an event that gives the user a sense of discomfort or fatigue using other known technologies. The information acquisition processing unit 11 detects the above-mentioned predetermined events and passes them to the index calculation processing unit 13 as event information. The information acquisition processing unit 11 may detect an event using, for example, a learning model that has machine-learned voice and images. The information acquisition processing unit 11 may also accumulate the detected event information in the storage unit 16 as a history.

[0041] However, the event information acquisition unit is not limited to this configuration, and may be composed of, for example, a voice input unit 21 or an imaging unit 22, and an information acquisition processing unit 11. Alternatively, the event information acquisition unit may acquire, as event information, part or all of the information indicating the situation described as the driving situation or exercise situation, for example, part or all of the information described as the outdoor air bathing index. In this case, the event information acquisition unit may be composed of, for example, a communication unit 20 that communicates with an external server device or a separately provided sensor, and the information acquisition processing unit 11, in order to acquire the driving situation or exercise situation.

[0042] The index calculation device 1 includes an index calculation unit that calculates a behavior index indicating the behavior of the user based on the amount of exercise and the event information. This index calculation unit can be exemplified by the index calculation processing unit 13 and the storage unit 16. The behavior index may be called a movement index since it can be said to be an index indicating the movement of the user, or it may be called an outdoor bathing index since it can be said to be an index indicating the user's going out.

[0043] The index calculation processing unit 13 can calculate the behavior index from the amount of exercise and the event information, for example, according to a correspondence table or a calculation formula prestored in the storage unit 16. The behavior index may be determined, for example, so that the greater the amount of exercise, the higher the behavior index becomes, as the level of elation indicated by the event information increases. The appropriate range of the amount of exercise can be determined, for example, centered on an optimal amount of exercise. However, the method of determining the behavior index is not limited to this. For example, the index calculation processing unit 13 may calculate the behavior index so that, when the amount of exercise is within an appropriate range, the greater the amount of exercise, the higher the behavior index becomes, and the greater the level of elation becomes, the higher the behavior index becomes.

[0044] Furthermore, the index calculation processing unit 13 or the information acquisition processing unit 11 may quantify the event information by, for example, ranking events from events that give the user a sense of elation to events that give the user a sense of discomfort or fatigue, and calculating the sum of all events that occurred during movement. In this case, the index calculation processing unit 13 can calculate the behavior index from the amount of exercise and this sum in accordance with a correspondence table or a calculation formula pre-stored in the storage unit 16. In this calculation example, the index calculation processing unit 13 may perform calculation such that the behavior index is higher as the sum of the event ranks is larger, i.e., the number of events that give the user a sense of elation is larger.

[0045] The index calculation processing unit 13 can also calculate the behavior index using a learning model that has been machine-learned on the amount of exercise and event information. The control unit 10 may obtain a learning model by machine learning that inputs various information acquired by the information acquisition processing unit 11 and outputs a behavior index, store the model in the storage unit 16, and use the learning model to calculate the behavior index from various information during operation.

[0046] With the above configuration, when the user moves, the index calculation device 1 can calculate a behavior index as an index of the behavior that takes into account not only the amount of physical exercise but also mental fatigue and excitement. This behavior index is an index of the user's daily behavior, so it can be used in various situations. In addition, the index calculation processing unit 13 can accumulate the calculated behavior index in the storage unit 16 as a history.

[0047] Furthermore, as shown in FIG. 1, the control unit 10 may include a setting processing unit 14 and a destination proposal processing unit 15. The setting processing unit 14 constitutes the next setting unit together with, for example, a storage unit 16, an operation unit 17, and a display unit 18. The setting unit sets at least one of the travel distance and travel time that the user can tolerate, that is, an upper limit of at least one of the travel distance and travel time of the user. The travel distance and travel time set as the upper limit may be the travel distance and travel time that the user can travel regardless of whether or not the user uses a moving object. In addition, the travel distance and travel time set as the upper limit may be the travel distance and travel time that the user can travel using a moving object, or the travel distance and travel time that the user can travel without using a moving object, or both.

[0048] For example, the setting processing unit 14 may store this upper limit in the storage unit 16 in accordance with a user operation received from the operation unit 17. Alternatively, the setting processing unit 14 may determine an upper limit that is estimated to be currently preferable using, for example, a learning model that performs machine learning on the user's behavioral patterns, and store the upper limit in the storage unit 16. Furthermore, the setting processing unit 14 may be configured to be able to set an upper limit for each type of moving object used by the user.

[0049] The destination proposal processing unit 15, together with the storage unit 16 and the display unit 18, constitutes the next destination proposal unit. The destination proposal unit proposes a destination for movement to the user so as not to exceed the above-mentioned set upper limit. Since the destination proposal unit requires that the set upper limit not be exceeded, it is advisable to obtain the user's current location directly from the information acquisition processing unit 11 or the location information acquisition unit 19. The timing of proposing a destination can be determined, for example, based on the history of various information accumulated in the storage unit 16. For example, when the history of the user's exercise or movement by a moving object indicates that the user has not gone out for a predetermined period of time, the destination proposal processing unit 15 can propose a destination at that timing.

[0050] Furthermore, the proposed destination may be either a destination reached by travelling on a mobile object or a destination reached by movement without using a mobile object, or may be either a destination that is determined in advance or that is specified by the user.

[0051] For example, the destination proposal processing unit 15 reads map data pre-stored in the memory unit 16 based on the current location, reads the set upper limit, and determines the proposed destination based on the current location and the upper limit. The destination proposal processing unit 15 then causes the display unit 18 to display the destination on a map indicated by the map data. A navigation system may be used to display such a map. The destination proposal processing unit 15 may output the proposed destination as a voice from a voice output unit (not shown).

[0052] The proposed destination may be, for example, a place suitable for walking, such as a park or a promenade, or a place where people can interact, such as a senior citizen facility, an entertainment facility, or a facility where an event is held. In any case, the proposed more specific destination may be the entrance of the facility, the closest point to the current position in the facility, or, in the case of movement by a mobile object, a point in the facility where the mobile object can be parked.

[0053] In this way, the destination proposal processing unit 15 can present, as destinations, facilities that can be reached within an upper limit of, for example, 30 minutes from a current location such as a home. In particular, the proposed destinations should be facilities that are easy to stop by, such as parks, or facilities that the user would like to stop by. In addition, the destination proposal processing unit 15 may obtain the user's preferences by user specification or a machine learning learning model, and determine the genre of the proposed destination or the facility of the proposed destination based on the user's preferences.

[0054] The destination proposal processing unit 15 may also propose not only the destination but also the type of moving object or the type of exercise. The destination proposal processing unit 15 may also obtain weather forecast information predicting the current weather or the weather from the current weather to the upper limit from an external server device via the communication unit 20, and change the destination, or the destination and the moving object or the type of exercise, depending on the obtained weather.

[0055] The destination suggestion processing unit 15 may also suggest destinations by presenting multiple candidate destinations. This allows the user to select one destination from the multiple proposed destinations based on the weather, the user's physical condition, mood, and the like, and travel to that destination. Thus, by including the destination suggestion processing unit 15, the index calculation device 1 can stop the user from staying confined or withdrawn into the house and encourage the user to go out.

[0056] Furthermore, when the destination proposal processing unit 15 proposes a type of moving object or a type of travel, or proposes multiple candidate destinations, it reads out, for example, a UI (User Interface) image pre-stored in the storage unit 16. Then, the destination proposal processing unit 15 may embed the proposed content in the UI image and overlay it on the map.

[0057] The destination proposal processing unit 15 can also vary the proposed destination based on one or more of the various types of history as described above. For example, the destination proposal processing unit 15 can vary the proposed destination or the timing of the proposal based on the change in the daily behavior index accumulated as history. More specifically, if the change in the daily behavior index shows a recent tendency of a decrease in the behavior index, the destination proposal processing unit 15 can propose a destination that will increase the amount of exercise, or conversely, can propose a destination that will decrease the amount of exercise to make the proposal easier to accept. In these examples, the proposed destination is varied by referring to the past history. This allows the proposed destination to be determined based on the user's past behavioral patterns.

[0058] Varying the proposed destinations may include, for example, varying the type of facility, such as whether it is a park or an entertainment facility. However, the destination proposal processing unit 15 may vary the upper limit for searching destinations depending on the history, for example, by varying a coefficient for adding to or multiplying the set upper limit based on the history. In either example, the destination proposal processing unit 15 may determine the proposed destinations using a learning model obtained by machine learning.

[0059] The control unit 10 of the index calculation device 1 may allow the user to view one or more of the various types of histories described above. The user can view this history on the display unit 18 or an audio output unit (not shown) by operating the operation unit 17. The user can also view this history while moving on a moving object or while exercising without using a moving object, thereby grasping information such as the amount of exercise of the user in real time.

[0060] Next, an example of an index calculation process executed by the index calculation device 1 will be described with reference to Figs. 2 to 5. Fig. 2 is a flow diagram for explaining this example of the index calculation process. Fig. 3 is a schematic diagram showing an example of an environment in which the index calculation device 1 is used. Fig. 4 is a schematic diagram showing an example of a destination proposal image displayed on the index calculation device 1. Fig. 5 is a schematic diagram showing an example of an index display image displayed on the index calculation device 1.

[0061] Here, an example will be described in which the index calculation device 1 is used in an environment as shown in Fig. 3. First, the destination proposal processing unit 15 proposes one or more destinations based on the set upper limit of movement and the current location of the user U (step S1). The current location of the user U at this point is assumed to be the home shown in Fig. 3 as the starting point.

[0062] At this time, the destination recommendation processing unit 15 may display a guide image 18b on the display unit 18 as exemplified in Fig. 4. The guide image 18b may include a current location 18c and a route 18d with the destination shown on a map indicated by the map data. At this time, as exemplified in Fig. 4, the display unit 18 may display a guidance start button 18e and may also display an event history display button 18a that is not selectable. Note that Fig. 4 shows an example in which the index calculation device 1 is equipped with a front camera 22a as an example of the imaging unit 22.

[0063] If this suggestion is followed, the user U will select a destination from the operation unit 17 and select the guidance start button 18e. When only one destination is proposed, as in the example of Fig. 4, the selection of the guidance start button 18e means approval of the proposed destination. The control unit 10 determines whether or not a destination has been selected by the user U based on the operation of the operation unit 17 (step S2), and if a selection has been made (YES), sets the destination and starts guidance to the destination (step S3).

[0064] As shown in Fig. 3, the user U sits in the senior car M and heads to the destination. At this time, the index calculation device 1 can be attached to the senior car M so that the user U can easily see. The index calculation device 1 also displays the current position and the route to the destination on a map during this movement, and continues to guide the user to the destination. The following description will be given on the assumption that the information acquisition processing unit 11 is obtaining position information from the position information acquisition unit 19 during guidance.

[0065] Furthermore, the information acquisition processing unit 11 starts acquiring event information by requesting the voice input unit 21 and the imaging unit 22 to acquire voice and capture images, respectively, at the start of the guidance (step S4). In step S4, the information acquisition processing unit 11 also starts acquiring movement information by storing the position information acquired by the position information acquisition unit 19 in the storage unit 16.

[0066] Next, the information acquisition processing unit 11 determines whether or not the destination has been reached based on the location information from the location information acquisition unit 19 (step S5). The information acquisition processing unit 11 waits for arrival (if YES in step S5), and ends acquisition of event information by requesting the audio input unit 21 and the imaging unit 22 to stop acquiring audio and capturing images (step S6). In step S6, the information acquisition processing unit 11 also ends acquisition of movement information by stopping storage of the location information acquired by the location information acquisition unit 19.

[0067] The information acquisition processing unit 11 calculates movement information from the difference between the position information acquired in step S4 and step S6, and passes it to the exercise amount calculation processing unit 12, which then calculates the amount of exercise based on the movement information (step S7).

[0068] During steps S4 to S6, the information acquisition processing unit 11 detects events from the acquired sounds and images, and stores event information about the detected events in the storage unit 16. The event information may be stored together with or including at least one of time information indicating the date and time and location information indicating the location where the event occurred.

[0069] Due to such accumulation, the information acquisition processing unit 11 causes the display unit 18 to selectably display an event history display button 18a in Fig. 4. When the user U selects the event history display button 18a, the accumulated events are displayed on the route 18d. Fig. 5 shows a state in which the user U selects the event history display button 18a at the time when the user U reaches the destination. It can be seen that the event history display button 18a switches to an event history hide button 18ad, and each event acquired for the user U is displayed at the event occurrence point on the route 18d.

[0070] The example of FIG. 5 shows a case where events A, B, C, and D occur while a user U is traveling to a destination in a senior car M. Here, an example is given in which event A refers to a conversation with a neighbor, event B refers to using stairs, event C refers to meeting a dog, and event D refers to discovering a plant such as a flower. It can be seen that the occurrence points of each of the events A to D are displayed together with illustrations or marks representing each of the events A to D. Instead of illustrations or marks, characters may be used, or a thumbnail of an image actually captured by the imaging unit 22 may be used. Also, when an illustration or mark is displayed, the illustration or mark may be automatically generated from the image or its thumbnail.

[0071] By viewing the details of such an event, user U can not only recall the excitement, but can also be reminded of the fact that he or she has made the move, which can give the user a sense of accomplishment and motivate them to make the next move.

[0072] As described above, by storing event information together with at least one of time information and location information, when displaying the contents of the event, the event can be displayed on the map with at least one of text and illustration, making it easier for the user to view. Although not shown in FIG. 5, the time may also be displayed at the event occurrence point. This makes it possible to easily display the contents of the event on the map, such as at what time on what date, talking to a neighbor at point a, using the stairs at point b, meeting a dog at point c, finding a flower or other plant at point d, and so on.

[0073] 5, the movement distance, movement time, and road surface feel index among the movement amounts calculated in step S7 are also displayed as information 18AE together with the date as values ​​that are easy for the user U to understand. When displaying the movement amount calculated in step S7 as in this example, it is easy for the user U to understand if the movement distance and movement time are displayed among the values ​​calculated as the movement amount. Of course, the values ​​of other calculated movement amounts can also be displayed.

[0074] Next, the index calculation processing unit 13 calculates the user's behavior index based on the amount of exercise and the event information (step S8).

[0075] For example, let us assume that, when the above-mentioned events A to D occur, event B is defined as an event that gives a feeling of fatigue, while events A, C, and D are defined as events that give a feeling of elation to the user. In this case, for example, if the rank is calculated by giving a rank of -1 to the event that gives a feeling of fatigue and a rank of +1 to the event that gives a feeling of elation, the rank will be +2.

[0076] In step S8, the index calculation processing unit 13 may, for example, first calculate a behavior index of the user U based on the amount of exercise, correct the value by the rank indicated by the event information + 2, and calculate a final behavior index of the user U. For example, if the target daily behavior index is 100, the behavior index based on the amount of exercise is calculated to be 48, and the behavior index corresponding to the rank indicated by the event information + 2 is rank x k, where k = 6, the behavior index of the user U is 60. Of course, the calculation formula for the behavior index is not limited to this.

[0077] The calculated behavior index may be presented to the user U as illustrated as behavior index 18IN in Fig. 5. This completes the index calculation process.

[0078] In this case, the processing example has been described only for the case where the user is moving by a moving object. However, even if the user is exercising without using a moving object, such as a user 1w who has an index calculation device 1w having the same function as the index calculation device 1 shown in Fig. 3, the calculation method of the amount of exercise is basically the same, although it is different.

[0079] The first embodiment has been described above. In the index calculation device 1 according to the present embodiment, when the user moves, the behavior index can be calculated as an index of the behavior that takes into account not only fatigue due to the amount of physical exercise but also mental fatigue. In addition, this behavior index can be presented to the user as an index of daily behavior. In addition, by storing this behavior index as history, the user can judge the daily behavior from the past history and improve the motivation for the behavior after viewing it. That is, in this embodiment, by presenting the behavior index as described above, the user can be motivated to solve the lack of exercise, the decrease in opportunities to interact with others, and the decrease in the time spent going out. In addition, in this embodiment, by storing the behavior index and other history, the moving experience can be stored as history for the movement by a moving object or the exercise without a moving object, even if it is a short movement or a short walk. As a result, the user can feel that he is being supported by checking the history, and can get a sense of accomplishment by confirming the fact that he went out.

[0080] In this embodiment, the age of the target user is not an issue, but for the reasons described above, this embodiment is particularly beneficial for users who need measures to prevent frailty, such as senior users, and can prevent such users from becoming ill or becoming isolated, including various illnesses such as depression.

[0081] For the same reason, in this embodiment, the configuration is such that a destination for travel using a moving object is also proposed, making it possible to make a proposal that can resolve the decrease in the frequency of users going out. Therefore, with such a configuration, the index calculation device 1 can encourage users who do not go out much to go out, prevent them from staying indoors or staying at home, encourage them to change their mood, and resolve lack of exercise, that is, support or encourage them to go out and exercise. This is because senior users in particular find it troublesome to walk independently, are prone to lack of exercise, feel guilty about traveling by moving object such as a senior car, and feel like they want to drive themselves even after returning their license. In this way, it can be said that this embodiment can provide a health promotion effect, especially for seniors. In addition, in this embodiment, the proposal of travel to a public facility as a proposal for exercise also leads to promotion of use of the public facility.

[0082] <Embodiment 2> The index calculation device according to the second embodiment will be described with reference to Figures 6 and 7, focusing on the differences from the first embodiment, but the various examples described in the first embodiment can also be applied. Figure 6 is a block diagram showing a configuration example of an index calculation system including the index calculation device according to the second embodiment.

[0083] 6, an index calculation device 1a according to this embodiment includes a control unit 10a instead of the control unit 10 in the index calculation device 1. Here, the control unit 10a includes an information acquisition processing unit 11a and an activity amount calculation processing unit 12a instead of the information acquisition processing unit 11 and the activity amount calculation processing unit 12 in the control unit 10, respectively. Furthermore, the index calculation device 1a is connected to a biometric information acquisition device 3 via a communication unit 20, and configures an index calculation system together with the biometric information acquisition device 3.

[0084] The biometric information acquisition device 3 is a device that acquires biometric information of a user. The biometric information acquisition device 3 may include a control unit 30 that controls the entire device, a sensor unit 31, and a communication unit 32. The sensor unit 31 includes one or more sensors that acquire biometric information of the user. The sensor included in the sensor unit 31 detects biometric information that can determine or estimate the user's degree of fatigue, excitement, tension, etc. from the detection result or a change over time in the detection result. Such biometric information may include one or more of various information such as pulse, body temperature, respiratory rate, brain waves, and cerebral blood flow. The biometric information may also be referred to as vital information. Feelings such as excitement, tension, or elation may be determined, for example, from cerebral blood flow and heart rate fluctuation. Emotions of elation may also be referred to as excitement, and may be expressed as a degree of elation.

[0085] The communication unit 32 communicates with an external device such as the index calculation device 1a. The communication unit 32 may be, for example, a communication unit that communicates in accordance with a short-range wireless communication standard such as Bluetooth LE, or a communication unit that communicates in accordance with a wireless communication standard such as WiFi.

[0086] The control unit 30 instructs the sensor unit 31 to detect biometric information in accordance with instructions received from the index calculation device 1a via the communication unit 32, or independently, and obtains the detection results and transmits them to the index calculation device 1a via the communication unit 32.

[0087] The bioinformation acquisition device 3 may be, for example, a wearable device such as a smart watch or an in-ear wearable device. However, the bioinformation acquisition device 3 may also be a non-wearable device equipped with a camera to detect bioinformation. An in-ear wearable device refers to a device that is worn on the ear and can detect cerebral blood flow rate, etc., using an optical sensor, and can also detect the standing state of the user by further including an acceleration sensor. The bioinformation acquisition device 3 may also be incorporated into the index calculation device 1a, in which case a smart device such as a smart watch may be used as the index calculation device 1a.

[0088] The information acquisition processing unit 11a acquires movement information in the same manner as the information acquisition processing unit 11. Furthermore, the information acquisition processing unit 11a also acquires biometric information of the user acquired by the biometric information acquisition device 3 via the communication unit 20. The information acquisition processing unit 11a can also accumulate the acquired biometric information in the storage unit 16 as history.

[0089] The information acquisition processing unit 11a acquires biometric information acquired by the biometric information acquisition device 3 at least at the start of the movement of the moving body toward the destination and at the destination after the movement, and calculates the difference between them. Note that the difference between the biometric information before and after the movement can be calculated by the biometric information acquisition device 3 and acquired by the information processing acquisition unit 11a. The information acquisition processing unit 11a passes the above difference to the exercise amount calculation processing unit 12a.

[0090] The exercise amount calculation processing unit 12a calculates the amount of exercise based on information indicating the difference in biological information before and after the user's movement, which is received from the information acquisition processing unit 11a. There is no restriction on the method of calculating the amount of exercise based on the difference in biological information, but for example, it can be calculated based on the movement information and the difference in information regarding fatigue, such as pulse rate and body temperature, before and after the user's movement. For example, when the pulse rate after the user's movement shows an increase of a predetermined value or more compared to the pulse rate before the user's movement, the exercise amount calculation processing unit 12a calculates that the user's exercise intensity due to the movement is high, which has caused the pulse value to increase, and therefore the amount of exercise of the user is high. The amount of exercise of the user may be calculated in several stages, such as exercise amount levels 0 to 3.

[0091] Further, the information acquisition processing unit 11a calculates information indicating the degree of excitement caused by the event as at least a part of the event information based on information indicating the difference between the biological information before and after the occurrence of the event. The degree of excitement caused by the event can be calculated based on, for example, the difference between the cerebral blood flow, the pulse rate, etc. before and after the occurrence of the event, although the calculation method is not limited thereto. For example, when the pulse rate after the detection of the event shows an increase of a predetermined value or more compared to the pulse rate before the detection of the event, the information acquisition processing unit 11a calculates the information indicating the user's excitement as high, assuming that the user's excitement caused by the event is high and the pulse value has increased as a result. The information indicating the user's excitement may be calculated in several stages, such as excitement levels 0 to 3.

[0092] The information acquisition processing unit 11a detects events, more specifically, detects events with high excitement levels based on the information indicating the calculated excitement levels, and generates event information. Alternatively, the information acquisition processing unit 11a ranks each of the events detected from other information based on the information indicating the calculated excitement levels, and generates information with excitement levels as event information.

[0093] Note that the bioinformation can be used for only one of the calculation of the amount of exercise and the calculation of the event information. Also in this embodiment, the index calculation device 1a can include a destination proposal processing unit 15. In the destination proposal processing unit 15 in this embodiment, the proposed destination can be changed based on the history of the movement information, etc., but instead of or in addition to this, the proposed destination can be changed based on the history of the bioinformation.

[0094] Next, an example of the index calculation process executed by the index calculation device 1a will be described with reference to Fig. 7. Fig. 7 is a flow chart for explaining this example of the index calculation process.

[0095] Here again, an example will be described in which the index calculation device 1a is used in the environment shown in Fig. 3. First, similar to steps S1 to S3 in Fig. 2, the index calculation device 1a suggests a destination using the senior car M, and starts guidance to the destination if the suggestion is accepted (steps S11 to S13).

[0096] At the start of the guidance, the information acquisition processing unit 11a starts acquiring movement information and event information, as in step S4, and also starts acquiring biometric information by requesting the biometric information acquisition device 3 to acquire biometric information via the communication unit 20 (step S14).

[0097] Next, the information acquisition processing unit 11a determines whether or not the destination has been reached based on the location information from the location information acquisition unit 19 (step S15). The information acquisition processing unit 11a waits for arrival (if YES in step S15), and ends acquisition of movement information and event information in the same manner as in step S6, and ends acquisition of biometric information by requesting the biometric information acquisition device 3 to stop acquisition (step S16).

[0098] The information acquisition processing unit 11a calculates movement information from the difference between the position information acquired in step S14 and step S16, calculates the difference between the bioinformation acquired in step S14 and step S16, and passes it to the exercise amount calculation processing unit 12a (step S17). When the information acquisition processing unit 11a has obtained an image of the user's facial expression captured by the camera 22a in steps S14 to S16, it may analyze the change in facial expression as the difference in the bioinformation, and may convert the change into a numerical value as a change in fatigue level or elation level, and may use this as the difference or include it as one piece of information on the difference.

[0099] In step S17, the exercise amount calculation processing unit 12a further calculates the exercise amount based on the difference between the movement information and the biological information. In addition, in step S17, the information acquisition processing unit 11a may generate or modify event information, such as by giving an excitement level rank based on the difference between the biological information.

[0100] Next, the index calculation processing unit 13 calculates the user's behavior index based on the amount of exercise and the event information (step S18), similarly to step S8, and ends the process.

[0101] The above describes the embodiment 2. As described above, in the embodiment, in addition to the effects of the embodiment 1, it is possible to calculate an activity index based on a change in the biometric information of the user before and after movement on a moving object.

[0102] In addition, the index calculation device 1a according to this embodiment can suggest movement based on the behavior index reflecting the difference in biological information, or may instead directly suggest movement based on the difference. In this case, movement is basically suggested to people who do not exercise. However, the index calculation device 1a according to this embodiment can be similarly applied to a case where a person who exercises excessively or a person with a disease such as heart disease is suggested to suppress movement such as exercise. In this case, the index calculation device 1a may suggest a destination that can be reached in a time corresponding to the actual fatigue level, or suggest movement by a moving object, or present a sentence that suppresses exercise. Such a sentence may be, for example, "You seem tired, so let's limit your movement to about 5 minutes today." In addition, even when suppressing such exercise, a suggestion for movement may be made based on the amount of exercise accumulated as a history.

[0103] <Embodiment 3> The index calculation device according to the third embodiment will be described with reference to Figures 8 to 13, focusing on the differences from the second embodiment, but the various examples described in the first and second embodiments can also be applied. Figure 8 is a block diagram showing a configuration example of an index calculation system including the index calculation device according to the third embodiment.

[0104] As shown in Fig. 8, the index calculation device 1b according to this embodiment includes a control unit 10b instead of the control unit 10a in the index calculation device 1a. Here, the control unit 10b includes an information acquisition processing unit 11b and an activity amount calculation processing unit 12b instead of the information acquisition processing unit 11a and the activity amount calculation processing unit 12a in the control unit 10a, respectively. The control unit 10b also includes a decision processing unit 23 and a proposal processing unit 24.

[0105] The momentum calculation processing unit 12b may calculate the first momentum and the second momentum, and calculate the momentum based on them. The first momentum and the second momentum correspond to the moving body momentum and the non-moving body momentum, respectively, but the range of movement that is the subject of the momentum calculation is different.

[0106] The first amount of exercise refers to an amount of exercise generated by the user due to movement on a moving object, based on information indicating at least one of a distance and a time traveled by the moving object to a destination by the moving object boarded by the user, as the movement information. The second amount of exercise refers to a second amount of exercise generated by the user due to the exercise, based on information indicating at least one of a distance and a time traveled by the user from a destination by the moving object to a destination by the moving object and without using the moving object, as the movement information. The exercise amount calculation processing unit 12 calculates the amount of exercise, for example, by adding the first amount of exercise and the second amount of exercise with a predetermined weight.

[0107] Then, the index calculation processing unit 13 calculates the user's final behavior index for a series of movements based on the amount of exercise calculated for the series of movements in this manner and the detected event information.

[0108] Although a detailed description of the above-mentioned first amount of exercise is omitted, the index calculation device 1b can obtain the amount of exercise by performing processing for a case where the destination proposed by the destination proposal processing unit 15 is set as the arrival point, by the exercise amount calculation processing unit 12b. Alternatively, although a detailed description of the above-mentioned first amount of exercise is also omitted, the index calculation device 1b can obtain the amount of exercise by performing processing for a movement voluntarily performed by the user using a moving object, by the exercise amount calculation processing unit 12b.

[0109] Although a detailed description of the second exercise amount described above will be omitted, the index calculation device 1b can obtain the second exercise amount by the exercise amount calculation processing unit 12b by having the user voluntarily perform an exercise without using a moving object after the user has moved using the moving object.

[0110] Alternatively, the above-mentioned second amount of exercise can be calculated as the amount of exercise performed according to a proposal of an exercise that does not use a moving object, which is proposed by the index calculation device 1b after the user moves by a moving object and arrives at a destination, based on the behavior index of the movement. For such a proposal, the control unit 10b includes a decision processing unit 23 and a proposal processing unit 24, which will be described next.

[0111] The determination processing unit 23 constitutes the next determination unit together with the storage unit 16, for example. The determination unit determines the predetermined time based on the behavior index calculated for the movement to the destination using the moving object. For example, the determination processing unit 23 acquires the behavior index from the index calculation processing unit 13 or the storage unit 16, and determines the predetermined time by referring to information previously stored in the storage unit 16 as a correspondence table or the like based on the behavior index and reading out the predetermined time corresponding to the behavior index. Alternatively, the determination processing unit 23 may determine the predetermined time by substituting the behavior index into a predetermined calculation formula. A learning model generated by machine learning may be used for such a determination. The determination processing unit 23 passes the determined predetermined time to the proposal processing unit 24.

[0112] The determination processing unit 23 may determine the predetermined time based on not only the behavior index but also other information. The other information here may be, for example, information used in the calculation of the behavior index, which allows the target information to be more reflected in the determination of the predetermined time. In other words, the other information may include any one or more of the following regarding the movement to the destination using a moving body: movement information, driving status, the first movement amount which is the amount of movement, the difference in bioinformation, the rank of event information, and the like. For example, the difference in the bioinformation described above indicates the degree of fatigue and the degree of elation which are the physical burden on the user due to the movement by the moving body, so that the exercise can be proposed in consideration of the degree of fatigue and the degree of elation determined from the change in the bioinformation before and after the movement by the moving body. For example, if the user has a low degree of fatigue or has a sense of elation, the user is more likely to accept and exercise even if the recommendation to exercise for a long time is given. The other information may also include any one or more of the history of the past behavior index and the history of various other information.

[0113] The suggestion processing unit 24 constitutes the next suggestion unit together with, for example, the storage unit 16 and the display unit 18. The suggestion unit suggests to the user to exercise without using a moving object for a predetermined time or more after arrival at the destination. This suggestion unit can be called an exercise suggestion unit because it suggests exercise to the user. The timing of suggesting exercise can be determined, for example, based on the history of various information accumulated in the storage unit 16. For example, when the history of exercise without using a moving object for the user indicates that the cumulative behavior index for a predetermined period is insufficient, the suggestion processing unit 24 can suggest exercise after movement with a moving object, and conversely, when the cumulative behavior index is sufficient or excessive, it can not suggest exercise after movement with a moving object.

[0114] In addition, since this suggestion is a suggestion to exercise for a predetermined time or more, the predetermined time can be said to be a threshold for the suggestion. Note that this exercise can be walking, running, etc., but it may also be a type of exercise that does not involve movement, such as calisthenics.

[0115] For example, the suggestion processing unit 24 makes a suggestion by reading a UI image stored in advance in the storage unit 16, embedding the predetermined time received from the decision processing unit 23 in the UI image, and displaying it on the display unit 18. When making a suggestion of a type of exercise, it is preferable to include the type of exercise to be suggested in the UI image.

[0116] The suggestion processing unit 24 can, for example, select a destination where exercise for a predetermined time or more determined based on the acquired behavior index can be performed from the arrival destination, that is, a destination that provides an appropriate behavior index from the arrival destination, and present the destination on the display unit 18. In order to present the destination, the suggestion processing unit 24 may read map data previously stored in the memory unit 16, and display the destination on the display unit 18 with the map indicated by the map data.

[0117] For example, the suggestion processing unit 24 suggests other destinations within a predetermined time that can ensure the overall activity index, or other destinations within a predetermined time that can keep the overall activity index below a predetermined upper limit, taking into consideration the increase in fatigue caused by travelling in a mobile body such as a senior car. Specifically, the suggestion processing unit 24 suggests destinations that can be reached by 10 minutes of walking if the user has travelled for 20 minutes in the senior car, and suggests destinations that can be reached by 15 minutes of walking if the user has travelled for 10 minutes in the senior car.

[0118] Conversely, the proposal processing unit 24 may propose a destination with a time ratio that maintains the ratio between the behavior index of driving in the senior car and the behavior index of walking. Specifically, the proposal processing unit 24 proposes a destination that can be reached by 10 minutes of walking after the user has driven the senior car for 20 minutes, and proposes a destination that can be reached by 5 minutes of walking after the user has driven the senior car for 10 minutes.

[0119] In addition, the suggestion processing unit 24 may obtain weather forecast information predicting the current weather or the weather up to the time when the above-mentioned specified time has elapsed from the current weather from an external server device via the communication unit 20, and change the suggested destination depending on the obtained weather.

[0120] Of course, the proposal processing unit 24 may propose a time for exercise such as walking, or a time and a type of exercise, instead of a destination. The proposal processing unit 24 may change the content of the proposal depending on the user's age, the user's health condition, and whether the moving object is a senior car or the back seat of another type of vehicle. The proposal candidates may be set by the user. The proposal processing unit 24 may make a proposal using a learning model generated by machine learning. In particular, by making a proposal using a learning model machine-learned on a data set including information on the user's personal proposal acceptance, a proposal specialized for the user can be made.

[0121] Furthermore, the proposal processing unit 24 can vary the content of the proposed exercise based on the behavior index or the like, similar to the example described as the destination proposal by the destination proposal processing unit 15. Note that, similar to the destination proposal processing unit 15, the proposal processing unit 24 may output the content of the proposal as sound from the sound output unit.

[0122] In addition, the suggestion processing unit 24 may suggest to the user to exercise without using the mobile body after the mobile body arrives at the destination as the arrival point, but may also determine the content of the suggestion based on information obtained up to that point, such as a predetermined time before arrival, and make the suggestion.

[0123] In the above, an example has been given in which the index calculation device 1b includes the determination processing unit 23 that determines the predetermined time. However, the index calculation device 1b may not include the determination processing unit 23, and the suggestion processing unit 24 may suggest to the user an exercise that does not use a moving object based on the acquired behavior index or the behavior index and other information.

[0124] Furthermore, the user can respond from the operation unit 17 as to whether or not to accept the exercise proposed by the proposal processing unit 24. The proposal processing unit 24 may simultaneously propose multiple types of candidates, such as multiple destinations. In this case, the user can respond as to which proposal to accept from among the multiple types of candidates.

[0125] In addition, when the user performs an exercise suggested by the suggestion processing unit 24, the control unit 10 may store the history in the memory unit 16 without distinguishing between the suggested exercise and exercise unrelated to the suggestion, or may store the history by distinguishing between the suggested exercise and exercise unrelated to the suggestion.

[0126] With the above configuration, the index calculation device 1b can suggest an appropriate behavior index or time of exercise to the user of the moving body after moving with the moving body. Therefore, the index calculation device 1b can recommend to the user exercise such as moderate walking when going out, that is, to resolve lack of exercise. The index calculation device 1b can be called a behavior support device because it supports the user's behavior by suggesting exercise to the user in this way.

[0127] Moreover, the index calculation device 1b can perform such two-stage proposals by including the destination proposal processing unit 15 and the proposal processing unit 24. Therefore, with this configuration, the index calculation device 1b can encourage users who do not go out much to go out, prevent them from staying indoors or staying at home, encourage them to change their mood, and eliminate lack of exercise, that is, support or encourage them to go out and exercise.

[0128] Next, an example of index calculation processing executed by the index calculation device 1b according to the present embodiment will be described with reference to Figs. 9 to 13. Fig. 9 is a flow diagram for explaining this example of index calculation processing. Fig. 10 is a schematic diagram showing an example of the location of an event detected by the index calculation processing in an example of an environment in which the index calculation device 1b is used. Fig. 11 is a schematic diagram showing an example of an exercise suggestion image displayed in the index calculation device 1b. Fig. 12 is a schematic diagram showing an example of an exercise suggestion image displayed when an event history display operation is performed from the exercise suggestion image of Fig. 11 in the index calculation device 1b. Fig. 13 is a schematic diagram showing an example of an index display image displayed in the index calculation device 1b.

[0129] Here, an example will be described in which the index calculation device 1b is used in an environment as shown in Fig. 10. Note that Fig. 10 shows an example of the same environment as Fig. 3 from the departure point to the destination. First, similar to steps S11 to S18 in Fig. 7, the index calculation device 1b proposes a destination using the senior car M, starts guidance to the destination when the proposal is accepted, calculates the behavior index of the user U during the movement, and so on (steps S21 to S28).

[0130] Next, the determination processing unit 23 acquires the user's behavior index calculated from the index calculation processing unit 13, determines a predetermined time based on the behavior index, etc., and passes the predetermined time to the proposal processing unit 24 (step S29). In step S29, the proposal processing unit 24 further proposes to the user U to exercise without using the senior car M for a predetermined time or more from the current time, which is the time of arrival at the destination. As a proposal method, for example, it is preferable to display a proposal image 18g as a pop-up image or the like so as not to overlap or to overlap the guidance image 18b, as in the UI image shown in the display unit 18 of FIG.

[0131] Here, the proposed image 18g is an example including a sentence such as "You have arrived at the destination. Since you are here, let's walk to the nearby park P (it takes about 10 minutes)." However, the contents of the proposal are not limited to this. For example, three destinations, namely, point A, point B, and park P shown in FIG. 10, may be proposed as destinations, or only two of them may be proposed. Here, when the predetermined time is determined to be, for example, 9 minutes, walking to park P is proposed among points A, B, and park P, which take 8 minutes, 6 minutes, and 10 minutes, respectively. Note that the guide image 18b in FIG. 11 shows the destination as park P in the guide image 18b in FIG. 4, and can display the route 10d to park P, a guide end button 18f, and a guide resume button 18h.

[0132] Also, the guide image 18b in Fig. 11 includes an event history display button 18a. When the user U selects this event history display button 18a, for example, as in the guide image 18b in Fig. 12, the map is reduced and the route of travel using the senior car M so far and event information that occurred along the route are also displayed. Also, the guide image 18b in Fig. 12 also displays an event history hide button 18ad, and when the user U selects this event history hide button 18ad, the display can be switched to the guide image 18b in Fig. 11.

[0133] 11 or 12 is displayed, the control unit 10b determines whether the user U has accepted the proposal based on whether the user U has selected the resume guidance button 18h or the end guidance button 18f (step S30). If the control unit 10b determines that the resume guidance button 18h has been selected and the proposal has been accepted (YES in step S30), it performs control to start guidance to park P (step S31). On the other hand, if NO in step S30, the process ends.

[0134] After step S31, the control unit 10b performs basically the same control as steps S24 to S28 (steps S32 to S36), and ends the process. However, in step S32, the start of acquisition of various information corresponds to the restart of acquisition, and the destination in step S33 is park P. Also, in step S36, a behavior index for a series of movements, that is, a behavior index for movements using a moving object and movements not using a moving object, or a behavior index for the sum of these, is finally calculated.

[0135] During steps S32 to S34, the information acquisition processing unit 11b accumulates event information in the storage unit 16, similarly to steps S24 to S26. For example, if events E and F occur as illustrated in Fig. 10 after the user U gets off the senior car M, event information regarding these events is accumulated in the storage unit 16. For example, event E may be meeting a cat, event F may be discovering trees, and so on, and the respective event information may be accumulated, and the locations and times of these events may also be included in the event information.

[0136] Due to such accumulation, after the user U arrives at the park P or when an event occurs, the information acquisition processing unit 11b causes the display unit 18 to display the event history display button 18a in a selectable manner as in FIG. 11. When the user U selects the event history display button 18a, the accumulated events are displayed on the route 18d. FIG. 13 shows a state in which the user U selects the event history display button 18a when he or she arrives at the park P. It can be seen that the event history display button 18a switches to the event history hide button 18ad, and each event including the events E and F acquired for the user U is displayed at the event occurrence point on the route 18d. Note that, when guidance is being provided with the event history display button 18a selected, event information for the event may be displayed at the time of the event occurrence.

[0137] As shown in Fig. 13, the calculated amount of exercise and action index are also displayed when the user U reaches the park P. In the example of Fig. 13, it can be seen that the travel distance and travel time indicated by the information 18AE in the example of Fig. 5 have increased by the amount of exercise without using the senior car M. In addition, in the example of Fig. 13, it can be seen that the value of the action index 18IN in the example of Fig. 5 has increased by the amount of exercise without using the senior car M. Note that the amount of exercise and action index can be calculated during the process, and the values ​​at the time of calculation may be displayed.

[0138] The third embodiment has been described above. As described above, in this embodiment, in addition to the effects of the first or second embodiment, after moving with the moving body, that is, when the user of the moving body is out and about, it is possible to suggest an exercise of an appropriate time or an action index to the user of the moving body. In this way, the index calculation device 1b can suggest two stages of exercise. Then, in the case where the user accepts the suggestion, the index calculation device 1b can calculate the action index for the exercise.

[0139] In addition, the index calculation device 1b according to this embodiment can suggest exercise after moving on a moving object based on the behavior index reflecting the difference in biological information, or alternatively, can directly suggest exercise after moving on a moving object based on the difference. In this case, exercise is basically suggested to people who do not exercise. However, the index calculation device 1b according to this embodiment can also be applied to cases where it is suggested to people who exercise excessively or people with diseases such as heart disease to suppress exercise after moving on a moving object.

[0140] (Alternative examples, etc.) The above-mentioned program includes a set of instructions (or software code) for making the computer perform one or more functions described in the embodiment when the program is loaded into the computer. The program may be stored in a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, the computer-readable medium or the tangible storage medium includes random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technology, CD-ROM, digital versatile disc (DVD), Blu-ray (registered trademark) disk or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may be transmitted on a transitory computer-readable medium or a communication medium. By way of example and not limitation, the transitory computer-readable medium or the communication medium includes electrical, optical, acoustic, or other forms of propagated signals.

[0141] The present disclosure is not limited to the above-mentioned embodiment, and can be appropriately modified within the scope of the present disclosure. For example, the index calculation device of the above-mentioned various examples may be configured as a system in which some of its functions are distributed to multiple devices. For example, the index calculation device may be configured to include an information processing device such as a smartphone or a smartwatch owned by a user, and a server device connected to the information processing device via a network and performing processing such as calculation of the behavior index. In addition, the behavior index calculated by the index calculation device of the above-mentioned various examples can be used for various purposes, such as an index for estimating stress in a health management device, without being limited to a proposal for movement by a moving object or a proposal for movement without a moving object.

[0142] This disclosure includes matters that contribute to the realization of the SDGs' goal of "creating sustainable urban and urban areas" and contributing to the safety and security of public facilities. [Explanation of symbols]

[0143] 1, 1a, 1b, 1w index calculation device 3 Biometric information acquisition device 10, 10a, 10b, 30 Control unit 11, 11a, 11b Information acquisition processing unit 12, 12a, 12b Momentum calculation processing unit 13. Index calculation processing unit 14 Setting processing section 15 Destination suggestion processing unit 16 Memory section 17 Control section 18 Display 19 Location information acquisition unit 20, 32 Communications Department 21 Audio input section 22 Imaging unit 22a Camera 23 Decision Processing Unit 24 Proposal Processing Unit 31 Sensor section M Mobile vehicle (senior car) U, Uw User

Claims

1. an exercise amount calculation unit that calculates an amount of exercise caused by the user based on movement information indicating the movement of the user; an event information acquisition unit that acquires event information indicating an event that has occurred while the user is moving; an index calculation unit that calculates a behavior index indicating a behavior of the user based on the amount of exercise and the event information; An index calculation device comprising:

2. a biometric information acquisition unit for acquiring biometric information of the user, The exercise amount calculation unit calculates the exercise amount based on information indicating a difference in the biological information before and after the movement of the user. The index calculation device according to claim 1 .

3. a biometric information acquisition unit for acquiring biometric information of the user, the event information acquisition unit calculates, as at least a part of the event information, information indicating a degree of excitement caused by the event, based on information indicating a difference between the biological information before and after the occurrence of the event; The index calculation device according to claim 1 or 2.

4. The exercise amount calculation unit Calculating a first momentum generated by the user due to movement in the moving body based on information indicating at least one of a movement distance and a movement time to a destination by the moving body in which the user is riding, as the movement information; Calculating a second amount of exercise generated by the user due to the exercise based on information indicating at least one of a distance and a time of an exercise performed by the user from the arrival point using the moving object to the exercise without using the moving object, as the movement information; Calculating the amount of exercise based on the first amount of exercise and the second amount of exercise. The index calculation device according to claim 1 or 2.

5. The computer Calculating an amount of exercise caused by the user based on movement information indicating the movement of the user; acquiring event information indicating an event that occurred during the movement of the user; Calculating a behavior index indicating a behavior of the user based on the amount of exercise and the event information. Index calculation method.

Images