Health improvement device, health improvement method, and health improvement program

Abstract

To appropriately encourage actions that improve the user's health. [Solution] The health improvement device according to this embodiment includes an acquisition unit 131, an activity determination unit 133, a location identification unit 134, and an output unit 135. The acquisition unit 131 acquires information about the railway used by the user and information about the user's sleep. The activity identification unit 133 identifies activities that improve the user's health level, which indicates the degree of the user's health, based on the sleep information acquired by the acquisition unit 131. The location identification unit 134 identifies locations in the area where the user travels, as identified from the railway information, that correspond to the activities identified by the activity identification unit 133. The output unit 135 outputs the activities identified by the activity identification unit 133 and the locations identified by the location identification unit 134.

Description

Technical Field

[0001] The present invention relates to a health improvement device, a health improvement method, and a health improvement program.

Background Art

[0002] Conventionally, there is known a technique (see, for example, Patent Document 1) in which various sensors acquire health information such as vital data of a user and provide the user with health-related advice and advertisements while observing time-series changes.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the prior art, there are cases where actions to improve the health state of a user cannot be appropriately encouraged. For example, in the prior art, since it is conceivable to recommend product links for Internet shopping to the user, there are few connections between the proposed advice and the user's real life, and it is assumed that the user may not execute the advice.

Means for Solving the Problems

[0005] To solve the above-mentioned problems and achieve the objective, the health improvement device of the present invention is characterized by comprising: an acquisition unit that acquires information about the railway used by the user and information about the user's sleep; an activity identification unit that identifies activities to improve the user's health level, which indicates the degree of the user's health, based on the sleep information acquired by the acquisition unit; a location identification unit that identifies a location in the area where the user travels, which is identified from the railway information, that corresponds to the activity identified by the activity identification unit; and an output unit that outputs the activity identified by the activity identification unit and the location identified by the location identification unit. [Effects of the Invention]

[0006] According to the present invention, it is possible to appropriately encourage actions that improve the user's health condition. [Brief explanation of the drawing]

[0007] [Figure 1] Figure 1 shows an example of a health improvement system using a health improvement device according to an embodiment. [Figure 2] Figure 2 is a block diagram showing an example configuration of a health improvement device according to an embodiment. [Figure 3] Figure 3 shows an example of data stored in the railway information storage unit according to this embodiment. [Figure 4] Figure 4 shows an example of data stored in the user information storage unit according to the embodiment. [Figure 5] Figure 5 shows an example of data stored in the factor information storage unit according to the embodiment. [Figure 6] Figure 6 shows an example of data stored in the activity information storage unit according to this embodiment. [Figure 7] Figure 7 shows an example of data stored in the location information storage unit according to this embodiment. [Figure 8] Figure 8 shows an example of the processing performed by the factor identification unit according to the embodiment. [Figure 9]Figure 9 shows an example of the processing of the factor identification unit according to the embodiment. [Figure 10] Figure 10 shows an example of the processing of the factor identification unit according to the embodiment. [Figure 11] Figure 11 shows an example of the processing performed by the activity identification unit according to the embodiment. [Figure 12] Figure 12 shows an example of the processing of the location identification unit according to the embodiment. [Figure 13] Figure 13 shows an example of the processing of the location identification unit according to the embodiment. [Figure 14] Figure 14 shows an example of the processing of the output unit according to the embodiment. [Figure 15] Figure 15 shows an example of the processing of the output unit according to the embodiment. [Figure 16] Figure 16 shows an example of the processing of the output unit according to the embodiment. [Figure 17] Figure 17 shows an example of the processing of the output unit according to the embodiment. [Figure 18] Figure 18 is a flowchart showing an example of the processing flow of a health improvement device according to an embodiment. [Figure 19] Figure 19 shows an example of a computer that implements the processing of the health improvement device according to the embodiment. [Modes for carrying out the invention]

[0008] The embodiments of the health improvement device, health improvement method, and health improvement program according to the present application will be described in detail below with reference to the drawings. However, these embodiments do not limit the health improvement device, health improvement method, and health improvement program according to the present application. Furthermore, in the drawings, identical parts are denoted by the same reference numerals, and redundant explanations are omitted as appropriate.

[0009] [Configuration of Health Improvement System 1] First, the configuration of the health improvement system 1 having the health improvement device 100 according to this embodiment will be described. FIG. 1 is a diagram showing an example of the configuration of the health improvement system according to the embodiment. As shown in FIG. 1, the health improvement system 1 includes a health improvement device 100, a railway information server 200, a sleep information server 300, and a terminal device 400, and each device is communicably connected via a network.

[0010] Regarding the form of the network shown in FIG. 1, each device may communicate via an arbitrary communication network such as the Internet, a LAN (Local Area Network), or a VPN (Virtual Private Network), regardless of whether it is wired or wireless. Note that the configuration shown in FIG. 1 is merely an example, and the specific configuration and the number of each device are not particularly limited.

[0011] The health improvement device 100 is an information processing device that identifies activities for improving the user's health and proposes them to the user, and is realized by a server device or a cloud system. For example, the health improvement device 100 supports the execution of activities for improving the user's health by identifying activities for improving the user's health and transmitting them to the terminal device 400 owned by the user.

[0012] The railway information server 200 is a server device owned by a railway company that provides information related to railways, and is realized by a computer, a cloud system, or the like. For example, the railway information server 200 receives a request from the health improvement device 100 and transmits information related to railways, such as the riding history and commuter pass information of the requested user, to the health improvement device 100.

[0013] [[ID=I6]]The sleep information server 300 is a server device owned by a company that performs sleep analysis of users and provides information related to sleep, and is realized by a computer, a cloud system, or the like. For example, the sleep information server 300 receives a request from the health improvement device 100 and transmits information related to the sleep of the requested user to the health improvement device 100.

[0014] The terminal device 400 is an information processing terminal owned by the user and can be implemented as a smartphone, tablet, or the like. For example, the terminal device 400 displays activity information transmitted from the health improvement device 100 on its display. The terminal device 400 also transmits information detected by various sensors, such as acceleration sensors and positioning sensors, installed in its own device, to the health improvement device 100. Furthermore, the terminal device 400 transmits vital data, such as pulse rate data and respiratory data, measured by sensors in wearable devices or the like that are communicatively connected to its own device, to the health improvement device 100. In addition, the terminal device 400 transmits payment information using its own device to the health improvement device 100.

[0015] Next, the processing details of the health improvement device 100 according to this embodiment will be described. The health improvement device 100 acquires information about the railway used by the user and information about the user's sleep, and identifies activities that improve the user's health level, which indicates the degree of the user's health, based on the sleep information. Subsequently, the health improvement device 100 identifies locations in the area where the user travels, as identified from the railway information, that correspond to the activities that improve health. Then, the health improvement device 100 outputs the activities that improve health and the locations that correspond to the activities that improve health.

[0016] As a result, the health improvement device 100 outputs to the user's terminal device 400 activities that can improve the user's health, identified from railway-related information and sleep-related information, as well as locations within the area the user is traveling in where these activities can be performed. This allows the device to recommend activities that can be performed in locations that are close to the user and require minimal effort, thereby appropriately encouraging actions that improve the user's health.

[0017] [Configuration of Health Improvement Device 100] Next, an example of the functional configuration of the health improvement device 100 will be described. Figure 2 is a block diagram showing an example of the configuration of the health improvement device according to the embodiment. As shown in Figure 2, the health improvement device 100 has a communication unit 110, a storage unit 120, and a control unit 130.

[0018] The communication unit 110 is implemented, for example, by a NIC (Network Interface Card). For example, the communication unit 110 is connected to the railway information server 200 and the terminal device 400 via a network such as the Internet, enabling communication and information transmission and reception with each device.

[0019] The memory unit 120 is implemented by a storage device such as RAM (Random Access Memory) or a hard disk. The memory unit 120 stores data and programs necessary for various processes performed by the control unit 130. The memory unit 120 may also be implemented by a storage system installed outside the health improvement device 100. As shown in Figure 2, the memory unit 120 includes a railway information memory unit 121, a user information memory unit 122, a factor information memory unit 123, an activity information memory unit 124, and a location information memory unit 125. The individual parts of the memory unit 120 will be described below.

[0020] The railway information storage unit 121 stores information about the railway used by the user. For example, the railway information storage unit 121 stores information such as the user's commuter pass information and travel history. Here, with reference to Figure 3, the information stored by the railway information storage unit 121 will be explained. Figure 3 is a diagram showing an example of data stored by the railway information storage unit according to the embodiment. Figure 3(1) shows an example of commuter pass information stored by the railway information storage unit 121. Figure 3(2) shows an example of travel history information stored by the railway information storage unit 121.

[0021] As shown in Figure 3(1), the railway information storage unit 121 stores information for the following items: "No," "Section," "Period," "Classification," "Name," "Fare," "Address," and "Telephone Number." "No" indicates the identification number of the commuter pass. "Section" indicates the section covered by the commuter pass. "Period" indicates the period during which the commuter pass is valid. "Classification" indicates the classification of the commuter pass, such as for commuting or school. "Fare" indicates the fare of the commuter pass. "Name" indicates the name of the person covered by the commuter pass. "Address" indicates the address of the person covered by the commuter pass. "Telephone Number" indicates the telephone number of the person covered by the commuter pass.

[0022] For example, the railway information memory unit 121 stores the following information about the commuter pass "No:1": "Section: Omiya Station - Tokyo Station", "Period: **** / ** / **-**** / ** / **", "Classification: Commuter", "Fare: 83,160 yen", and the issuer of the commuter pass is "Name: ○○ Taro", "Address: Saitama City, Saitama Prefecture ******", and "Telephone number: 070-****-****".

[0023] Furthermore, as shown in Figure 3(2), the railway information storage unit 121 stores information for the following items: "No," "Date and Time of Boarding," "Boarding Station," "Date and Time of Alighting," "Alighting Station," and "Fare." "No" indicates the identification number of the boarding history. "Date and Time of Boarding" indicates the date and time the user passed through the ticket gate at the boarding station. "Boarding Station" indicates the station from which the user boarded. "Date and Time of Alighting" indicates the date and time the user passed through the ticket gate at the alighting station. "Alighting Station" indicates the station from which the user alighted. "Fare" indicates the fare from the boarding station to the alighting station.

[0024] For example, the railway information storage unit 121 stores information in the "No:1" ride history that the user boarded at "Departure Station: Tokyo Station" on "Date and Time of Departure: ** / ** **:**", alighted at "Alighting Station: Omiya Station" on "Date and Time of Alighting: ** / ** **:**", and paid "Fare: 580 yen".

[0025] The user information storage unit 122 stores information about the user. For example, the user information storage unit 122 stores the user's basic information and information about the user's sleep. The user's basic information includes, for example, attribute information such as the user's name, age, gender, and address. Information about the user's sleep includes, for example, information such as a sleep questionnaire, bedtime, wake-up time, sleep duration, lifestyle habits, and vital data. Lifestyle habits include, for example, information about the user's lifestyle, such as "meal times, eating habits, whether or not they exercise, and lifestyle." Note that information about bedtime, wake-up time, sleep duration, and lifestyle habits may be included in the sleep questionnaire. Furthermore, information about sleep may be estimated from data measured by a wearable device worn by the user.

[0026] Here, with reference to Figure 4, the information stored in the user information storage unit 122 will be described. Figure 4 is a diagram showing an example of data stored in the user information storage unit according to this embodiment. Figure 4(1) shows an example of basic user information stored in the user information storage unit 122. Figure 4(2) shows an example of information related to the user's sleep stored in the user information storage unit 122.

[0027] For example, as shown in Figure 4(1), the user information storage unit 122 stores information for items such as "No," "Name," "Age," "Gender," "Address," and "Occupation." "No" indicates the user's identification number. "Name" indicates the user's name. "Age" indicates the user's age. "Gender" indicates the user's gender. "Address" indicates the user's address. "Occupation" indicates the user's occupation. For example, the user information storage unit 122 stores the following information for user "No:1": "Name: Taro ○○," "Age: 38 years old," "Gender: Male," "Address: Omiya Ward, Saitama City, Saitama Prefecture *****," and "Occupation: Company employee."

[0028] Furthermore, as shown in Figure 4(2), the user information storage unit 122 stores information for each user in the form of items such as "No," "Question," and "Answer." "No" indicates the question number. "Question" indicates the content of the question. "Answer" indicates the user's answer to the question. For example, the user information storage unit 122 stores information such as "No: 1," "Question: I sleep well," and "Answer: No."

[0029] The factor information storage unit 123 stores information about factors that reduce (worsen) various health indicators of the user's health. Examples of health indicators include sleep quality, stress level, and fatigue level. For example, the factor information storage unit 123 stores "conditions and factors for identifying factors that reduce sleep quality," "conditions and factors for identifying factors that increase stress level," and "conditions and factors for identifying factors that increase fatigue level."

[0030] Here, with reference to Figure 5, the information stored by the factor information storage unit 123 will be explained. Figure 5 is a diagram showing an example of data stored by the factor information storage unit according to the embodiment. In Figure 5, "Conditions and Factors for Identifying Factors that Reduce Sleep Quality" will be explained as an example. For example, the factor information storage unit 123 stores information for items such as "Conditions" and "Factors". "Conditions" indicate the conditions for identifying factors. "Factors" indicate the factors that reduce the user's sleep quality, as identified from the conditions. For example, as shown in Figure 5, if the condition "Condition: The time from bedtime to wake-up time is less than 6 hours, and the user feels they have not slept well" is met, the factor information storage unit 123 stores the information "Factor: Short sleep duration".

[0031] The factor information storage unit 123 may store information where the symptoms of the disease are the "condition" and the disease name is the "factor". For example, as shown in Figure 5, the factor information storage unit 123 stores the information that "Factor: Sleep apnea syndrome" when the condition "The answer to the question 'Does breathing sometimes stop for 10 seconds or more while sleeping?' is 'yes'" is met. Note that although the above example shows "sleep apnea syndrome" as the factor, the condition and factor information that the factor information storage unit 123 stores is not limited to this.

[0032] The activity information storage unit 124 stores information about activities. For example, the activity information storage unit 124 stores factors that reduce health and activities to eliminate those factors. Now, with reference to Figure 6, the information stored by the activity information storage unit 124 will be explained. Figure 6 is a diagram showing an example of data stored by the activity information storage unit according to this embodiment.

[0033] For example, the activity information storage unit 124 stores information for the following items: "Factor," "Activity," and "Type." "Factor" indicates factors that reduce the user's health. "Activity" indicates activities to eliminate the factor. In addition to the content of the activity, "Activity" may also include information such as the recommended time for the activity and the effects of the activity. "Type" indicates the type of activity. For example, the activity information storage unit 124 stores information such as "Factor: Short sleep duration" followed by "Activity: Go to bed earlier, delay wake-up time," and "Type: Sleep." Also, the activity information storage unit 124 stores information such as "Factor: Sleep apnea syndrome" followed by "Activity: Visit a hospital," and "Type: Visit a doctor."

[0034] The location information storage unit 125 stores information about locations. For example, the location information storage unit 125 stores the address of each location, the types and content of activities that can be performed at each location, etc. Now, with reference to Figure 7, the information stored by the location information storage unit 125 will be explained. Figure 7 is a diagram showing an example of data stored by the location storage unit according to this embodiment.

[0035] For example, the location information storage unit 125 stores information such as "No," "Name," "Category," "Address," and "Type of Activity." "No" indicates the number assigned to each location. "Name" indicates the name of each location. "Category" indicates the category of facility each location is. "Address" indicates the address of each location. "Type of Activity" indicates the type of activity that can be performed at each location. Examples of "Type of Activity" include "Sleep" indicating an activity related to sleep, "Eating" indicating an activity related to eating, "Exercise" indicating an activity related to exercise, "Lighting" indicating an activity for dimming, and "Hospital" indicating an activity related to medical care. For example, the location information storage unit 125 stores information such as "Name: Restaurant," "Category: Restaurant," "Address: Shinbashi, Minato-ku, Tokyo ****," and "Type of Activity: Eating" for the location indicated by "No: 1." Although not shown in the diagram, the location information storage unit 125 may also store the costs incurred when activities are performed at each location, as well as information about the users who visited each location (such as visit history and how much the user liked the location).

[0036] Let's return to the explanation of Figure 2. The control unit 130 is realized by a processor such as an integrated circuit (CPU), MPU, ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Gate Array), etc., which executes various programs stored in the storage device inside the health improvement device 100 using RAM or the like as the working area. In the example shown in Figure 2, the control unit 130 has an acquisition unit 131, a factor identification unit 132, an activity identification unit 133, a location identification unit 134, an output unit 135, and an assignment unit 136. The following describes each part of the control unit 130.

[0037] The acquisition unit 131 acquires information about the railways used by the user and information about the user's sleep. For example, the acquisition unit 131 acquires railway-related information such as ride history and commuter pass information from the railway information server 200 and stores it in the railway information storage unit 121.

[0038] More specifically, the acquisition unit 131 acquires travel history information such as "Date and time of boarding: ** / ** **:**", "Boarding station: Tokyo Station", "Date and time of alighting: ** / ** **:**", "Alighting station: Tokyo Station", and "Fare: 580 yen" from the railway information server 200, as well as commuter pass information such as "Section: Omiya Station - Tokyo Station", "Period: **** / ** / **-**** / ** / **", "Classification: Commuter", "Fare: 83,160 yen", "Name: ○○ Taro", "Address: ****** Omiya Ward, Saitama City, Saitama Prefecture", and "Telephone number: 070-****-****", and stores it in the railway information storage unit 121.

[0039] Furthermore, the acquisition unit 131 acquires information related to the user's sleep, such as the user's basic information, a questionnaire about the user's sleep, and user sleep information, from the sleep information server 300 and stores it in the user information storage unit 122. More specifically, the acquisition unit 131 acquires basic user information such as "Name: Taro XX", "Age: 38", "Gender: Male", "Address: Omiya Ward, Saitama City, Saitama Prefecture *****", "Occupation: Company employee", and information from the sleep information server 300, such as "Q. Are you sleeping well?: A. No", and stores it in the user information storage unit 122.

[0040] The factor identification unit 132 identifies factors that worsen the value of the health index, which indicates the degree of the user's health. Examples of health index indicators include sleep quality, which indicates the degree of the user's sleep; stress level, which indicates the degree of the user's stress; and fatigue level, which indicates the degree of the user's fatigue. For example, the factor identification unit 132 identifies factors that reduce the user's sleep quality from the user's sleep duration and lifestyle information included in the user's sleep information acquired by the acquisition unit 131.

[0041] Here, the processing of the factor identification unit 132 will be explained using Figures 8 to 10. Figures 8 to 10 show an example of the processing of the factor identification unit according to the embodiment. For example, the factor identification unit 132 refers to the information on conditions and factors related to sleep quality stored in the factor information storage unit 123, and as shown in Figure 8(1), identifies "sleep deprivation" as a factor that reduces the user's sleep quality based on the information from the user's sleep questionnaire, "Q. Sleep time is less than 6 hours: A. Yes" and "Q. I feel that I am not sleeping well: A. Yes".

[0042] Furthermore, the factor identification unit 132 refers to the information on conditions and factors related to sleep quality stored in the factor information storage unit 123 and identifies "lack of exercise" as a factor that reduces the user's sleep quality based on the information from the user's sleep questionnaire, "Q. Do you have an exercise habit? A. No."

[0043] The factor identification unit 132 can identify a disease as a factor by referring to the information stored in the factor information storage unit 123, which is structured as "symptoms as conditions and diseases as factors." For example, the factor identification unit 132 refers to the information on conditions and factors related to sleep quality stored in the factor information storage unit 123, and, as shown in Figure 8(2), identifies "sleep apnea syndrome" as a factor that reduces the user's sleep quality based on the information from the user's sleep questionnaire, "Q. Sometimes breathing stops for 10 seconds or more while sleeping: A. Yes." In the example in Figure 8(2), a sleep-related disease was identified as a factor, but the diseases identified by the factor identification unit 132 are not limited to this.

[0044] The factor identification unit 132 may use a model to identify factors that worsen various aspects of the user's health. For example, the user's sleep duration and lifestyle information may be input into a model that has learned the relationship between the user's sleep duration and lifestyle information and the user's sleep quality to identify factors that decrease the user's sleep quality. Alternatively, for example, the user's sleep duration and lifestyle information may be input into a model that has learned the relationship between the user's sleep duration and lifestyle information and the user's stress level to identify factors that increase the user's stress level.

[0045] For example, a model that has learned the relationship between a user's sleep duration and lifestyle habits and their fatigue level may be used to identify factors that increase a user's fatigue level by inputting the user's sleep duration and lifestyle habits into the model. Each model can be trained using supervised learning such as GBDT (Gradient Boosting Decision Tree) or unsupervised learning such as hierarchical clustering.

[0046] Furthermore, the factor identification unit 132 can further identify factors that reduce the user's quality of sleep by utilizing railway-related information. For example, the factor identification unit 132 identifies factors that reduce the user's quality of sleep from the boarding and alighting time information and commuter pass information included in the railway-related information acquired by the acquisition unit 131, and the user's sleep duration and lifestyle information included in the user's sleep-related information acquired by the acquisition unit 131.

[0047] For example, the factor identification unit 132 refers to the information on conditions and factors related to sleep quality stored in the factor information storage unit 123, and as shown in Figure 9, it uses the user's sleep questionnaire information "Q. Bedtime: A. 11pm, Q. Have you eaten a meal within 3 hours of going to bed: A. Yes", the ride history information "Date and time of disembarkation: ** / ** 20:00, Station of disembarkation: Omiya Station", and the commuter pass information "Address: Omiya Ward, Saitama City, Saitama Prefecture ******" to determine that although the user has eaten a meal within 3 hours of going to bed, it does not satisfy the condition "The time from disembarkation at the nearest station to bedtime is not within 3 hours", and therefore does not identify "eating immediately before going to bed" as a factor that reduces the user's sleep quality.

[0048] As an alternative example, the factor identification unit 132 refers to the information on conditions and factors related to sleep quality stored in the factor information storage unit 123, and as shown in Figure 10, from the user's sleep time "Wake-up time: 19:00, Bedtime: 11:00", travel history "Departure date and time: 6:00, Departure station: Tokyo Station, Alighting date and time: 7:00, Alighting station: Omiya Station", and commuter pass information "Address: Omiya Ward, Saitama City, Saitama Prefecture ******", it does not identify the factor "reversal of day and night" that reduces the user's sleep quality, because although the user wakes up at night and goes to bed during the day, it does not satisfy the condition "not working nights".

[0049] In this way, the factor identification unit 132 can further use railway-related information to identify factors, thereby excluding factors that would be significantly burdensome to address or difficult to address, from among the factors identified using only sleep-related information, and identifying factors that worsen health conditions such as sleep quality.

[0050] The above describes an example in which the factor identification unit 132 identifies factors that reduce the quality of sleep. However, the factor identification unit 132 can also identify factors that increase stress levels and factors that increase fatigue levels, in addition to factors that reduce the quality of sleep. For example, the factor identification unit 132 refers to the information stored in the factor information storage unit 123 and identifies "factors that increase stress levels" based on conditions that are met by the user's sleep time and information about the user's lifestyle. The factor identification unit 132 also refers to the information stored in the factor information storage unit 123 and identifies "factors that increase fatigue levels" based on conditions that are met by the user's sleep time and information about the user's lifestyle.

[0051] In addition to the above examples, the factor identification unit 132 may also use a model to identify factors that worsen various aspects of the user's health. For example, the user's sleep duration, lifestyle information, travel history, and commuter pass information may be input into a model that has learned the relationship between the user's sleep duration, the user's lifestyle information, travel history, and commuter pass information, and the user's sleep quality, in order to identify factors that decrease the user's sleep quality.

[0052] Alternatively, for example, a model that has learned the relationship between a user's sleep duration, lifestyle information, travel history, commuter pass information, and stress level could be used to input the user's sleep duration, lifestyle information, travel history, and commuter pass information, and identify factors that increase the user's stress level.

[0053] For example, a model that has learned the relationship between a user's sleep duration, lifestyle information, travel history, commuter pass information, and fatigue level can be used to identify factors that increase a user's fatigue level by inputting the user's sleep duration, lifestyle information, travel history, and commuter pass information into the model. Each model can be trained using supervised learning such as GBDT, or unsupervised learning such as hierarchical clustering.

[0054] The activity identification unit 133 identifies activities that improve the user's health status, which indicates the degree of the user's health, based on the sleep information acquired by the acquisition unit 131. For example, the activity identification unit 133 can identify activities that improve the user's sleep quality, activities that reduce the user's stress level, activities that reduce the user's fatigue level, etc. The following is an example of identifying activities that improve sleep quality.

[0055] For example, the activity identification unit 133 identifies activities that improve the user's sleep quality, which indicates the degree of the user's health, as a measure of the user's health. For example, the activity identification unit 133 identifies activities that eliminate the factors identified by the factor identification unit 132.

[0056] Here, the processing of the activity identification unit 133 will be explained with reference to Figure 11. Figure 11 is a diagram showing an example of the processing of the activity identification unit 133. For example, if the factor identification unit 132 identifies that a factor that reduces the quality of sleep is eating immediately before sleep, the activity identification unit 133 refers to the activity information storage unit 124 and identifies an activity to eliminate the factor that reduces the quality of sleep, "eating immediately before sleep (eating within 3 hours of going to bed)," which is "eating earlier (eating more than 3 hours before going to bed)."

[0057] Furthermore, if the factor identification unit 132 identifies a lack of exercise as a factor that reduces sleep quality, the activity identification unit 133 refers to the activity information storage unit 124 to identify an activity that will eliminate the factor "lack of exercise" that reduces sleep quality, namely "increasing the amount of exercise (for example, a 20-minute walk)." Activities that "increase the amount of exercise" include, for example, repetitive exercises using exercise equipment, walking, running, and sports.

[0058] Furthermore, if the factor identification unit 132 identifies sleep apnea syndrome as a factor that reduces the quality of sleep, the activity identification unit 133 refers to the activity information storage unit 124 to identify the activity "visiting a hospital" as a way to resolve the factor "sleep apnea syndrome" that reduces the quality of sleep.

[0059] The location identification unit 134 identifies locations that correspond to the activities identified by the activity identification unit 133, located within the area where the user identified from railway information travels. Here, a location corresponding to an identified activity is a place where the identified activity can be performed, or a place where goods or services necessary for the identified activity can be provided. Furthermore, a location corresponding to an activity may also be a place that can be indicated as an area, such as the XX road from □□ station to ×× station.

[0060] The location identification unit 134 first identifies the area between Omiya Station and Yokohama Station as the user's travel area based on the information "boarding station: Omiya Station" and "arrival station: Yokohama Station" included in the ride history stored in the railway information storage unit 121.

[0061] Then, the location identification unit 134 refers to the location information storage unit 125 and identifies the location "Gohan-ken" that corresponds to the activity "Earlier mealtime" identified by the activity identification unit 133, located in the area "Omiya Station - Yokohama Station" where the user is traveling. If there are multiple locations corresponding to the activity, the location may be identified based on predetermined conditions (distance to the user's home, the cost required for the activity, whether the user has visited the location before, the degree to which the user likes it, the business hours of the target location, the clinic hours, the available hours, ascending or descending order of "No", etc.).

[0062] The area identified by the location identification unit 134 may be an area that the user repeatedly travels to, such as their living area. For example, the location identification unit 134 identifies a location that exists within an area that the user repeatedly travels to, as identified from railway-related information. More specifically, the location identification unit 134 identifies the area that the user repeatedly travels to as "Omiya Station - Tokyo Station" from the commuter pass information "Section: Omiya Station - Tokyo Station" stored in the railway information storage unit 121, and identifies a location within the "Omiya Station - Tokyo Station" area that corresponds to an activity identified by the activity identification unit 133. The location identification unit 134 may also identify an area that the user repeatedly travels to from information on places that the user has visited multiple times within a predetermined period, which is included in the ride history information. The predetermined period can be freely changed according to the purpose.

[0063] Now, with reference to Figure 12, the processing of the location identification unit 134 will be explained. Figure 12 is a diagram showing an example of the processing of the location identification unit 134. For example, if the activity identification unit 133 identifies that the activity to eliminate the cause is "eating earlier (eating at least 3 hours before going to bed)," the location identification unit 134 refers to the location information storage unit 125 and identifies a place called "Gohan-ken" that corresponds to the activity of eating earlier, located in the area "Omiya Station - Tokyo Station" that the user repeatedly moves to.

[0064] As an alternative example, if the activity identification unit 133 identifies that the activity to eliminate the cause is "increasing the amount of exercise," the location identification unit 134 refers to the location information storage unit 125 to identify a location "○○ Gym" that corresponds to the activity of increasing the amount of exercise, located in the area "Omiya Station - Tokyo Station" that the user repeatedly travels to.

[0065] Furthermore, if the activity identification unit 133 identifies that the activity to resolve the cause is "visiting a hospital," the location identification unit 134 refers to the location information storage unit 125 to identify a hospital location, "○○ Hospital," that corresponds to visiting a hospital and is located in the area "Omiya Station - Tokyo Station" that the user repeatedly travels to.

[0066] The location identification unit 134 may further use railway-related information to identify the location corresponding to the activity. For example, the location identification unit 134 uses the boarding and alighting stations and boarding / alighting time information included in the railway-related information acquired by the acquisition unit 131 to identify the location corresponding to the activity identified by the activity identification unit 133.

[0067] Here, the processing of the location identification unit 134 will be explained with reference to Figure 13. Figure 13 is a diagram showing an example of the processing of the location identification unit 134. For example, if the activity identification unit 133 identifies the activity that will resolve the cause as "eating earlier (eating at least 3 hours before going to bed)", the location identification unit 134 identifies the location "Yukitei" which corresponds to the activity of eating earlier, from the commuter pass information "Section: Omiya Station - Tokyo Station" stored in the railway information storage unit 121, the boarding history information "Boarding date and time: ** / ** 18:00, Boarding station: Tokyo Station, Alighting date and time: None, Alighting station: None" and the location information stored in the location information storage unit 125 "Name: Yukitei, Address: Saitama City, Saitama Prefecture *****, Type of activity: Eating ○".

[0068] In other words, since it is assumed that the user is already on a train heading home, the location identification unit 134 identifies "Yukitei," a location near Omiya Station, which is the user's nearest station to their home, rather than "Gohan-ken," a location near Tokyo Station. In addition to the above example, the location identification unit 134 can also identify locations that are on or near the user's commuting or return-home route, estimated from railway information, as locations corresponding to their activities.

[0069] As an alternative example, if the activity identification unit 133 identifies the activity that will resolve the cause as "increasing exercise (20 minutes of walking)," the location identification unit 134 will use the commuter pass information stored in the railway information storage unit 121 ("Section: Omiya Station - Tokyo Station"), the boarding history information ("Boarding date and time: ** / ** 20:00, Boarding station: Tokyo Station, Alighting date and time: None, Alighting station: None"), and the location information stored in the location information storage unit 125 ("Name: ○○ Road, Address: Saitama City, Saitama Prefecture *****, Activity type: Exercise ○") to identify "○○ Road," which is the road from Saitama Shintoshin Station to Omiya Station, as the location corresponding to the activity of increasing exercise (20 minutes of walking). In other words, since it is assumed from the boarding history that the user is already on a train returning home, the location identification unit 134 identifies "○○ Road," a location near Omiya Station, which is the nearest station to the user's home, rather than "○○ Gym."

[0070] As an alternative example, if the activity identification unit 133 identifies the activity to resolve the cause as "sleep apnea syndrome," the location identification unit 134 identifies the location corresponding to a hospital visit, "△△ Hospital," from the commuter pass information stored in the railway information storage unit 121 ("Section: Omiya Station - Tokyo Station"), the boarding history information ("Boarding date and time: ** / ** 20:00, Boarding station: Tokyo Station, Alighting date and time: None, Alighting station: None"), and the location information stored in the location information storage unit 125 ("Name: △△ Hospital, Address: Saitama City, Saitama Prefecture *****, Type of activity: Hospital ○"). In other words, since the boarding history suggests that the user is already on a train returning home, the location identification unit 134 identifies "△△ Hospital," a location near Omiya Station, which is the nearest station to the user's home, rather than "○○ Hospital."

[0071] If there are multiple locations that correspond to an activity, the location may be specified based on predetermined conditions (distance to the user's home, distance from the current location, cost required for the activity, whether the user has visited the location before, how much the user likes it, distance from boarding / alighting stations, business hours of the target location, clinic hours, available hours, ascending or descending order of "No", etc.). For example, the location closest to the most recent boarding or alighting station in the user's travel history may be specified as the location corresponding to the activity.

[0072] Alternatively, based on the user's past travel history, the location closest to where the user is estimated to be at the recommended time of activity may be identified as the location corresponding to the activity. For example, if the user's weekday travel history is "Departure date and time: 18:00, Departure station: Tokyo Station, Disembarking date and time: 19:00, Disembarking station: Omiya Station", the location identification unit 134 estimates that the user was on a train from Tokyo Station to Omiya between 18:00 and 19:00 on a weekday. For example, if the recommended time for activity is 19:30 on a weekday, the unit estimates that the user is near Akabane Station on the route from Tokyo Station to Omiya Station, and identifies the location near Akabane Station among multiple locations as the location corresponding to the activity.

[0073] Alternatively, the location identification unit 134 may identify a location using a model. For example, the location identification unit 134 may identify a location by inputting information on the activity, boarding / alighting station, boarding / alighting date and time, and location into a model that has learned the relationship between the activity, boarding / alighting station, boarding / alighting date and time, and location. Each model can be trained using supervised learning such as GBDT, or unsupervised learning such as hierarchical clustering.

[0074] In this way, the location identification unit 134 can identify a place to perform an activity that is located within the user's living area when the user is moving in a pattern similar to their past travel history. This reduces the burden on the user before they perform the activity and appropriately encourages them to take actions that improve their health.

[0075] The output unit 135 outputs the activity identified by the activity identification unit 133 and the location identified by the location identification unit 134. For example, the output unit 135 displays on the terminal device 400 the content of the activity that eliminates the factors that reduce sleep quality identified by the activity identification unit 133, and the location information of the location identified by the location identification unit 134. At this time, the output unit 135 can also output the benefits and effects that the user will receive by performing the activity identified by the activity identification unit 133 at the location identified by the location identification unit 134. In the following description, an example of displaying the activity and location on the display will be explained, but the output unit 135 may also play audio explaining the activity and location through the speaker of the terminal device 400.

[0076] The processing of the output unit 135 will be explained with reference to Figures 14 to 17. Figures 14 to 17 show examples of the processing of the output unit 135. Figure 14 is an example of outputting information about activities and locations related to eating to the terminal device 400. Figure 15 is an example of outputting information about activities and locations related to exercise to the terminal device 400. Figure 16 is an example of outputting information about activities and locations related to light to the terminal device 400. Figure 17 is an example of outputting information about activities and locations related to medical consultation to the terminal device 400.

[0077] For example, as shown in Figure 14(1), the output unit 135 displays information on the terminal device 400 that includes the activity details "Eat dinner by 19:00 (3 hours before bedtime)," the location corresponding to the activity "Yukitei," and the effects of the activity, such as "By eating dinner at Yukitei by 19:00, you can expect to eliminate the problem of 'eating right before going to sleep'." At this time, the output unit 135 can output location information of the location corresponding to the activity. For example, as shown in Figure 14(2), the output unit 135 displays the location information of the location corresponding to the activity "Yukitei" on the display of the terminal device 400.

[0078] As an alternative example, as shown in Figure 15(1), the output unit 135 displays information on the terminal device 400 that includes the activity content "20 minutes of walking," the location of the activity, "road" from XX Station to YY Station, and the effects of the activity, such as "By walking for 20 minutes from XX Station to YY Station, you can expect to alleviate 'lack of exercise'." At this time, as shown in Figure 15(2), the output unit 135 displays the walking route information and the location information of the road corresponding to the activity on the terminal device 400.

[0079] As an alternative example, as shown in Figure 16, the output unit 135 displays information on the terminal device 400 that includes the activity content "Dim the lights in the room three hours before going to bed," the location corresponding to the activity "Home," and the effect of the activity, such as "By dimming the lights in the room three hours before going to bed, you can expect to alleviate 'difficulty falling asleep'."

[0080] As an alternative example, as shown in Figure 17, the output unit 135 displays information on the terminal device 400 that includes the activity content "Visit a hospital," the location corresponding to the activity "△△ Hospital," and the effect of the activity, "By visiting △△ Hospital, you can expect to be cured of sleep apnea syndrome." At this time, as shown in Figure 17(2), the output unit 135 also displays the location information of the location corresponding to the activity "△△ Hospital" on the terminal device 400.

[0081] The timing of output by the output unit 135 may be at a location and time set by the user. For example, the output unit 135 may output when the user arrives at a predetermined location set by the user (e.g., the nearest station to their home, a transfer station, etc.). Alternatively, the output unit 135 may output at a predetermined time set by the user (e.g., 6 PM on a weekday).

[0082] Alternatively, the output unit 135 may output according to the positional relationship between the activity and the corresponding location. For example, the output unit 135 outputs when the distance between the terminal device 400 and the location identified by the location identification unit 134 falls below a predetermined distance.

[0083] The granting unit 136 grants a reward to the user when the user performs an activity output by the output unit 135 at a specified location. First, the granting unit 136 determines whether the user performed an activity at a specified location based on information detected by various sensors such as positioning sensors and acceleration sensors equipped in the terminal device 400, as well as payment information using the terminal device 400. For example, the granting unit 136 determines that the user performed an activity (exercise: 20 minutes of walking) based on changes in location information and acceleration.

[0084] At this time, the assigning unit 136 may further determine whether the user performed an activity at the identified location using vital data detected by sensors on a wearable device that is communicably connected to the terminal device 400. For example, the assigning unit 136 may determine that the user performed an activity at the identified location based on changes in acceleration, location information, pulse data, and respiratory rate.

[0085] The granting unit 136 then grants points usable in the shopping service to the user when it determines that the user has performed an activity at a specified location. The rewards may include not only coupons and points usable in the specified service, but also electronic information such as specified images and audio.

[0086] 〔flowchart〕 Next, an example of processing by the health improvement device 100 according to this embodiment will be described with reference to Figure 18. Figure 18 is a flowchart showing an example of the processing flow of the health improvement device according to this embodiment. Note that each step in the flowchart shown in Figure 18 can be executed in a different order, and additional or omitted processes may be included.

[0087] First, the acquisition unit 131 acquires information about the railway used by the user and information about the user's sleep (step S101). Next, the factor identification unit 132 identifies factors that reduce the user's quality of sleep from the user's sleep duration and information about the user's lifestyle, which are included in the user's sleep information acquired by the acquisition unit 131 (step S102). Subsequently, the activity identification unit 133 identifies activities that eliminate the factors identified by the factor identification unit 132 (step S103).

[0088] Next, the location identification unit 134 identifies the area where the user identified from the railway information is traveling (step S104). Subsequently, the location identification unit 134 identifies the location in the area that corresponds to the activity identified by the activity identification unit 133 (step S105).

[0089] Then, the output unit 135 outputs the activity identified by the activity identification unit 133 and the location identified by the location identification unit 134 (step S106). Subsequently, the assignment unit 136 determines whether the user performed the activity output by the output unit 135 at the location (step S107).

[0090] If the assignment unit 136 determines that the user has performed the activity output by the output unit 135 at the location (step S107; Yes), the assignment unit 136 assigns a specific status to the user (step S108). The health improvement device 100 then terminates processing. On the other hand, if the assignment unit 136 determines that the user has not performed the activity output by the output unit 135 at the location (step S107; No), the health improvement device 100 terminates processing.

[0091] 〔effect〕 The health improvement device 100 according to this embodiment includes an acquisition unit 131 that acquires information about the railway used by the user and information about the user's sleep; an activity identification unit 133 that identifies activities to improve the user's health level, which indicates the degree of the user's health, based on the sleep information acquired by the acquisition unit 131; a location identification unit 134 that identifies a location in the area where the user travels, as identified from the railway information, that corresponds to the activity identified by the activity identification unit 133; and an output unit 135 that outputs the activity identified by the activity identification unit 133 and the location identified by the location identification unit 134.

[0092] As a result, the health improvement device 100 outputs to the user's terminal device 400 activities that improve the user's health, identified from railway-related information and sleep-related information, as well as locations within the area the user travels where these activities can be performed. By providing recommendations for activities that are close to the user and require minimal effort to perform, the device can appropriately encourage actions that improve the user's health.

[0093] The activity identification unit 133 of the health improvement device 100 identifies activities that improve the user's sleep quality, which indicates the degree of the user's health, as a health status that indicates the degree of the user's health. As a result, the health improvement device 100 outputs to the user's terminal device 400 the activities that improve the user's sleep quality, which have been identified from railway-related information and sleep-related information, as well as locations within the area where the user is traveling where the activities can be performed, thereby appropriately encouraging actions that improve the user's health.

[0094] The health improvement device 100 further includes a factor identification unit 132 that identifies factors that reduce the user's quality of sleep based on the user's sleep duration and lifestyle information included in the user's sleep information acquired by the acquisition unit 131, and an activity identification unit 133 that identifies activities to eliminate the factors identified by the factor identification unit 132.

[0095] As a result, the health improvement device 100 can output to the user's terminal device 400 activities that eliminate factors that reduce the user's quality of sleep, as well as locations where these activities can be performed, thereby appropriately encouraging the user to take actions that improve their health.

[0096] The factor identification unit 132 of the health improvement device 100 identifies factors that reduce the user's quality of sleep based on information about boarding and alighting times and commuter pass information included in the railway information acquired by the acquisition unit 131, the user's sleep duration included in the user's sleep information acquired by the acquisition unit 131, and information about the user's lifestyle habits.

[0097] As a result, the health improvement device 100 can further use railway-related information to identify factors, thereby excluding factors that would be significantly burdensome or difficult to resolve from those identified using only sleep-related information. It can then identify factors that worsen health conditions such as sleep quality and appropriately encourage actions to improve the user's health.

[0098] The location identification unit 134 of the health improvement device 100 identifies locations within areas where the user repeatedly travels, as identified from railway-related information. This allows the health improvement device 100 to identify locations corresponding to activities within the user's living area, and to more appropriately encourage actions that improve the user's health by suggesting activities within areas that are less burdensome for the user to perform.

[0099] The health improvement device 100 uses the location identification unit 134, which includes information on boarding and alighting stations and boarding / alighting times included in the railway information acquired by the acquisition unit 131, to identify a location corresponding to the activity identified by the activity identification unit 133. As a result, the health improvement device 100 can further identify a location for performing the activity using the railway information, making it possible to identify a location that is less burdensome for the user when performing the activity, such as a location close to the user's commute route during their commuting hours. This allows the device to more appropriately encourage actions that improve the user's health.

[0100] The health improvement device 100 further includes a rewarding unit 136 that grants a reward to the user when the user performs an activity output by the output unit 135 at a specified location. This allows the health improvement device 100 to more appropriately encourage actions that improve the user's health by providing incentives to the user who performs the activity.

[0101] 〔others〕 Furthermore, among the processes described in the above embodiments, all or part of those described as being performed automatically may be performed manually. Conversely, all or part of those described as being performed manually may be performed automatically by known methods. In addition, the processing procedures, specific names, and various data and parameters shown in the above documents and drawings may be changed at will unless otherwise specified.

[0102] Furthermore, each component of the illustrated device is a functional concept and does not necessarily have to be physically or functionally configured as shown. In other words, the specific forms of distribution and integration of each device and functional configuration are not limited to those shown, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions. In addition, the embodiments described above and the processes carried out in each embodiment may be combined as appropriate, as long as the processing content is not contradictory.

[0103] 〔program〕 Furthermore, the health improvement device 100 according to the above-described embodiment is realized by including, for example, a computer 1000 having the configuration shown in Figure 19. Figure 19 is a diagram showing an example of a computer that realizes the processing of the health improvement device according to the embodiment. The computer 1000 is connected to an output device 1010 and an input device 1020, and has a configuration in which a central processing unit 1030, memory 1040, storage 1050, output IF (Interface) 1060, input IF 1070, and communication interface 1080 are connected by a bus 1090.

[0104] The central processing unit 1030 operates based on programs stored in the memory 1040 and storage 1050, as well as programs read from the input device 1020, and executes various processes. The memory 1040 is a memory device, such as RAM, that temporarily stores data used by the central processing unit 1030 for various calculations. The storage 1050 is a storage device where data used by the central processing unit 1030 for various calculations and various databases are registered, and is implemented using ROM (Read Only Memory), HDD (Hard Disk Drive), flash memory, etc.

[0105] Output IF1060 is an interface for transmitting information to be output to output devices 1010 that output various types of information, such as monitors and printers. It can be implemented using connectors of standards such as USB (Universal Serial Bus), DVI (Digital Visual Interface), or HDMI (High Definition Multimedia Interface). Input IF1070 is an interface for receiving information from various input devices 1020, such as mice, keyboards, and cameras. It can be implemented using USB, for example. Input devices 1020 may also be devices that read information from optical recording media, magneto-optical recording media, tape media, magnetic recording media, or semiconductor memory, or external storage media such as USB memory.

[0106] The communication interface 1080 receives data from other devices via the network N and sends it to the central processing unit 1030, and also transmits data generated by the central processing unit 1030 to other devices via the network N. The central processing unit 1030 controls the output device 1010 and input device 1020 via the output IF 1060 and input IF 1070. For example, the central processing unit 1030 loads a program from the input device 1020 or storage 1050 into memory 1040 and executes the loaded program.

[0107] For example, if computer 1000 functions as the control unit 130 of health improvement device 100, the central processing unit 1030 of computer 1000 realizes the functions of the control unit 130 by executing a program loaded on memory 1040.

[0108] Although some embodiments of the present invention have been described above with reference to the drawings, these are illustrative examples, and the present invention may be implemented in other forms by various modifications and improvements based on the knowledge of those skilled in the art, starting with the embodiments described in the disclosure section of the invention. Furthermore, the terms "section, module, unit" used above can be read as "means" or "circuit," etc. For example, the "applying part" can be read as the "applying means" or "applying circuit." [Explanation of symbols]

[0109] 100 Health Improvement Device 110 Communications Department 120 Storage section 121 Railway Information Storage Unit 122 User Information Storage Unit 123 Factor Information Storage Unit 124 Activity information storage unit 125 Location Information Storage Unit 130 Control Unit 131 Acquisition Department 132 Factor Identification Section 133 Activity Specification Department 134 Location Identification Section 135 Output section 136 Assignment section 200 Railway Information Server 300 Sleep Information Server 400 terminal devices

Claims

1. An acquisition unit that acquires information about the railway used by the user and information about the user's sleep, Based on the sleep information acquired by the acquisition unit, an activity identification unit identifies activities that improve the user's health status, which indicates the degree of the user's health. A location identification unit that identifies a location corresponding to the activity identified by the activity identification unit, which is located in the area where the user travels, as identified from the railway information; An output unit that outputs the activity identified by the activity identification unit and the location identified by the location identification unit, A health improvement device characterized by having the following features.

2. The health improvement device according to claim 1, characterized in that the activity identification unit identifies activities that improve the sleep quality, which indicates the degree of the user's restful sleep, as a health level indicating the degree of the user's health.

3. The system further includes a factor identification unit that identifies factors that reduce the quality of sleep of the user, based on the user's sleep duration and lifestyle information included in the user's sleep information acquired by the acquisition unit. The activity identification unit identifies an activity to eliminate the factor identified by the factor identification unit. The health improvement device according to feature 2.

4. The aforementioned factor identification unit, Based on the information on boarding and alighting times and commuter pass information included in the railway information acquired by the acquisition unit, the user's sleep duration included in the user's sleep information acquired by the acquisition unit, and the user's lifestyle information, factors that reduce the user's quality of sleep are identified. The health improvement device according to feature 3.

5. The health improvement device according to claim 2, characterized in that the location identification unit identifies the location located in the area to which the user repeatedly travels, as identified from the railway information.

6. The location identification unit is, The acquisition unit uses the information on boarding and alighting stations and boarding / alighting times included in the railway information acquired by the acquisition unit to identify the location corresponding to the activity identified by the activity identification unit. The health improvement device according to feature 5.

7. Granting Unit: Grants a benefit to the user when the user performs the activity output by the output unit at the location. The health improvement device according to claim 1, further comprising the above.

8. A method performed by a health improvement device, An acquisition process for acquiring information about the railway used by the user and information about the user's sleep, Based on the sleep information obtained in the acquisition step, an activity identification step identifies activities that improve the user's health status, which indicates the degree of the user's health. A location identification step that identifies a location corresponding to the activity identified by the activity identification step, which is located in the area where the user travels, as identified from the railway information; An output step that outputs the activity identified by the activity identification step and the location identified by the location identification step, A method for improving health, characterized by including [a certain component].

9. A step of acquiring information about the railway used by the user and information about the user's sleep, Based on the sleep information obtained in the acquisition step, an activity identification step identifies activities that improve the user's health status, which indicates the degree of the user's health. A location identification step that identifies a location corresponding to the activity identified by the activity identification step, which is located in the area where the user travels, as identified from the railway information; An output step that outputs the activity identified by the activity identification step and the location identified by the location identification step, A health improvement program characterized by having a computer execute it.

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