Information Processing Apparatus and Program

Abstract

To provide an information processor and a program that can support the self-management of the activities of a user.SOLUTION: In an information processor 1, activity target information on a target of the activity amount of a user is received and is converted to activity amount information which represents the activity amount to be performed in a predetermined period of time in the common unit. After that, the type of an activity that satisfies an execution condition set for each type of activity is extracted, and specific recommended activity information for a user is generated on the basis of the activity amount of each specific unit amount related to the extracted type of activity and the activity amount information as the result of conversion of the activity target information of the user.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to an information processing apparatus and a program.

Background Art

[0002] In recent years, in the medical field, exercise therapy may be incorporated for the purpose of improving muscle strength, maintaining vital capacity, and improving glucose metabolism and lipid metabolism. In exercise therapy, based on the guidance of a doctor, patients and the like perform exercises such as walking or going to the gym.

[0003] Here, even in a situation where it is not possible to increase so-called sports and exercises, such as not being able to go to the gym for various reasons, it is possible to ensure the necessary amount of physical activity by increasing physical activities including daily life activities such as housework, household chores, walking for commuting, and hobby and leisure activities carried out in free time. However, there is a limit to accurately grasping the daily life of a patient and implementing appropriate lifestyle guidance and exercise therapy within a limited face-to-face time. Specifically, at present, although a doctor can provide general information such as presenting target values such as energy consumption and METs, the doctor cannot present an exercise program that can actually be executed by patients and the like.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] That is, patients and the like who receive such general information can receive presentations of general target values such as energy consumption and METs from doctors and the like, but they need to self-manage their activities themselves. However, it is difficult for patients and the like to know specifically what activities and to what extent they should perform in order to achieve the target value.

[0006] Therefore, there is a need for a technology to support self-management when patients and the like who receive guidance from doctors and users who actually perform activities self-manage how much of what activities they should perform to achieve the target activity level.

[0007] In view of the above situation, one of the objectives of the present invention is to provide an information processing apparatus and a program that can support the self-management of users' activities.

[0008] Note that Patent Document 1 discloses a device that detects walking by an acceleration sensor, receives input of calorie consumption, and converts and displays calorie consumption into the number of steps based on data of the user's walking speed, weight, and stride length.

Means for Solving the Problems

[0009] One aspect of the present invention for solving the problems of the above conventional example is an information processing apparatus, which includes means for receiving activity target information that is a target of activity amount for a user, and for each type of activity, holding the activity amount for each predetermined unit amount as a value in a predetermined common unit and holding the implementation conditions for each type of activity; means for converting the received activity target information into activity amount information representing the activity amount to be performed in a predetermined period in the common unit; information generation means for extracting the types of activities that satisfy the implementation conditions from among the types of activities, and generating predetermined recommended activity information for the user based on the activity amount for each predetermined unit amount related to the extracted types of activities and the activity amount information that is the conversion result of the activity target information related to the user; and means for outputting the generated recommended activity information.

Effects of the Invention

[0010] According to one aspect of the present invention, it is possible to support the user's self - management of activities.

Brief Description of the Drawings

[0011]

Figure 1

Figure 2

Figure 3

Modes for Carrying Out the Invention

[0012] Embodiments of the present invention will be described with reference to the drawings. The information processing apparatus 1 according to an embodiment of the present invention is, for example, a mobile terminal or the like, and as illustrated in FIG. 1, includes a control unit 11, a storage unit 12, an operation unit 13, a display unit 14, and a communication unit 15. Further, this information processing apparatus 1 is connected to a server 2 via a network.

[0013] The control unit 11 is a program - control device such as a CPU and operates according to a program stored in the storage unit 12. In the example of the present embodiment, this control unit 11 receives activity target information that is the target of the user's activity amount. Further, the control unit 11 accesses a database (hereinafter referred to as an activity database) that holds the activity amount for each predetermined unit amount for each type of activity as a value in a predetermined common unit. Then, this control unit 11 converts the received activity target information into information on the activity amount to be performed in a predetermined period. The control unit 11 shall represent the information after this conversion in a predetermined common unit.

[0014] Further, the control unit 11 extracts, from the activity database, the types of activities that satisfy the implementation conditions among the types of activities. The control unit 11 generates predetermined recommended activity information for the user based on the activity amount per predetermined unit related to the extracted activity type and the conversion result of the activity target information related to the user, and outputs the generated recommended activity information. The detailed operation of this control unit 11 will be described later.

[0015] The storage unit 12 is a memory device or the like and holds a program executed by the control unit 11. This program may be stored and provided in a computer-readable and non-transitory recording medium and stored in this storage unit 12. Further, this storage unit 12 also operates as a work memory of the control unit 11.

[0016] In an example of the present embodiment, an activity database recording the implementation conditions for each type of activity is held in this storage unit 12. This activity database may be set for each user, and as illustrated in FIG. 2, its content associates information specifying the type of activity (activity type name: A) with the implementation conditions of the activity (B) and information on the activity amount per predetermined unit (activity amount: C). Further, in a certain example of the present embodiment, information on the activity characteristics (activity characteristic information: D) for each type of activity recorded in this activity database may be associated and recorded. Here, the activity characteristic information may be, for example, information on whether the activity amount is determined or not. Specifically, activities such as commuting have a determined activity amount, but depending on the activity, there are some whose activity amount can be adjusted according to the activity time or the like. The activity characteristic information may include information indicating whether such an activity amount is fixed or variable.

[0017] One of the features of the present embodiment is that this activity amount information is converted into a predetermined common unit. Here, the common unit may be a unit of any activity or exercise amount. Specifically, the common unit may be the number of steps, which is a unit of walking.

[0018] Here, the implementation conditions of the activities can be arbitrarily determined, including the day of the week (weekday or holiday), appropriate time zone, appropriate weather conditions, indoor or outdoor location, the time required for the activity (the time from the start to the completion of a series of activities), necessary equipment (such as AEROBIKE (registered trademark)), taboos (such as the presence or absence of certain diseases), the impact of factors that prevent going out (such as whether the implementation of the activity is restricted due to the restriction on going out accompanying the spread of infectious diseases), and other conditions.

[0019] Furthermore, in this storage unit 12, for each user of the information processing device 1, information for identifying the user (such as the user name), in addition to the user's physical information such as gender, date of birth (or age), height, weight, taboos (types of activities restricted due to underlying diseases, etc.), there is also stored a user database in which information about the user's work location, information about the means of transportation usually used, information about the location of the home, commuting time, family composition (presence or absence of a spouse, number and age of children, etc.), types of housework undertaken within the family, and the general schedule of the user's weekdays and holidays (environmental information) is associated and recorded. The information stored in this user database may be input in advance by the user or others, or may be estimated based on information registered by the user or collected from the user during the use of the information processing device 1 in this embodiment. For example, the information processing device 1 may estimate the user's activity time, etc. based on the aggregation result of the time the user used the information processing device 1 and store it in the user database.

[0020] The operation unit 13 is a touch panel, keyboard, etc., which accepts instructions and information input from the user and outputs the instructions and information to the control unit 11. The display unit 14 is a display, etc., which displays and outputs information according to instructions input from the control unit 11.

[0021] The communication unit 15 is a network interface, etc., which transmits and receives information to and from a server 2, etc. connected via a network according to instructions input from the control unit 11. Also, this communication unit 15 outputs the information received from the server 2, etc. to the control unit 11.

[0022] In an example of this embodiment, the server 2 is a general server device (such as a web server), generates information to be set in the activity database according to a request input from the information processing device 1, and sends the generated information to the information processing device 1.

[0023] As an example, the server 2 receives, together with information such as the age, gender, height, and weight of the user from the information processing device 1, a request for generating information to be stored in the activity database. Then, the server 2 generates, for at least one type of activity, the implementation conditions of the activity and information on the amount of activity per predetermined unit amount, and sends them to the information processing device 1.

[0024] Specifically, as the types of activities, the server 2 · Walking · Running · Squat In addition to exercises such as · Basal metabolism · Commuting (on foot) · Commuting (by train) · Working · Shopping · Going out Regarding information on various activities including housework such as the above, for each activity, information on the amount of activity per certain time (for example, 1 hour) is obtained based on information such as the age, gender, height, and weight of the user received from the information processing device 1. Also, the server 2 obtains this information on the amount of activity as a value converted into a predetermined common unit, for example, the number of steps which is the unit of walking exercise (such as a value of the number of steps like "300 steps").

[0025] As an example, the basal metabolism per hour and per 1 kg of body weight is calculated by an equation such as the Harris - Benedict equation having different coefficients for each gender, and its unit is represented by calories (kcal). In the example of this embodiment, the server 2 converts it into the number of steps (for example, a value of the number of steps such as "300 steps") which is the unit of walking exercise as a common unit and sends it to the information processing device 1.

[0026] Next, the operation of the control unit 11 will be described. In an example of the present embodiment, as illustrated in FIG. 3, this control unit 11 functionally includes an activity target setting unit 21, an activity amount holding unit 22, an information generation unit 23, and an output control unit 24.

[0027] The activity target setting unit 21 receives activity target information (such as the target number of steps per day) that is the target activity amount of the user from the user himself / herself or a doctor. Here, the activity amount target information may be set as an improvement item as more long-term target information, for example, a change over a predetermined period for a predetermined index according to the disease state. Here, the index may directly represent, for example, the calorie consumption, or may be determined based on values representing blood glucose control such as blood glucose level and HbA1c value, values representing lipid metabolism such as HDL cholesterol value, LDL cholesterol value, non-HDL cholesterol, and triglyceride, or values representing disease states such as bone density. Specifically, the activity amount target information may be the calorie consumption per day, the change amount of HbA1c value every three months (improvement of blood glucose control), the change amount of values representing lipid metabolism (such as HDL cholesterol value and LDL cholesterol value) every month (improvement of lipid metabolism), the change amount of bone density every three months (improvement of bone density), etc.

[0028] The activity amount holding unit 22 holds, for each type of activity, the activity amount for each predetermined unit amount as a value in a predetermined common unit in the storage unit 12, and holds the implementation conditions for each type of the activity.

[0029] In an example of the present embodiment, the activity amount holding unit 22 sends a request for generating information to be stored in the activity database to the server 2 together with information such as the age, gender, height, and weight of the user set by the user. Further, this activity amount holding unit 22 receives, from the server 2, the activity amount value for each predetermined unit amount for each type of activity. Here, the activity amount holding unit 22 receives, from the server 2, the activity amount value calculated by the server 2 based on the physical information and environmental information of each user.

[0030] The activity amount maintenance unit 22 records the information on the activity amount for each type of activity received from the server 2 in the activity database of the storage unit 12, associating it with the execution conditions of the corresponding activity. Note that the execution conditions of the activity may be determined in advance for each type of activity, and when sending the information on the activity amount from the server 2, the information on the corresponding execution conditions may also be sent together.

[0031] The information generation unit 23 converts the activity target information received by the activity target setting unit 21 into information on the activity amount in the above common unit, which represents the activity amount to be performed within a predetermined period (for example, within one day). The conversion method to the information on the activity amount in this common unit may be performed based on, for example, the improvement item targeted by the activity target information (such as diabetes control, lipid metabolism, bone density, etc.) or a method determined in advance for each index.

[0032] For example, when the calorie consumption (calorie consumption excluding basal metabolism) by exercise in one day is set as the activity target information at 300 kcal, the information generation unit 23 converts this set value into the number of steps, which is the information on the activity amount in the common unit to be achieved within a predetermined period (for example, within one day). As an example, when the common unit is the number of steps, the relationship between calories and the number of steps can be estimated by a known method using information such as the user's age, weight, and step width, and the information generation unit 23 calculates the required activity amount in one day in the above common unit as "10,000 steps" by this method.

[0033] Also, when the change amount of the HbA1c value for diabetes improvement is set as the activity target information, using the information on the type of activity and the activity amount (value in the above common unit) in a certain period, which was performed by a large number of subjects in the past, and the change amount of the HbA1c value of the subjects in the predetermined period when performing the activity as the input, the required activity amount value in the common unit in the predetermined period (for example, per day) may be obtained based on the change amount of the HbA1c value set as the activity target information using a machine learning model that has been machine-learned to output the value.

[0034] Note that this machine learning model is set to be different for each metric, not only for the improvement items targeted by the activity target information. For example, even when the goal is to improve diabetes, a different machine learning model (such as an insulin resistance impact model considering insulin resistance) is used depending on whether the metric is blood glucose level or HbA1c level. In this example, information on the types and amounts of activities (values in the above common unit) performed by a large number of subjects in a certain period in the past is used, and the amount of change in the subjects' blood glucose levels during a predetermined period when performing the activity is input, and this machine learning model is machine-learned to output the required activity amount value in the above common unit for a predetermined period (e.g., per day).

[0035] In addition, the machine learning model may be made different not only for each metric, but also for different classifications according to the user's body information and environmental information even for the same metric. For example, when it is known that the correlation between the activity amount and the HbA1c level varies depending on the user's age group, subjects who have performed activities in the past and had their HbA1c level changes measured are divided into each age group, and information on the types and amounts of activities (values in the above common unit) in a certain period for each subject in the divided age groups is used, and the amount of change in the subjects' HbA1c levels during a predetermined period when performing the activity is input, and a plurality of machine learning models machine-learned to output the required activity amount value in the above common unit for a predetermined period (e.g., per day) may be generated. In this example, a machine learning model (after machine learning) corresponding to the age group of the user for whom the activity target information is set is selected, and using the selected machine learning model, the required activity amount per day in the above common unit may be obtained based on the specified amount of change in the HbA1c level for the user.

[0036] The information generation unit 23 further refers to the information in the activity database, extracts the types of activities that satisfy the implementation conditions from among the types of activities represented by the information held in the activity database, and generates recommended activity information for the user based on the amount of activity per predetermined unit related to the extracted types of activities and the conversion result of the activity target information related to the user.

[0037] The information generation unit 23 starts processing, for example, according to the instructions of the user, and while referring to the user's physical information and environmental information, extracts information identifying the types of activities that satisfy the implementation conditions at each time point of the day from the activity database.

[0038] For example, for a certain user A, assume that the age is 40 years old, the weight is 70 kg, and the user is a male (physical information). After getting up in the morning, the user commutes to work by train and on foot, mainly performs desk work from morning to evening, returns home by train and on foot at night, and does light exercise before going to bed (weekdays). Assume that such environmental information is set.

[0039] First, the information generation unit 23 classifies weekdays and holidays, for example, and obtains from the activity database the daily physical activity amount target except for at least basal metabolism. As described above, this activity amount is calculated by the server 2 from information such as the user's age and weight, and here assume that it is set to, for example, "10,000 steps (about 300 kcal)".

[0040] Also, the information generation unit 23 classifies and sets the time zones for activities as · Morning (after getting up) · Morning (from 9:00 to 12:00) · Afternoon (from 12:00 to 15:00) · Evening (from 15:00 to 18:00) · Night (from 18:00 to around 21:00 (before going to bed)) And the information generation unit 23 extracts from the activity database information identifying the types of activities that satisfy the implementation conditions in each of the time zones of, for example, morning, afternoon, evening, and night (every 3 hours in the above example), while referring to the user's physical information and environmental information, and sequentially determines the activities for each of the above time zones.

[0041] For example, the information generation unit 23 extracts from the activity database the activities determined to be appropriate time zones for the morning time zone on weekdays. Specifically, examples of activities that make the morning time zone an appropriate time zone include activities in daily life such as running, as well as housework and commuting.

[0042] Also, in the following example, assume that the implementation conditions for "running" are defined as "temperature 25 degrees or less, outdoors, implementation time 30 minutes or more, not including commuting during the morning time zone, taboos: heart disease...", etc. Also assume that the implementation conditions for "commuting" are set as "the user's environmental information includes morning commuting".

[0043] Under this example, regarding the above user A, since the environmental information of user A includes information indicating commuting during the weekday morning time zone, the information generation unit 23 extracts the activity of "commuting", but does not extract the activity of "running". Therefore, the information generation unit 23 defines "commuting" as the activity performed by user A in the morning on weekdays.

[0044] Hereinafter, in the same manner, the information generation unit 23 acquires information for specifying the activities (recommended activities) that the user should perform in each time zone on weekdays and holidays.

[0045] Also, for each of the recommended activities acquired for each time zone, the information generation unit 23 generates information on the recommended activity amount.

[0046] Next, for activities such as commuting, which are set as having a fixed activity amount in the activity database among the recommended activities acquired for each time zone, the information generation unit 23 obtains the activity amount.

[0047] For example, in the case of the above user A, assume that commuting by train in the morning and at night each corresponds to an activity amount of 1000 steps, and an activity amount of 2000 steps is obtained in desk work. In this case, the information generation unit 23 subtracts a total of 4000 steps from the target activity amount to get 10000 - 4000 = 6000 steps which is obtained. Hereinafter, the value obtained here is referred to as the residual activity amount for convenience.

[0048] Next, the information generation unit 23 calculates the activity amount for activities for which the activity amount has not been calculated among the recommended activities acquired for each time zone (here, activities that are set to have a variable activity amount in the activity database).

[0049] The method by which the information generation unit 23 calculates the activity amount here may be, for example, dividing the residual activity amount by the number of activities for which the activity amount has not been calculated to obtain the activity amount for each activity. The information generation unit 23 generates recommended activity information for one day for the user by the processes exemplified above.

[0050] The output control unit 24 presents the recommended activity information generated by the information generation unit 23 to the corresponding user. As a result, the user can know the types of activities and the goals for the amount of activities that should be performed in each time zone of the day.

[0051] [Operation] The information processing apparatus 1 of the present embodiment performs the operations exemplified above and operates as follows.

[0052] In the following example, user B, a 70-year-old female receiving diabetes treatment from a doctor, sets the change amount α of the HbA1c value every three months as activity target information to the information processing apparatus 1 according to the doctor's instructions. The information processing apparatus 1 accepts this setting. It is assumed that this user B has set environmental information such that she does housework in the morning, goes shopping in the afternoon, does housework in the evening, and goes to bed early at night.

[0053] The information processing apparatus 1 converts the received activity target information into information on the activity amount in a common unit (the number of steps). Here, the information processing apparatus 1 uses a machine learning model that has been machine-learned to output the value of the number of steps corresponding to the required activity amount for a predetermined period (for example, per day) with the change amount of the HbA1c value of the subject during a predetermined period when the activity was being performed as the input, and obtains the required activity amount for one day of this user B in terms of the number of steps, which is a common unit, based on the change amount of the HbA1c value set as activity target information. Here, it is assumed that the number of steps is calculated to be 3000 steps.

[0054] The information processing device 1 acquires information representing the daily physical activity amount target other than basal metabolism (hereinafter referred to as the actual target activity amount) from the activity database. As already described, this physical activity amount is calculated by the server 2 from information such as the user's age and weight, and here it is assumed to be set to, for example, "3000 steps".

[0055] The information processing device 1 operates, for example, before the user's wake-up time (which may be a predetermined time such as 4:00 am), and refers to the physical information and environmental information of this user B to extract information identifying the types of activities that satisfy the implementation conditions in each time period of the morning, morning, afternoon, evening, and night of the day from the activity database, and sequentially determines the activities in each of the above time periods. Hereinafter, the case where the process is executed in the morning on weekdays will be described as an example.

[0056] In this example, the information processing device 1 extracts activities determined to be in an appropriate time period in the morning on weekdays from the activity database. As in the example described above, examples of activities that take the morning time period as an appropriate time period include not only exercises such as walking and running, but also activities in daily life such as housework and commuting. Here, it is assumed that the implementation conditions for "walking" and "running" are set as "temperature 25 degrees or less, not rainy, outdoors, implementation time 30 minutes or more, commuting not included in the morning time period, taboos: heart disease...", etc. Also, as the implementation condition for "commuting", a condition such as "the user's environmental information includes morning commuting" is set.

[0057] Regarding user B, since the environmental information does not include information indicating commuting during the morning time period on weekdays, the information processing device 1 does not extract the activity of "commuting". Therefore, the information processing device 1 extracts "walking" or "running" as the activity to be performed by user B in the morning on weekdays.

[0058] Initially, for example, the information processing device 1 may randomly select any activity and present it as a recommended activity to user B for activities to be done in the morning. Also, if there is an input indicating an activity that was recommended in the past but that user B does not want to do, the information to that effect is added to the activity database. For example, when user B sets "running" as an activity they do not prefer, the information processing device 1 adds information such as "avoided by user" to the activity characteristic information, for example, in association with the information identifying the "running" activity in the activity database.

[0059] Then, when extracting activities, the information processing device 1 extracts activities for which the information "avoided by user" is not added. In this example, for user B, the information processing device 1 avoids "running" as an activity to be done on weekdays in the morning and extracts "walking".

[0060] Similarly, the information processing device 1 extracts activities (recommended activities) that are suitable to be done in each time period such as in the morning, afternoon... from the activity database with reference to the physical information and environmental information of user B. Here, it is assumed that the information processing device 1 Morning: Walking Morning: Cleaning, Laundry,... Afternoon: Shopping Evening: Cooking, Tidying up,... Night: Gymnastics indoors determines recommended activities such as these. Among the above activities, · Cleaning · Laundry · Shopping · Cooking · Tidying up are assumed to have a fixed amount of activity determined in advance, for example, respectively: · Cleaning: Equivalent to 300 steps · Laundry: Equivalent to 100 steps · Shopping: Equivalent to 500 steps · Cooking: Equivalent to 200 steps · Tidying up: Equivalent to 100 steps and so on.

[0061] Furthermore, for each of the recommended activities determined for each time period, the information processing apparatus 1 generates information on the amount of activity to be recommended. The information processing apparatus 1 subtracts the basal metabolism component from the activity target information converted into information on the amount of activity in a common unit to obtain the amount of activity to be performed by activities other than basal metabolism.

[0062] Next, the information processing apparatus 1 obtains the total amount of activity for activities such as commuting and housework, whose activity amounts are set as fixed in the activity database, among the recommended activities acquired for each time period. In the case of this user B, various housework corresponds to this.

[0063] In the above example, since the activity amounts are fixed for each activity of cleaning (equivalent to 300 steps), washing (equivalent to 100 steps), shopping (equivalent to 500 steps), cooking (equivalent to 200 steps), and tidying up (equivalent to 100 steps), the information processing apparatus 1 300 + 100 + 500 + 200 + 100 = 1200 and obtains this. Then, the information processing apparatus 1 subtracts the obtained total amount of activity from the actual target activity amount to obtain the residual activity amount: 3000 - 1200 = 1800 and obtains this.

[0064] The information processing apparatus 1 divides the value (1800) obtained here by the number of recommended activities whose activity amounts are variable to obtain the activity amount of each recommended activity. Therefore, in the above example, the information processing apparatus 1 determines the activity amount for each recommended activity as follows. Morning: Walking 1700 steps Morning: Cleaning, washing... 400 steps Afternoon: Shopping 500 steps Evening: Cooking, tidying up... 300 steps Night: Gymnastics (indoors) 100 steps Then, the information processing apparatus 1 uses this information as the recommended activity information.

[0065] The information processing apparatus 1 displays the recommended activity information generated in this way and presents it to the user B.

[0066] [Consideration of weather, etc.] Further, the information processing apparatus 1 may obtain information regarding the weather in the area where the information processing apparatus 1 is located (which can be detected by various well-known position information acquisition means) from a weather information service on the Internet or the like, and use it for determining recommended activities.

[0067] For example, when starting the process of determining the recommended activity for each time period, the information processing apparatus 1 obtains information on the temperature and weather in that area for each of those time periods.

[0068] Then, when the information processing apparatus 1 extracts the recommended activity from the activity database, it extracts the activity whose temperature and weather information match the implementation conditions. As an example, when the information on the afternoon temperature obtained by the information processing apparatus 1 is "35 degrees", and the implementation conditions for "running" are defined as "temperature 25 degrees or less, not rainy, outdoors, implementation time 30 minutes or more, not including commuting in the morning time period, taboos: heart disease...", etc., the information processing apparatus 1 does not extract "running" as an activity to be performed in the afternoon (it does not meet the condition of "25 degrees or less").

[0069] Also, for example, in an area where an outdoor restriction is required to prevent the spread of infectious diseases, the information processing apparatus 1 controls so as not to extract an activity with "outdoors" as an implementation condition as a recommended activity.

[0070] [Achievement acquisition] Furthermore, the information processing apparatus 1 may be provided with a step sensor, an acceleration sensor, etc. (not shown), collect information on the amount of activity performed by the user from the information of these step sensors, etc., and perform the following process immediately before the start of each time period for which the recommended activity is determined (for example, a few minutes before).

[0071] In this process, the information processing apparatus 1 subtracts the recommended activity information already implemented during that day (within the predetermined period for setting the recommended activity information) from the actual target activity amount (the activity amount excluding the activity amount corresponding to basal metabolism among the activity amounts of activities to be performed in a day) to obtain the remaining target activity amount.

[0072] Furthermore, the information processing apparatus 1 obtains a residual activity amount by subtracting the fixed activity amount from the activity amount of the recommended activities that are set to be carried out in a time zone after the time zone in which this process is being performed, and divides the residual activity amount by the number of variable activities among the recommended activities that are set to be carried out in a time zone after the time zone in which the process is being performed, thereby determining the activity amount to be recommended for the variable activities.

[0073] For example, in the case of the above-mentioned user B, when user B walks according to the morning recommended activity information and, for example, obtains that the number of steps is 1,500 steps, the information processing apparatus 1 determines the activity amount after the morning time zone as follows.

[0074] That is, the information processing apparatus 1 obtains the sum of the activities such as commuting and housework, whose activity amounts are fixedly set in the activity database, among the recommended activities obtained for each time zone after the morning. As described above, this sum is equivalent to 1,200 steps.

[0075] The information processing apparatus 1 subtracts the obtained sum of the activity amounts from the actual target activity amount (3,000 steps in the case of user B) to obtain a residual activity amount: 3000 - 1200 = 1800 to obtain.

[0076] When it is just before the end of the morning time zone, the information processing apparatus 1 further subtracts the activity amount (1500) of the activities already performed in the morning time zone from the residual activity amount (1800) obtained here, and divides it by the number of activities whose activity amount is set as variable in the activity database among the recommended activities acquired for each time zone after morning, to obtain the activity amount of each activity after afternoon. That is, at the end of each time zone, the information processing apparatus 1 subtracts the total activity amount of the activities performed so far from the actual target activity amount to obtain the residual activity amount, then subtracts the activity amount of the activities whose activity amount is fixed among the recommended activities in the subsequent time zone from the residual activity amount, and divides the target activity amount after the subtraction by the number of activities whose activity amount is set as variable among the recommended activities in the subsequent time zone, to determine the activity amount for each activity set as variable.

[0077] Specifically, in this example, the information processing apparatus 1 determines the activity amount of the recommended activities in the time zones after morning as follows. Morning: Cleaning, laundry... 400 steps Afternoon: Shopping 500 steps Evening: Cooking, tidying up... 300 steps Night: Gymnastics (indoors) 300 steps Then, the information processing apparatus 1 presents this information to the user as recommended activity information.

[0078] Note that here, among the residual activity amount, after subtracting the activity amount of the activities whose activity amount is fixed among the recommended activities in the subsequent time zone (the target activity amount after this subtraction is referred to as the distribution target activity amount for convenience), it is divided by the number of activities whose activity amount is set as variable among the recommended activities (the activity amount is set to be equal for the activities whose activity amount is variable), but the present embodiment is not limited to this, and weights may be set for each activity, and the distribution target activity amount may be divided at a ratio according to the weights, and the activity amount of each activity whose activity amount is variable may be set.

[0079] In addition, when the information on the amount of activity performed by the user is acquired in a unit other than the common unit, the information processing apparatus 1 converts the information into a value of the amount of activity in the common unit by a conversion method to the common unit set for the activity target information.

[0080] [Recommendation of alternative] Also, the information processing apparatus 1 may perform the following processing immediately before the start of each time period (for example, a few minutes before) in which the recommended activity is determined.

[0081] At this timing, the information processing apparatus 1 acquires information on the weather in the area where the information processing apparatus 1 is located from a weather information service on the Internet or the like, and determines whether the implementation conditions associated with the recommended activity determined for the time period after this processing time are satisfied for the activity.

[0082] Specifically, assume that the information processing apparatus 1 has determined "running" as the recommended activity in the nighttime time period. At this time, if the information on the nighttime temperature acquired in this processing is "30 degrees", and the implementation conditions for "running" are defined as "temperature 25 degrees or less, not rainy, outdoors, implementation time 30 minutes or more, not including commuting in the morning time period, taboos: heart disease...", etc., the information processing apparatus 1 determines that "running" is inappropriate as the activity to be performed at night, and extracts an activity (activity corresponding to the implementation conditions matching the acquired temperature information) to replace "running" and sets it as the activity to be performed at night.

[0083] In this example, for example, activities such as "gymnastics indoors" where the outside temperature is not included in the implementation conditions are extracted and proposed as alternative activities.

[0084] [Use for telemedicine, etc.] Furthermore, in an example of the present embodiment, it may be possible to present, to a doctor via, for example, a network, the amount of activity presented to the user (which may be the actual target activity amount) and the actual results of the user's activities. The doctor can refer to this information and consider, for example, resetting the target activity information. What is characteristic in the present embodiment is that information specifying the recommended activity is not transmitted. Also, since the actual target activity amount is also shown in a common unit, the doctor does not know what activities were presented to the user and what activities the user actually carried out, and the privacy of the user is also protected.

Explanation of Signs

[0085] 1 Information processing apparatus, 2 Server, 11 Control unit, 12 Storage unit, 13 Operation unit, 14 Display unit, 15 Communication unit, 21 Activity target setting unit, 22 Activity amount holding unit, 23 Information generation unit, 24 Output control unit.

Claims

1. means for receiving activity target information that is the target activity amount of a user; for activities of a plurality of types of users, for each type of activity, the activity amount for each predetermined unit amount is held as a value in a common unit with the unit related to any one of the activities as the common unit, and information holding means for holding the implementation conditions for each type of the activity; means for converting the received activity target information into activity amount information representing the activity amount to be performed in a predetermined period in the common unit; among the activities of the plurality of types of users, extracting activities that satisfy the implementation conditions, and based on the activity amount for each predetermined unit amount related to the extracted activities and the activity amount information that is the conversion result of the activity target information related to the user, information generation means for generating predetermined recommended activity information for the user; means for outputting the generated recommended activity information, an information processing apparatus including the same.

2. In the information processing apparatus according to claim 1, further, means for collecting information related to the activity amount of activities that the user has already performed within the predetermined period; means for converting the collected information related to the activity amount into information in a predetermined common unit; means for displaying the converted information; an information processing apparatus including the same.

3. In the information processing apparatus according to claim 2, the conversion is performed by a conversion method to a common unit set for the activity target information, an information processing apparatus.

4. In the apparatus according to claim 2 or 3, the information generation means subtracts the collected information on the activity amount from the activity amount represented by the activity target information of the user, and generates recommended activity information for the user based on the activity amount after the subtraction, an information processing apparatus.

5. In the apparatus according to any one of claims 1 to 4, The method for converting to the activity amount represented by the common unit is an information processing device determined in advance according to whether the activity amount target information is any of blood glucose control, lipid metabolism improvement, and bone density improvement.

6. A computer, means for receiving activity target information that is the target of the activity amount of the user; for each of a plurality of types of user activities, for each type of activity, the activity amount for each predetermined unit amount is held as a value of the common unit with the unit related to any one of the activities as the common unit, and the implementation conditions for each type of the activity are held information holding means; means for converting the received activity target information into activity amount information representing the activity amount to be performed in a predetermined period in the common unit; extracting activities that satisfy the implementation conditions among the plurality of types of user activities, and based on the activity amount for each predetermined unit amount related to the extracted activities and the activity amount information that is the conversion result of the activity target information related to the user, information generation means for generating predetermined recommended activity information for the user; means for outputting the generated recommended activity information; A program that functions as.

Images