JP6688022B2 - Information processing device and program - Google Patents

Description

  The present invention relates to an information processing device and a program.

  2. Description of the Related Art Conventionally, a massage device that massages a user by applying pressure to the user's neck, shoulders, waist, or the like has been used. The massage device has multiple massage menus prepared in advance regarding which part to be massaged, and the user selects a massage menu that focuses on the part that feels tired or stiff. can do.

  In addition, a sensor for acquiring the biometric information of the user is connected, the degree of stress is estimated from the acquired biometric information of the user, and an appropriate massage menu is automatically selected from the estimated degree of stress. A massage device is known (for example, refer to Patent Document 1).

JP, 2010-220820, A

  However, since the massage device described above selects the massage menu based only on the biometric information of the user, there is a possibility that an accurate massage menu may not be selected if the physical condition, fatigue level, etc. of the user do not appear in the biometric information. There was a problem.

  The disclosed technique has been made in view of the above, and an object thereof is to provide a technique capable of automatically selecting an appropriate massage menu.

  An information processing apparatus according to the disclosed technology is an information processing apparatus that generates a massage menu, and includes an acquisition unit that acquires biometric information of a user, behavior information of the user, and environment information, the biometric information, and the behavior. Based on at least one of the information and the environmental information, an estimation unit that estimates a stiffness region and a stiffness degree of the user's body, and an estimated stiffness region and a stiffness degree of the user's body And a generating unit for generating a massage menu, and an output unit for outputting the generated massage menu.

  According to the disclosed technique, a technique capable of automatically selecting an appropriate massage menu is provided.

It is a figure which shows an example of a structure of the information processing system which concerns on each embodiment. It is a figure showing an example of functional composition of an information processor concerning each embodiment. 5 is a flowchart showing an example of an estimation process performed by the information processing device according to the first embodiment. It is a figure which shows the specific example of various information (current) used for massage menu generation, and an estimated stiffness region. It is a figure which shows various information (past or future) used for massage menu generation, and the specific example of the estimated stiffness part. It is a figure for demonstrating the specific example of an estimation process. 9 is a flowchart showing an example of a processing procedure performed by the information processing device according to the second embodiment.

Hereinafter, embodiments will be described with reference to the drawings. In each drawing, the same components may be denoted by the same reference numerals, and duplicate description may be omitted. <Overview>
FIG. 1 is a diagram showing an example of the configuration of an information processing system according to each embodiment. As illustrated in FIG. 1, an information processing system according to an embodiment includes an information processing device 10 that generates a massage menu, and various types of information used when the information processing device 10 generates a massage menu (user biometric information). , An input source device 20 that holds user behavior information, environmental information such as a weather forecast, and the like, and an output destination device 30 that performs various processes using a massage menu output from the information processing device 10.

  The input source device 20 is, for example, the biometric sensor 21, the wearable terminal 22, or the information disclosure server 23. The biometric sensor 21 is attached to the user's body and can measure the blood flow rate and the like at the attached location. The wearable terminal 22 has functions such as GPS and a pedometer, and can measure the action history of the user wearing the wearable terminal 22 and the environmental information in the action range of the user. In addition, the wearable terminal 22 can also accept the input of the action history or the environment information that the user self-reports. The information disclosure server 23 is a server that publishes environmental information, for example, a server (site) that publishes weather forecasts (weather, temperature, humidity, probability of precipitation, etc.) on the Internet.

  The output destination device 30 is, for example, the information terminal 31 or the massage machine 32. The information terminal 31 has a function of displaying a massage menu generated by the information processing device 10, and the user performs massage treatment by showing the massage menu displayed on the screen of the information processing device 10 to the practitioner. It is envisioned that the usage pattern will be received. The information terminal 31 may be, for example, a smartphone or a PC (Personal Computer). The massager 32 is a device that applies a massage to the user by applying pressure to the user's neck, shoulders, waist, and other parts. The massage machine 32 in the present embodiment is supposed to massage the user according to the massage menu generated by the information processing device 10.

  In the present embodiment, the information processing device 10 acquires the biometric information of the user, the behavior information of the user, and the environment information from the input source device 20, and at least one of the acquired biometric information, the behavior information, and the environment information. Based on one or more of them, the stiffness region and the stiffness degree of the user's body are estimated. Further, the information processing device 10 generates a massage menu based on the estimated stiffness region and stiffness degree of the user's body, and outputs the generated massage menu to the output destination device 30.

<Functional configuration>
(Information processing device)
FIG. 2 is a diagram illustrating an example of a functional configuration of the information processing device according to each embodiment. As illustrated in FIG. 2, the information processing device 10 includes an acquisition unit 11, an estimation unit 12, a generation unit 13, an output unit 14, and a storage unit 15.

  The acquisition unit 11 has a function of acquiring various types of information (user's biometric information, user's behavior information, environment information) used to generate a massage menu from the input source device 20 and storing the acquired information in the storage unit 15. Further, the acquisition unit 11 may have a function of acquiring the massage menu actually given to the user from the output destination device 30 and storing the massage menu in the storage unit 15 as a massage history.

  Further, more specifically, the acquisition unit 11 determines the current biometric information of the user, the behavior information of the user, the current environmental information, the massage history of the user, the past environmental information, and the future environmental information. The environment information may be acquired and stored in the storage unit 15. Further, the acquisition unit 11 may acquire biometric information when the user is actually undergoing a massage from the biometric sensor 21 and store the biometric information in the storage unit 15. The acquisition unit 11 may acquire various information held by the input source device 20 at a timing when the information is added or updated, or may acquire the information at predetermined intervals.

  The estimation unit 12 has a function of estimating the stiffness region and the stiffness degree of the user's body based on various information stored in the storage unit 15. Note that the estimation unit 12 determines that if the future environmental information (weather forecast, etc.) has a predetermined environmental condition (low pressure, etc.), and the predetermined environmental condition also exists in the past environmental information, the predetermined environmental condition is given. It is also possible to estimate the stiffness region and stiffness degree of the user's body by further using the massage history corresponding to the date when the environmental condition was present in the past environmental information.

  Further, the estimation unit 12 may estimate the massage effect using biometric information when the user is undergoing massage.

  The generation unit 13 has a function of generating a massage menu based on the stiffness region and the stiffness degree of the user's body estimated by the estimation unit 12. Further, the generation unit 13 stores the generated massage menu in the massage history stored in the storage unit 15. When the estimation unit 12 estimates that the massage effect is not sufficient, the generation unit 13 adjusts the massage menu and outputs the adjusted massage menu to the output destination device 30 via the output unit 14. Good.

  The output unit 14 has a function of outputting the massage menu generated by the generation unit 13 to the output destination device 30.

  The storage unit 15 is realized by an HDD, a memory, or the like, and stores the biometric information, the behavior information, and the environment information acquired by the acquisition unit 11. In addition, the storage unit 15 stores a past massage menu generated by the generation unit 13 in the past, or a massage history that is fed back from the output destination device 30 and indicates a past massage menu actually given to the user. To do.

<System operation example>
Hereinafter, an operation example of the system will be described separately for the first embodiment and the second embodiment.

[First embodiment]
Next, an operation example of the information processing system according to the first embodiment will be described. The information processing device 10 massages based on only various information at present (current time) among various information stored in the storage unit 15, or based on both various information at present and various information at past or future. Create a menu.

(Example of processing procedure)
FIG. 3 is a flowchart illustrating an example of the estimation process performed by the information processing device according to the first embodiment. A processing procedure performed when the information processing apparatus 10 generates a massage menu will be described with reference to FIG.

  First, the estimation unit 12 acquires the biometric information of the user from the storage unit 15 (S101). Subsequently, the estimation unit 12 acquires the current behavior information and the current environment information of the user from the storage unit 15 (S102). Then, the estimation unit 12 proceeds to the processing procedure of step S106 when creating a massage menu based only on various information at present (at the present time), and based on both various information at present and various information at the past or in the future. When creating a massage menu, the process proceeds to step S104 (S103). In addition, whether the information processing apparatus 10 creates a massage menu based only on various information at present (at the present time) or whether to create a massage menu based on both various information at present and various information in the past or future, You may make it switch according to a user's instruction.

  Subsequently, the estimation unit 12 acquires the past environmental information, the future environmental information, and / or the user's future behavior information from the storage unit 15 (S104). Subsequently, the estimation unit 12 acquires the massage history of the user from the storage unit 15 (S105).

  Subsequently, the estimation unit 12 estimates the user's stiffness region and degree of stiffness using the acquired various information (S106). In addition, the estimation unit 12 may estimate the user's stiffness region by comparing the value of each collected data with a predetermined threshold value corresponding to each collected data. It should be noted that specific examples of each collected data and details of the corrosive part estimated from each collected data will be described later.

  The degree of collision is estimated, for example, by adding up the correlating portion estimated from each of a plurality of (current, past, or future) various information. For example, if the stiffness region estimated from the current blood flow of the user is “neck” and “shoulder” and the stiffness region estimated from the number of steps on the day is “shoulder” and “waist”, The part and the degree of stiffness may be estimated as “neck: collision degree = 1”, “shoulder: collision degree = 2”, and “waist: collision degree = 1”. Further, the degree of collation may be obtained by multiplying a predetermined weighting coefficient for each collection data, rather than simply adding the correlation parts estimated from each of the plurality of collection data. For example, when the weighting coefficient that is doubled is applied to the colloidal portion estimated from the current blood flow of the user, the above-mentioned colloidal portion and the degree of collation are “neck: collation degree = 2. , “Shoulder: collision degree = 3”, and “waist: collision degree = 1”.

  Further, different weighting factors may be multiplied by the degree of collision of the collated part estimated from various kinds of current information and the degree of collision of the collated part estimated from various kinds of past or future information.

  Subsequently, the generation unit 13 generates a massage menu based on the estimated stiffness region and the degree of stiffness, and the output unit 14 outputs the generated massage menu to the output destination device 30 (S107). The generation unit 13 may generate the massage menu by including all of the estimated colic regions and multiplying the degree of collision for each of the colloidal regions by a predetermined time. For example, when the estimated stiffness region and stiffness degree are “neck: collision degree = 2”, “shoulder: collision degree = 3”, and “waist: collision degree = 1”, “neck: 10 minutes, shoulder : 15 minutes, waist: 5 minutes ”may be generated.

  In addition, the generating unit 13 focuses on the colloidal part that includes all the estimated correlating parts from a plurality of massage menus stored in advance in the memory or the like, and has the largest correlating ratio among the correlating parts. A massage menu to be massaged may be selected.

  The processing procedure performed when the information processing device 10 generates a massage menu has been described above. Next, a specific example of various information in the present condition (present), a specific example of various information in the past or the future, and a specific example of a cortical part that can be estimated from these various information will be described.

(Specific examples of various information (current) and estimated cortical part)
FIG. 4 is a diagram showing a specific example of various pieces of information (current) used for generating a massage menu and an estimated stiffness region. The various types of information (current) used when the information processing apparatus 10 estimates a massage menu are roughly divided into the current biometric information of the user, the current behavior information of the user (including the behavior history of a certain day), And the current environmental information (including the environmental information of one day).

  The “data acquisition source” shown in FIG. 4 is an example of a sensor or the like that outputs the information shown in the “collected data”, and these sensors are assumed to be provided in the input source device 20. The “estimation of behavior or symptom” means the behavior of the user or the symptom that the user feels (is supposed to feel). The “estimated stiffness region” indicates an example of the stiffness region in the user's body, and is estimated by comparing the value of “collected data” with a predetermined threshold value corresponding to the collected data, for example. In addition, the estimation unit 12 holds in advance mapping information in which the value of “collected data” is associated with a cortical site estimated to be a predetermined threshold, and compares the mapping information with the value of collected data. By doing so, the stiffness region may be estimated.

  The current biometric information is information output from the biometric sensor 21 mounted on the user's body. When the blood flow rate measured at the site where the biometric sensor 21 is attached is small (or the blood flow rate is slow or the blood volume is low), it can be estimated that the site has stiffness due to poor circulation. Good. In the example of FIG. 4, the biosensors 21 are attached to the user's neck, shoulders, waist, and head, and the blood flow rate at each site is smaller than a predetermined threshold value (or the blood flow velocity is slower than a predetermined threshold value). , Or the blood volume is less than a predetermined threshold value), it can be estimated that stiffness is occurring in the user's neck, shoulders, waist or head. If the biometric sensor 21 is attached to one place, it may be estimated whether or not the stiffness is generated only in the attached portion. Further, when the biometric sensor 21 is attached to the user's finger, it is assumed that it is difficult to estimate the specific stiffness region. In this case, the estimation unit 12 may estimate the stiffness portion based on other various information without estimating the stiffness portion by the biosensor 21.

  In the current biometric information, the items measured by the biometric sensor are a heartbeat and a pulse in addition to the blood flow rate (and blood velocity, blood volume) or instead of the blood flow rate (or blood velocity, blood volume). It may be number, skin temperature, sweat rate, pulse wave, EEG, blood pressure, or body temperature.

  The current action information is information output from various sensors included in the wearable terminal 22 worn by the user. The estimation unit 12 uses the data output from the acceleration sensor, the GPS, or the pedometer to measure the number of steps of the user (on a certain day), the travel distance of the user (on a certain day), and the user (for a certain day). The stiffness region is estimated by comparing the amount of exercise with a predetermined threshold value. For example, when the number of steps is large, the moving distance is long, and the amount of exercise is large, the estimation unit 12 determines that the user has “walked a lot” and estimates that the legs and waist have stiffness, and the number of steps is low. If the distance traveled is short and the amount of exercise is small, it is judged that the person has been “sitting and sitting”, and it is estimated that there is stiffness on the shoulders and hips, and the number of steps is long, the amount of movement is short, and the amount of exercise is small. It is possible to judge that “was standing” and to estimate that the waist has stiffness.

  Similarly, the estimation unit 12 can estimate whether the shoulder, waist or head of the user has stiffness by comparing the output value of the heartbeat sensor or the electroencephalogram sensor with a predetermined threshold value. In addition, the estimation unit 12 determines the posture of the user by comparing the output value of the motion sensor with a predetermined threshold value, and when the user has a stoop, the neck and shoulder of the user are stiff. Therefore, when the user bends forward, it may be estimated that stiffness is occurring on the waist of the user.

  Further, the estimation unit 12 determines the amount of sleep and the quality of sleep of the user by comparing the output value of the sleep sensor with a predetermined threshold value, and when the quality of sleep is poor, the sole of the user (pot). It may be estimated that the user needs to be stimulated, and if the user is not sleeping well, it may be estimated that stiffness is occurring on the shoulder of the user. In addition, the estimation unit 12 determines the degree of tension of the user by comparing the output value of the heartbeat sensor or the non-contact pulse wave detection sensor with a predetermined threshold value, and when the user is continuously in tension. May be estimated to have stiffness in the shoulder. In addition, the estimation unit 12 determines whether the user's eyes are tired by comparing the output value of the electro-oculography sensor with a predetermined threshold value, and when the eyes are tired, the estimation unit 12 applies to the head, neck, and shoulders. It may be estimated that stiffness is occurring.

  In addition, the estimation unit 12 determines the smoking amount of the user by comparing the pulse oximeter output value with a predetermined threshold value or by the user's self-report, and when the smoking amount of the user is large, shoulder, It may be estimated that stiffness is occurring in the waist and head.

  The current environment information is information output from various sensors that the wearable terminal 22 worn by the user has, or information disclosed by the information disclosure server 23. For example, the estimation unit 12 compares the atmospheric pressure, the temperature, and the humidity of the day obtained from the temperature / humidity sensor or the information disclosure server 23 with a predetermined threshold value, and is placed in an environment in which the user is deprived of body temperature. In this case, it may be estimated that the neck, shoulders, and the entire lower half of the body have stiffness, or if the day is low pressure, it may be estimated that the shoulders and hips have stiffness.

  In addition, the estimation unit 12 compares the noise amount obtained from the sound level meter and the noise measurement application with a predetermined threshold value, and when the user is in a tense state in a noisy place, stiffness is generated in the neck and shoulder. You may presume that you are doing. In addition, the estimation unit 12 determines whether the user has been in the crowd for a long time by comparing the output value of the infrared / carbon dioxide sensor with a predetermined threshold value, and if the user is in the crowd for a long time. May estimate that stiffness is occurring in the shoulder and the head.

  Although an example of various pieces of information (current) and the estimated colliated portion has been described above with reference to FIG. 4, FIG. 4 is merely an example, and the estimation unit 12 may collate the portion different from the example illustrated in FIG. May be estimated to have occurred.

(Specific examples of various information (past or future) and estimated cortical part)
FIG. 5 is a diagram showing a specific example of various pieces of information (past or future) used to generate a massage menu and an estimated stiffness region.

  The past or future behavior information is information acquired from the scheduler of the user held in the wearable terminal 22 or the like. The estimation unit 12 estimates a possible cortical site in the future based on a future event of the user included in the scheduler.

  For example, when the schedule of the next day of the scheduler includes a plan to participate in a plurality of conferences, the estimation unit 12 estimates that the neck and shoulders of the user will be stiff due to the tension caused by the participation in the conference. Good.

  Further, for example, when the schedule of the next day of the scheduler includes a long-distance business trip schedule, the estimation unit 12 may estimate that the shoulder and the waist will be stiff due to sitting for a long time. Furthermore, when the means of transportation is the Shinkansen / airplane or the like, the estimating unit 12 may estimate that when sitting on a narrow chair for a long time, stiffness is generated not only on the shoulders and waist, but also on the entire lower body.

  In addition, the estimation unit 12 may store the specific behavior pattern and the cortical region corresponding to the specific behavior pattern in advance and estimate the cortical region by extracting the specific behavior pattern from the scheduler. Good. For example, when the schedule of the day after the scheduler includes the schedule of all-day desk work that continues every day, the estimation unit 12 may estimate that the shoulder and the waist will be stiff due to sitting for a long time. In addition, the estimation unit 12 may estimate that the neck, shoulders, and waist will be stiff due to eye fatigue caused by long-term PC operation in addition to sitting for a long time.

  In addition, when the same schedule as the schedule of the next day exists in the past schedule in the scheduler, the estimation unit 12 acquires a massage menu performed on the same date as the past schedule from the massage history and acquires the acquired massage. You may make it estimate the site | part which a stiffness may generate from a menu. Furthermore, the degree of stiffness of a region where stiffness may occur is estimated from the massage time of each region in the obtained massage menu, and the estimated amount of stiffness is added in the processing procedure of step S106 in FIG. Good.

  In addition, the estimation unit 12 identifies a caution day in the user's body rhythm from the biorhythm predicted from the user's date of birth, and if the current date is close to the caution day, stiffness occurs in the entire body. It may be estimated.

  The past environmental information is the history of past meteorological data (pressure, temperature and humidity) accumulated in the wearable terminal 22 worn by the user, or past meteorological data published by the information disclosure server 23. (Atmospheric pressure, temperature and humidity). The future environment information is a predicted value of future weather data (atmospheric pressure, temperature, and humidity) disclosed by the information disclosure server 23. The estimation unit 12 may estimate a possible stiffness region in the future by combining past environmental conditions, future environmental information, and a massage history.

  Here, a specific example of the estimation process will be described with reference to FIG. 6A shows an example of a massage history, FIG. 6B shows an example of past environmental information (past weather), and FIG. 6C shows a future environmental information (weather forecast). This is an example. The current date is assumed to be around May 15th, for example. In addition, in FIG. 6A, the “correction part” indicates a part added to the massage menu by the user. "Time" indicates the time of the entire massage menu. The “additional menu” refers to a massage part that the user added himself / herself after the massage is finished. For example, when the user feels that the stiffness has not been resolved after the massage is finished, the user assumes the massage site added by himself.

  The estimation unit 12 confirms whether or not there is a predetermined environmental condition (for example, low pressure) in future (approximately one week) environmental information (weather forecast). In the example of FIG. 6C, since the atmospheric pressure on May 17 is 980.8 hPa, the estimation unit 12 determines that the low pressure exists in the environmental information (weather forecast) for about one week.

  Next, the estimation unit 12 is. It is confirmed whether the date of the environmental condition that matches the predetermined environmental condition exists in the past environmental information. In the example of FIG. 6B, since the atmospheric pressure on May 2 is 980.4 hPa, the estimation unit 12 determines that there is a low pressure day on May 2.

  Then, the estimation part 12 acquires the massage history on that day, and estimates a stiffness region from the acquired massage history. In the example of FIG. 6A, the estimation unit 12 acquires the massage history on May 2. The massage menu on May 2 is a foot-focused massage menu, and "neck" is added as an additional menu. In this case, the estimation unit 12 estimates that the stiffness region is the “foot” and the “neck”.

  Although an example of various pieces of information (past or future) and an estimated cortical part has been described above with reference to FIGS. 5 and 6, the examples shown in FIGS. It may be estimated that the stiffness is generated in a portion different from that in FIG.

[Second embodiment]
Next, a second embodiment will be described based on the drawings. Note that description of the same components as those of the first embodiment will be omitted. In addition, points not particularly mentioned may be the same as those in the first embodiment.

  The second embodiment assumes a situation in which the user is actually undergoing a massage operation based on the massage menu output from the information processing device 10. The information processing apparatus 10 according to the second embodiment performs tuning of the massage menu based on the feedback from the biometric sensor 21 worn by the user.

  FIG. 7 is a flowchart showing an example of a processing procedure performed by the information processing apparatus according to the second embodiment.

  The processing procedure of step S201 is the same as that of steps S101 to S107 of FIG. Then, a massage is given to the user based on the massage menu output in step S201 (S202).

  Subsequently, the acquisition unit 11 of the information processing device 10 acquires the biometric information of the user from the biometric sensor 21 attached to the user (S203). The acquired biological information is, for example, the blood flow rate, blood flow velocity, or blood volume of the user. Subsequently, the estimation unit 12 estimates whether or not the massage effect is sufficient from the acquired biological information (S204). If it is estimated that the massage effect is sufficient, the process proceeds to step S206, and if it is estimated that the massage effect is not sufficient, the process proceeds to step S205. For example, the estimation unit 12 may estimate whether or not the massage effect is sufficient by determining whether or not the blood flow rate in the user's stiffness region estimated in step S201 has improved. . It should be noted that whether or not the blood flow rate has improved may be determined by, for example, whether or not the blood flow rate exceeds a predetermined threshold value.

  Subsequently, the generation unit 13 tunes (adjusts) the massage menu, and the output unit 14 outputs the tuned massage menu to the output destination device 30 (S205). For example, the generation unit 13 may increase the massage time of a part of the massage menu where the blood flow is not improved, or may gradually increase the massage time of all parts, or other You may make it tune by a method.

  In step S206, the output unit 14 outputs the biometric information acquired in the processing procedure of step S203 to the output destination device 30 so that the user can refer to the biometric information after the massage treatment. The output biometric information is displayed on the screen of the information terminal 31 or the screen of the massage machine 32, for example.

<Summary>
The information processing device 10 in each of the above-described embodiments acquires the biometric information of the user, the behavior information of the user, and the environment information from the input source device 20, and at least one of the acquired biometric information, the behavior information, and the environment information. Based on three or more, the stiffness region and stiffness degree of the user's body are estimated. Further, the information processing device 10 automatically generates a massage menu based on the estimated stiffness region and stiffness degree of the user's body, and outputs the generated massage menu to the output destination device 30. This allows the user to receive a massage menu suitable for his / her condition. Moreover, this allows the user to receive an appropriate massage operation without selecting the massage menu by himself.

  Further, the information processing device 10 in each embodiment uses the future behavior information / environment information in addition to the user's current biometric information, the user's current behavior information, or the current environment information. The body stiffness area and the degree of stiffness were estimated. As a result, the user can prevent body stiffness that may occur in the future depending on changes in weather conditions.

  Further, the information processing apparatus 10 according to the second embodiment enables tuning (adjustment) of the massage menu based on the biometric information of the user during the massage operation. This allows the user to receive a more effective massage treatment.

  Further, the information processing apparatus 10 according to the second embodiment is capable of outputting the biological information after the massage treatment to the output destination apparatus 30. Thereby, the user can grasp the biological information (for example, blood circulation state) after the massage, and can visually feel the massage effect.

<Supplement to Embodiment>
In each embodiment, the information terminal 31 or the massage machine 32 may have all the functions of the information processing apparatus 10.

  The present invention is not limited to the above-described embodiments, and various modifications and applications are possible within the scope of the claims.

  As described above, the function of the information processing apparatus 10 according to the embodiment executes the program corresponding to the processing performed by the information processing apparatus 10 by using the hardware resources such as the CPU and the memory included in the information processing apparatus 10. It can be realized by Further, the program can be stored in a storage medium.

10 information processing device 11 acquisition unit 12 estimation unit 13 generation unit 14 output unit 15 storage unit 20 input source device 21 biometric sensor 22 wearable terminal 23 information disclosure server 30 output destination device 31 information terminal 32 massage machine

Claims (3)

An information processing device for generating a massage menu,
An acquisition unit for acquiring biometric information of the user, behavior information of the user, massage history of the user, past environmental information, current environmental information, and future environmental information;
Based on at least one of the biometric information, the behavior information, the massage history, the past environmental information, the present environmental information, and the future environmental information, the stiffness region and stiffness degree of the user's body An estimation unit for estimating
A generation unit that generates a massage menu based on the estimated stiffness region and stiffness degree of the user's body,
An output unit that outputs the generated massage menu,
Have
The estimation unit is
In the case where a predetermined environmental condition exists in the future environmental information and the predetermined environmental condition also exists in the past environmental information, the predetermined environmental condition is added to the date when the past environmental information exists. An information processing apparatus for estimating a stiffness region and a stiffness degree of the user's body using the corresponding massage history. The acquisition unit acquires biometric information when the user is receiving a massage,
The estimation unit estimates the massage effect using the biological information when the user is receiving a massage,
The information processing apparatus according to claim 1, wherein the generation unit adjusts the massage menu when the estimation unit estimates that the massage effect is not sufficient. A program in an information processing device for generating a massage menu,
In the information processing device,
A step of obtaining biometric information of the user, behavior information of the user, massage history of the user, past environmental information, present environmental information and future environmental information;
Based on at least one of the biometric information, the behavior information, the massage history, the past environmental information, the present environmental information, and the future environmental information, the stiffness part and stiffness degree of the user's body. Estimating Eq.
Generating a massage menu based on the estimated stiffness region and stiffness degree of the user's body,
Outputting the generated massage menu,
Run
The estimating step includes
When the predetermined environmental condition exists in the future environmental information and the predetermined environmental condition also exists in the past environmental information, the predetermined environmental condition is set to the date when the past environmental information exists. A program for estimating the stiffness region and stiffness degree of the user's body using the corresponding massage history.

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