Information processing device, information processing system, information processing method, and program

Abstract

The purpose of the present invention is to achieve a configuration that enables a user to appropriately perform rehabilitation while confirming whether or not the user is performing appropriate exercise according to an exercise prescription. The present invention has: an exercise type inference unit for inferring the type of exercise which a user is performing on the basis of detection information from a sensor mounted on the user's body; a database for storing user-specific exercise intensities corresponding to types of exercise; an exercise type / personally tailored exercise intensity acquisition unit for acquiring, from the database, an exercise type / personally tailored exercise intensity, which is a user-specific exercise intensity corresponding to the type of exercise inferred by the exercise type inference unit; and an exercise performing status analysis unit for analysing exercise performing status data generated on the basis of the exercise type / personally tailored exercise intensity acquired from the database, and generating an exercise performing status analysis result indicating whether or not the user is performing appropriate exercise according to an exercise prescription preliminarily generated. The exercise performing status analysis result generated is output to a display unit.

Description

[Technical field]

[0001] The present disclosure relates to an information processing device, an information processing system, an information processing method, and a program, and more particularly to an information processing device, an information processing system, an information processing method, and a program that analyze the execution state of rehabilitation. [Background technology]

[0002] For example, when a patient suffers from a heart disease such as a myocardial infarction, the patient undergoes treatment such as surgery at a hospital, and thereafter undergoes rehabilitation while hospitalized in order to regain his or her physical strength.

[0003] However, there are limits on the length of stay at the hospital and the rehabilitation period, and after being discharged, patients are required to undergo outpatient rehabilitation according to a program created by the hospital, or voluntary home rehabilitation at home, etc.

[0004] When undergoing rehabilitation at a hospital, patients can exercise appropriately under the supervision of a specialist, but when undergoing rehabilitation at home, patients must exercise independently without the supervision of a specialist. In this case, patients must decide for themselves whether the amount of exercise is appropriate, which creates the problem of difficulty in performing rehabilitation with the optimal amount of exercise. In particular, in the case of heart disease, excessive exercise may actually worsen the condition.

[0005] Incidentally, examples of conventional techniques disclosing configurations for allowing a patient to perform appropriate rehabilitation include Patent Document 1 (JP Patent Publication No. 2014-018213) and Patent Document 2 (JP Patent Publication No. 2016-158711).

[0006] Patent Document 1 discloses a configuration in which a patient undergoing rehabilitation wears a user terminal that detects pulse, and appropriate pulse rate range data is sent to the user terminal from an instructor terminal at the hospital, and the patient refers to the pulse rate sent to the user terminal and performs rehabilitation so that the pulse rate that increases with exercise falls within the range of the received pulse rate.

[0007] However, pulse rate is mostly calculated based on the periodicity of blood flow, and during vigorous exercise such as sports, blood flow becomes significantly turbulent, making it difficult to observe the periodicity. In this case, the pulse rate differs significantly from the actual heart rate. For this reason, it can be said that monitoring the pulse rate alone is insufficient to check whether the person is exercising appropriately.

[0008] Patent Document 2 discloses a configuration in which a patient undergoing rehabilitation wears electrocardiogram underwear that measures the electrocardiogram, the electrocardiogram is acquired, and the user's position is acquired using a position information detection device. The electrocardiogram and user position are then transmitted via the user's terminal to a hospital terminal, and the hospital analyzes the user's amount of exercise and cardiac condition.

[0009] In this document, the amount of exercise of a user is measured based on the change in the user's position, and the amount of exercise is estimated when the user is running or walking. However, the exercise performed by the user is not limited to the exercise accompanied by such a change in position. For example, the user may exercise using a fitness machine such as an indoor running machine or a stationary bike (e.g., an exercise bike (registered trademark)). When exercising using such a machine, the change in the user's position cannot be observed, and therefore the amount of exercise cannot be estimated. This is a problem. [Prior art documents] [Patent documents]

[0010] [Patent Document 1] JP 2014-018213 A [Patent Document 2] JP 2016-158711 A Summary of the Invention [Problem to be solved by the invention]

[0011] The present disclosure has been made in consideration of, for example, the above-mentioned problems, and aims to provide an information processing device, an information processing system, an information processing method, and a program that enable each user to perform optimal rehabilitation by taking into account the exercise intensity according to the type of exercise performed by each user performing rehabilitation. [Means for solving the problem]

[0012] A first aspect of the present disclosure is an exercise type estimation unit that estimates an exercise type performed by a user based on sensor detection information; A database storing the user's unique exercise intensity corresponding to the type of exercise; an exercise type / individual exercise intensity acquisition unit that acquires, from the database, an exercise type / individual exercise intensity that is specific to the user and corresponds to the exercise type estimated by the exercise type estimation unit; The information processing device has an exercise implementation status analysis unit that analyzes exercise implementation status data generated based on the exercise type and individual exercise intensity obtained from the database, and generates exercise implementation status analysis results indicating whether the exercise being performed by the user is in accordance with a previously generated exercise prescription.

[0013] Furthermore, a second aspect of the present disclosure is an exercise type estimation unit that estimates an exercise type performed by a user based on sensor detection information; a steady-state activity amount analysis unit that inputs the estimated type of exercise estimated by the exercise type estimation unit and the user's breath gas analysis result to calculate the exercise type and individual corresponding activity amount based on the breath analysis result; an exercise-intensity-based exercise-type / individual-corresponding activity amount calculation unit that acquires a standard exercise intensity corresponding to the exercise type estimated by the exercise-type estimation unit from an exercise-type-based standard exercise intensity database that stores standard exercise intensities corresponding to the exercise types, and calculates an exercise-intensity-based exercise type / individual-corresponding activity amount based on the acquired standard exercise intensity and the user's body weight; (a) the type of exercise and the amount of individual activity based on the breath analysis results; (b) the exercise type and individual activity amount based on the exercise intensity; The information processing device has an exercise type / individual exercise intensity calculation unit that calculates an exercise type / individual exercise intensity, which is an exercise intensity corresponding to the user's exercise type, based on the above data (a) and (b).

[0014] Furthermore, a third aspect of the present disclosure is An information processing system having a user terminal and a hospital terminal, The user terminal, an exercise type estimation unit that estimates an exercise type performed by a user based on sensor detection information; A database storing the user's unique exercise intensity corresponding to the type of exercise; an exercise type / individual exercise intensity acquisition unit that acquires, from the database, an exercise type / individual exercise intensity that is specific to the user and corresponds to the exercise type estimated by the exercise type estimation unit; a communication unit that transmits exercise implementation status data generated based on the exercise type and individual exercise intensity obtained from the database to the hospital terminal; The hospital terminal includes: an exercise implementation status analysis unit that analyzes the exercise implementation status data received from the user terminal and generates an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with a previously generated exercise prescription; a communication unit that transmits the exercise implementation status analysis result generated by the exercise implementation status analysis unit to the user terminal; The user terminal, The information processing system displays the exercise implementation status analysis results received from the hospital terminal on a display unit.

[0015] Furthermore, a fourth aspect of the present disclosure is An information processing system having a user terminal and a geographic information providing server, The user terminal, an exercise type estimation unit that estimates an exercise type performed by a user based on sensor detection information; A database storing the user's unique exercise intensity corresponding to the type of exercise; an exercise type / individual exercise intensity acquisition unit that acquires, from the database, an exercise type / individual exercise intensity that is specific to the user and corresponds to the exercise type estimated by the exercise type estimation unit; a peak oxygen intake rate calculation unit that inputs the exercise type and individual exercise intensity acquired by the exercise type and individual exercise intensity acquisition unit and calculates a peak oxygen intake rate corresponding to the exercise type performed by the user; a communication unit that generates exercise prescription information for realizing the maximum value corresponding oxygen intake rate based on the maximum value corresponding oxygen intake rate calculated by the maximum value corresponding oxygen intake rate calculation unit, and transmits the generated exercise prescription information to the geographic information providing server; The geographic information providing server includes: an exercise prescription corresponding action route information generating unit that analyzes the exercise prescription information received from the user terminal and generates exercise prescription corresponding action route information for implementing the exercise prescription information; A communication unit that transmits the exercise prescription corresponding action route information to the user terminal, The user terminal, The information processing system displays the exercise prescription corresponding action route information received from the geographic information providing server on a display unit.

[0016] Furthermore, a fifth aspect of the present disclosure is An information processing method executed in an information processing device, an exercise type estimating step in which an exercise type estimating unit estimates an exercise type performed by a user based on sensor detection information; an exercise type / individual exercise intensity acquisition step in which an exercise type / individual exercise intensity acquisition unit acquires, from a database, an exercise type / individual exercise intensity that is an exercise intensity specific to the user corresponding to the exercise type estimated by the exercise type estimation unit; The information processing method includes an exercise implementation status analysis step in which an exercise implementation status analysis unit analyzes exercise implementation status data generated based on the exercise type and individual-specific exercise intensity obtained from the database, and generates an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with a previously generated exercise prescription.

[0017] Furthermore, a sixth aspect of the present disclosure is An information processing method executed in an information processing device, an exercise type estimating step in which an exercise type estimating unit estimates an exercise type performed by a user based on sensor detection information; A steady-state activity amount analysis step in which a steady-state activity amount analysis unit inputs the estimated type of exercise estimated by the exercise type estimation unit and the user's exhaled gas analysis result to calculate an exercise type and individual corresponding activity amount based on the exhaled gas analysis result; an exercise-intensity-based exercise-type / individual-corresponding activity amount calculation step in which an exercise-intensity-based exercise-type / individual-corresponding activity amount calculation unit acquires a standard exercise intensity corresponding to the exercise type estimated by the exercise-type estimation unit from an exercise-type-corresponding standard exercise intensity database storing standard exercise intensities corresponding to exercise types, and calculates an exercise-intensity-based exercise type / individual-corresponding activity amount based on the acquired standard exercise intensity and the user's body weight; The exercise type and individual exercise intensity calculation section (a) the type of exercise and the amount of individual activity based on the breath analysis results; (b) the exercise type and individual activity amount based on the exercise intensity; The information processing method includes executing an exercise type / individual-adapted exercise intensity calculation step for calculating an exercise type / individual-adapted exercise intensity, which is an exercise intensity adapted to the user corresponding to the exercise type, based on each of the data (a) and (b) above.

[0018] Furthermore, a seventh aspect of the present disclosure is A program for causing an information processing device to execute information processing, an exercise type estimating step of causing an exercise type estimating unit to estimate an exercise type performed by a user based on sensor detection information; an exercise type / individual exercise intensity acquisition step of causing an exercise type / individual exercise intensity acquisition unit to acquire, from a database, an exercise type / individual exercise intensity that is an exercise intensity specific to the user corresponding to the exercise type estimated by the exercise type estimation unit; The program causes the exercise implementation status analysis unit to execute an exercise implementation status analysis step of analyzing the exercise implementation status data generated based on the exercise type and individual exercise intensity obtained from the database, and generating an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with a previously generated exercise prescription.

[0019] Furthermore, an eighth aspect of the present disclosure is A program for causing an information processing device to execute information processing, an exercise type estimating step of causing an exercise type estimating unit to estimate an exercise type performed by a user based on sensor detection information; a steady-state activity amount analysis step of inputting the estimated type of exercise estimated by the exercise type estimation unit and the result of the breath gas analysis of the user to a steady-state activity amount analysis unit to calculate the type of exercise and the individual activity amount based on the breath analysis result; an exercise-intensity-based exercise type / individual-corresponding activity amount calculation step of causing an exercise-intensity-based exercise type / individual-corresponding activity amount calculation unit to acquire a standard exercise intensity corresponding to the exercise type estimated by the exercise type estimation unit from an exercise type-corresponding standard exercise intensity database storing standard exercise intensities corresponding to exercise types, and to calculate an exercise-intensity-based exercise type / individual-corresponding activity amount based on the acquired standard exercise intensity and the user's body weight; Exercise type and individual exercise intensity calculation section (a) the type of exercise and the amount of individual activity based on the breath analysis results; (b) the exercise type and individual activity amount based on the exercise intensity; The program executes an exercise type / individual exercise intensity calculation step for calculating an exercise type / individual exercise intensity, which is an exercise intensity for the user corresponding to the exercise type, based on the above data (a) and (b).

[0020] The program of the present disclosure is, for example, a program that can be provided by a storage medium or a communication medium in a computer-readable format to an information processing device or a computer system capable of executing various program codes. By providing such a program in a computer-readable format, processing according to the program is realized on the information processing device or the computer system.

[0021] Further objects, features, and advantages of the present disclosure will become apparent from the following detailed description of the embodiments of the present disclosure and the accompanying drawings. In this specification, a system refers to a logical collective configuration of multiple devices, and each device is not necessarily located in the same housing.

[0022] According to the configuration of one embodiment of the present disclosure, a configuration is realized that enables a user performing rehabilitation to appropriately perform rehabilitation while checking whether the exercise he or she is performing is appropriate in accordance with an exercise prescription. Specifically, for example, the device includes an exercise type estimation unit that estimates the type of exercise performed by a user based on detection information from a sensor worn by the user on the body, a database that stores user-specific exercise intensities corresponding to the types of exercise, an exercise type / individual-adapted exercise intensity acquisition unit that acquires from the database the exercise type / individual-adapted exercise intensity, which is the user-specific exercise intensity corresponding to the type of exercise estimated by the exercise type estimation unit, and an exercise implementation status analysis unit that analyzes exercise implementation status data generated based on the exercise type / individual-adapted exercise intensity acquired from the database and generates an exercise implementation status analysis result indicating whether the exercise performed by the user is in accordance with a previously generated exercise prescription, and outputs the generated exercise implementation status analysis result to a display unit. This configuration realizes a configuration that enables a rehabilitation performing user to appropriately perform rehabilitation while checking whether the exercise he or she is performing is appropriate exercise in accordance with an exercise prescription. It should be noted that the effects described in this specification are merely examples and are not limiting, and additional effects may also be provided. [Brief description of the drawings]

[0023] [Figure 1] FIG. 1 is a diagram illustrating an overview of processing according to the present disclosure. [Diagram 2] FIG. 1 is a diagram illustrating an overview of processing according to the present disclosure. [Diagram 3] FIG. 1 is a diagram illustrating an overview of processing according to the present disclosure. [Figure 4] FIG. 1 is a diagram illustrating an overview of processing according to the present disclosure. [Diagram 5] FIG. 1 is a diagram illustrating data applied to the processing of the present disclosure. [Figure 6] FIG. 1 is a diagram illustrating data applied to the processing of the present disclosure. [Figure 7] FIG. 1 is a diagram illustrating data applied to the processing of the present disclosure. [Figure 8] FIG. 1 is a diagram illustrating data applied to the processing of the present disclosure. [Figure 9] 11 is a diagram illustrating a process executed by a user terminal or the like when rehabilitation is performed in a hospital. FIG. [Figure 10] 11 is a diagram illustrating an example of stored data in an exercise type-based standard exercise intensity database. FIG. [Figure 11] 11 is a diagram illustrating an example of stored data in a user-specific exercise intensity database corresponding to exercise type. FIG. [Figure 12] 11 is a diagram illustrating the processing executed by a user terminal or the like when performing rehabilitation after being discharged from a hospital. FIG. [Figure 13] 10 is a diagram illustrating an example of stored data in an exercise implementation status record database. FIG. [Figure 14] FIG. 11 is a diagram illustrating an example of stored data in an exercise prescription information database. [Figure 15] 11 is a diagram illustrating an example of display data displayed on a user terminal when rehabilitation is performed after discharge from a hospital. FIG. [Figure 16] FIG. 13 is a flowchart illustrating a sequence of processing executed by a user terminal when rehabilitation is performed in a hospital. [Figure 17]FIG. 13 is a diagram illustrating an example of data processing during rehabilitation using an exercise bike (registered trademark). [Figure 18] FIG. 11 is a flowchart illustrating a sequence of data processing during rehabilitation using an exercise bike (registered trademark). [Figure 19] 13 is a diagram showing a flowchart illustrating a sequence of processing executed by a user terminal when performing rehabilitation after being discharged from a hospital. FIG. [Figure 20] FIG. 11 is a diagram illustrating a process executed by a user terminal and a hospital terminal in the second embodiment. [Figure 21] FIG. 11 is a flowchart illustrating a sequence of a process executed by a user terminal in the second embodiment. [Figure 22] FIG. 11 is a flowchart illustrating a sequence of a process executed by a hospital terminal in the second embodiment. [Diagram 23] FIG. 13 is a diagram illustrating a process executed by a user terminal and a hospital terminal in the third embodiment. [Figure 24] FIG. 13 is a diagram illustrating an example of stored data in an exercise prescription information database used in the third embodiment. [Diagram 25] FIG. 13 is a diagram illustrating an example of display data displayed on a user terminal in the third embodiment. [Figure 26] FIG. 11 is a flowchart illustrating a sequence of a process executed by a user terminal in a third embodiment. [Figure 27] FIG. 13 is a diagram illustrating an example of display data displayed on a user terminal in the fourth embodiment. [Figure 28] FIG. 13 is a diagram illustrating a process executed by a user terminal and a geographic information providing server in the fourth embodiment. [Figure 29] FIG. 13 is a diagram illustrating an example of stored data in a geographic information database used in the fourth embodiment. [Diagram 30] FIG. 13 is a diagram illustrating the processing executed by a user terminal and a hospital terminal in the fifth embodiment. [Diagram 31]FIG. 13 is a diagram illustrating an example of an exercise implementation status record database used in the fifth embodiment. [Diagram 32] FIG. 13 is a diagram illustrating an example of an exercise prescription information database used in the fifth embodiment. [Diagram 33] FIG. 13 is a diagram for explaining an example of exercise prescription information used in the fifth embodiment. [Diagram 34] FIG. 13 is a diagram for explaining an example of exercise prescription information used in the fifth embodiment. [Diagram 35] FIG. 13 is a diagram for explaining an example of exercise prescription information used in the fifth embodiment. [Diagram 36] FIG. 13 is a diagram for explaining an example of exercise prescription information used in the fifth embodiment. [Figure 37] FIG. 13 is a diagram for explaining an example of exercise prescription information used in the fifth embodiment. [Figure 38] FIG. 13 is a diagram illustrating an example of display data displayed on a user terminal in the fifth embodiment. [Figure 39] FIG. 2 is a diagram illustrating an example of a hardware configuration of an information processing device according to the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0024] Hereinafter, the information processing device, the information processing system, the information processing method, and the program of the present disclosure will be described in detail with reference to the drawings. The description will be made according to the following items. 1. Overview of rehabilitation 2. Overview of the Disclosure Process 3. Description of data used for processing this disclosure 4. (Example 1) User terminal configuration and details of the processing to be performed 4-1. (Phase 1) Details of the data acquisition phase for rehabilitation analysis in the hospital 4-2. (Phase 2) Processing the rehabilitation implementation phase outside the hospital 5. Sequence of processing executed by user terminal 5-1. (First Phase) Sequence of processing to be performed by the user device during the data acquisition phase for rehabilitation analysis in the hospital 5-2. (2nd Phase) Sequence of processing executed by the user device during the rehabilitation execution phase outside the hospital 6. (Example 2) Example of communication between user terminal and hospital terminal 7. Other Examples 7-1. (Example 3) Example of encouraging measurement of electrocardiogram (ECG) based on analysis results of exercise load 7-2. (Example 4) Example of presenting walking and running route information using a map 7-3. (Example 5) Example of updating exercise prescription 8. Examples of hardware configurations of information processing devices 9. Summary of the Disclosure

[0025] [1. Overview of rehabilitation] First, an overview of rehabilitation in general will be provided.

[0026] FIG. 1 is a diagram illustrating a typical rehabilitation procedure. For example, a user (patient) who develops a heart disease such as a myocardial infarction is admitted to a hospital and then undergoes surgery. If the surgery is successful, rehabilitation (hereinafter referred to as "rehab") is then started.

[0027] First, in step S01, a user (patient) performs rehabilitation in a hospital room or ward. This rehabilitation mainly involves walking practice in a hospital room or a corridor near the hospital room. Next, in step S02, the user (patient) undergoes rehabilitation at a rehabilitation center in the hospital, using various rehabilitation tools installed in the rehabilitation center. Up to this point, rehabilitation is carried out in a hospital under the supervision of specialists.

[0028] After that, the user (patient) is discharged from the hospital. After being discharged from the hospital, the user (patient) performs both the outpatient rehabilitation in step S03a and the home rehabilitation in step S03b. Outpatient rehabilitation involves visiting a hospital once or twice a week, for example, and using various rehabilitation equipment provided at the rehabilitation center. Home rehabilitation is rehabilitation that involves exercising at home or walking or running outside on days other than outpatient rehabilitation, for example.

[0029] Thereafter, depending on the recovery status of the user (patient), the outpatient rehabilitation in step S03a is terminated, and maintenance-phase home rehabilitation is started in step S04. Maintenance home rehabilitation, like home rehabilitation, involves exercise at home or outside, such as walking or running.

[0030] Among these rehabilitation steps, the home rehabilitation in step S03b and the maintenance home rehabilitation in step S04 will be carried out according to the exercise prescription specified by the hospital, but the type of exercise, duration of exercise, etc. will ultimately be decided by the user (patient) himself / herself.

[0031] In this way, if rehabilitation is performed by determining the type of exercise, duration, etc. based on the user's will, there is a high possibility that the user will exercise too much or too little, and the rehabilitation will not be performed appropriately.

[0032] [2. Overview of the Disclosure Process] Next, an overview of the processing of the present disclosure will be described.

[0033] The present disclosure solves the above problem, and makes it possible to execute the home rehabilitation of step S03b shown in FIG. 1 and the maintenance home rehabilitation of step S04, i.e., rehabilitation performed under user management without the supervision of a specialist, as rehabilitation with an optimal amount of exercise.

[0034] An overview of the processing of the present disclosure will be described with reference to FIG. 2 and subsequent figures. The process of this disclosure consists of two phases: (Phase 1) Data acquisition phase for in-hospital rehabilitation analysis (Phase 2) Out-of-hospital rehabilitation implementation phase

[0035] FIG. 2 is a diagram for explaining the "(first phase) phase of acquiring data for rehabilitation analysis in the hospital." This first phase is performed in the rehabilitation in a hospital room or ward in step S01 described with reference to FIG. 1, or in the rehabilitation using a rehabilitation center in a hospital in step S02.

[0036] 2 shows a user (patient) 11 who runs and uses a stationary bike (e.g., an exercise bike (registered trademark)). Note that these are the same user 11. It shows that the user is performing different exercises at different times.

[0037] While undergoing rehabilitation, the user (patient) 11 utilizes an exhaled gas analyzer 20 to perform an exhaled gas analysis. Furthermore, the user 11 wears the user terminal 30 and inputs sensor detection information of the sensor 12, such as an acceleration sensor, a gyro, a geomagnetic sensor, or an air pressure sensor, worn on the body of the user 11 to the user terminal 30. The user terminal 30 is, for example, a wearable device, a wristwatch band, a smartphone, or an HMD (Head Mount Display).

[0038] The user terminal 30 analyzes the expiratory gas analysis results obtained using the expiratory gas analyzer 20 and the sensor detection information obtained via the sensor 12, generates exercise intensity information corresponding to various user-specific exercise types for each individual user (patient) 11, and stores the generated data in an "exercise type-specific user-specific exercise intensity database 40" within the user terminal 30.

[0039] This user-specific exercise intensity database 40 corresponding to exercise type records user-specific exercise intensity corresponding to various types of exercise performed by the user (patient) 11, such as walking (walking speed = 4.0 km / h on flat ground), running (speed = 7.0 km / h on flat ground), and aero bike (registered trademark) (load = 120 W).

[0040] Specifically, the exercise intensity is, for example, METs (Metabolic equivalents). METs, an exercise intensity index value, is defined as METs = 1 at rest and indicates how many times the calories (= activity level) consumed by various types of exercise, such as walking (walking speed = 4.0 km / h on flat ground), running (speed = 7.0 km / h running on flat ground), and using an exercise bike (registered trademark) (load = 120 W), etc., are consumed compared to when at rest.

[0041] For example, METs for various types of exercise have been calculated and published, such as METs = 3.0 for walking slowly, METs = 5.2 for climbing stairs, etc. Hospitals often use these METs to create rehabilitation programs.

[0042] However, the published METs values ​​are only standard values, and exercise intensity is perceived differently by each individual. Therefore, in the system of the present disclosure, the exercise intensity corresponding to the type of exercise for each individual user (patient) 11 undergoing rehabilitation is calculated within the user terminal 30, and this calculated value is recorded in the "user-specific exercise intensity database 40 corresponding to exercise type."

[0043] That is, in the "(first phase) in-hospital rehabilitation analysis data acquisition phase" shown in FIG. 2, an "exercise type-specific user-specific exercise intensity database 40" is generated and recorded in the storage unit in the user terminal 30.

[0044] When the "(first phase) data acquisition phase for rehabilitation analysis in the hospital" shown in Figure 2 is completed, (Phase 2) Out-of-hospital rehabilitation implementation phase This will be carried out.

[0045] FIG. 3 is a diagram for explaining the "(second phase) rehabilitation execution phase outside the hospital." This second phase is executed in the home rehabilitation of step S03b and the maintenance-phase home rehabilitation of step S04 described with reference to FIG.

[0046] At the start of this (second phase), the user terminal 30 has already recorded therein the user-specific exercise intensity database 40 corresponding to the exercise type. The user-specific exercise intensity database 40 corresponding to the type of exercise stores exercise intensity data corresponding to the type of exercise for each individual user (patient) 11 undergoing rehabilitation.

[0047] 3 shows a user (patient) 11 who is running and who is using an exercise bike (registered trademark). Note that these are the same user 11. It shows that the user is performing different exercises at different times.

[0048] A user 11, who is a person performing rehabilitation, wears a user terminal 30 and inputs sensor detection information from a sensor 12 attached to the body of the user 11, such as an acceleration sensor, gyro, geomagnetic sensor, or air pressure sensor, to the user terminal 30.

[0049] The data processing unit of the user terminal 30 analyzes the sensor detection information acquired via the sensor 12 to estimate the type of exercise being performed by the user (patient) 11. Furthermore, by referring to the exercise type-corresponding user-specific exercise intensity database 40, the data processing unit acquires the user-specific exercise intensity (METs) corresponding to the estimated exercise type. Furthermore, the data processing unit of the user terminal 30 uses the user-specific exercise intensity (METs) value corresponding to the estimated type of exercise to analyze whether the exercise being performed by the user 11 is in accordance with the exercise prescription (rehabilitation program) created by the hospital, and displays the analysis results on the display unit of the user terminal 30.

[0050] Specifically, messages and analysis data such as those shown in Figure 3 are displayed. For example, the following information is displayed: (a) You haven't yet reached your exercise goal time this week. You still have time (b) Insufficient exercise content Low intensity = e.g. walking slowly (30 minutes) Moderate intensity = e.g. brisk walk (10 minutes) High Intensity = e.g. climbing stairs (5 minutes) Low intensity to high intensity is classification information for "exercise intensity." The time, such as 30 minutes, indicates the insufficient time.

[0051] The above-mentioned display information is displayed based on the analysis results on a weekly or daily basis, for example. The user 11 can see this display information and confirm the appropriate amount of exercise to be performed as rehabilitation, and can reliably perform rehabilitation with an appropriate amount of exercise.

[0052] FIG. 4 is a diagram for explaining another different processing example of the "(second phase) rehabilitation execution phase outside the hospital." Like FIG. 3, the process shown in FIG. 4 is executed in the second phase, that is, in the home rehabilitation of step S03b and the maintenance-phase home rehabilitation of step S04 described with reference to FIG.

[0053] The example shown in FIG. 4 is a processing example in which the user terminal 30 and the hospital terminal 70 communicate with each other. A user 11, who is a person performing rehabilitation, wears a user terminal 30 and inputs sensor detection information from a sensor 12 attached to the body of the user 11, such as an acceleration sensor, gyro, geomagnetic sensor, or air pressure sensor, to the user terminal 30.

[0054] The data processing unit of the user terminal 30 transmits the sensor detection information acquired via the sensor 12 directly to the hospital terminal 70, or transmits the analysis results. The hospital terminal 70 executes the same data analysis process as the process executed by the user terminal 30 described above with reference to FIG. Furthermore, based on the analysis result, advice information and the like for the user 11 is generated and transmitted to the user terminal 30.

[0055] The user terminal 30 displays the advice information received from the hospital terminal 70. The user 11 can check, based on this displayed information, whether or not appropriate rehabilitation is being performed.

[0056] [3. Description of data used in processing this disclosure] Next, data used in the processing of the present disclosure will be described.

[0057] Hereinafter, each of the data in the following categories (a) to (d) will be described in order with reference to FIGS. (a) Oxygen intake-related data (b) Exercise intensity-related data (c) Activity-related data (d) Other data

[0058] (a) Oxygen intake-related data First, (a) data relating to oxygen intake will be described with reference to Fig. 5. The data relating to oxygen intake includes the following data. (a1) Oxygen intake (VO2) (a2) Maximum oxygen intake (peak VO2) (a3) Maximum oxygen uptake rate (%peakVO2)

[0059] (a1) Oxygen uptake (VO2) is the amount of oxygen taken in by the body, measured in ml / min / kg. It is measured per minute and per kg of body weight. (a2) Peak oxygen uptake (peak VO2) is the maximum amount of oxygen the body can take in (oxygen uptake (VO2)). Specifically, it is the maximum amount of oxygen taken in during intense exercise, for example.

[0060] (a3) Peak oxygen uptake rate (%peakVO2) is the ratio of actual oxygen uptake (VO2) to maximum oxygen uptake (peakVO2). In addition, in the processing of the present disclosure, an estimated value may be calculated and used.

[0061] (b) Exercise intensity-related data Next, (b) exercise intensity related data will be described with reference to Fig. 6. (b) exercise intensity related data includes the following data. (b1) Standard exercise intensity (METs) (b2) Standard exercise intensity for each type of exercise (METs, K) (b3) Individual exercise intensity (METs, U) (b4) Exercise type and individual exercise intensity (METs, U, K) As described above, the exercise intensity is specifically expressed in, for example, METs (Metabolic equivalents).

[0062] (b1) Standard exercise intensity (METs) is defined as METs = 1 at rest, and indicates how many times the calories (= activity level) consumed by each exercise, such as walking (walking speed = 4.0 km / h on flat ground), running (speed = 7.0 km / h on flat ground), and using an exercise bike (registered trademark) (load = 120 W), etc. This standard exercise intensity (METs) is published data. The calories burned [kcal] (=activity level) can be calculated using the following formula. Calories burned [kcal] = (METs) x (body weight [kg]) x (exercise time [hr]) x 1.05

[0063] (b2) Standard exercise intensity (METs, K) corresponding to exercise type is a standard value of exercise intensity corresponding to each of various exercise types (K), such as walking (walking speed = 4.0 km / h on flat ground), running (speed = 7.0 km / h on flat ground), and aero bike (registered trademark) (load = 120 W). This is also publicly available data. It should be noted that (K) indicates a value corresponding to the type of exercise.

[0064] Furthermore, in the process of the present disclosure, the type of exercise performed by the user performing rehabilitation exercise is estimated based on detection information from a sensor worn by the user. The estimated type of motion is denoted as (Kest), and the corresponding motion type is The standard exercise intensity corresponding to the estimated type of exercise is expressed as (METs, Kest). In the following description, the exercise type (K) will be described as including not only confirmed exercise types but also estimated exercise types (Kest).

[0065] (b3) Individual exercise intensity (METs, U) is a value indicating the exercise intensity of an individual user (U) calculated by dividing the "calculated activity amount using the results of the exhaled breath analysis (EEref)" obtained from the analysis results of the exhaled breath gas analyzer worn by the user who is exercising by the user's weight [kg] and exercise time [hr]. The unit is [kcal / kg / hr]. METs,U=(EEref) / ((body weight [kg])×(exercise time [hr])) It is. It should be noted that (U) indicates that the value is unique to a particular user.

[0066] (b4) Exercise type and individual exercise intensity (METs, U, K) is the individual exercise intensity (METs, U) corresponding to the exercise type (K).

[0067] As described above, in the process of the present disclosure, the type of exercise performed by a user performing rehabilitation exercise is estimated based on detection information from a sensor worn by the user. The estimated type of motion is denoted as (Kest), and the corresponding motion type is The estimated exercise type and individual corresponding exercise intensity are expressed as (METs, U, Kest).

[0068] Next, (c) activity amount related data will be described with reference to Fig. 7. (c) activity amount related data includes the following data. (c1) Activity level (calories burned) (EE) (c2) Exercise intensity (METs)-based individual activity (EEmets,U) (c3) Exercise intensity (METs)-based exercise type and individual activity amount (EEmets,U,K) (c4) Individual activity based on breath analysis results (EEref,U) (c5) Exercise type and individual activity amount based on breath analysis results (EEref,U,K)

[0069] (c1) Activity (calories burned) (EE) is the amount of calories burned through activity (exercise), but it also includes calories burned through basal metabolism. The unit is [kcal]. Note that EE stands for energy expenditure.

[0070] (c2) Exercise intensity (METs)-based individual activity amount (EEmets,U) is an individual activity amount (calories burned) calculated based on the standard exercise intensity (METs), the user's (U) weight, and exercise time. EEmets,U[kcal]=(METs)×(body weight[kg])×(exercise time[hr])×1.05 It is calculated according to the above formula.

[0071] (c3) Exercise intensity (METs)-based exercise type-individual activity amount (EEmets,U,K) is the exercise intensity (METs)-based individual activity amount corresponding to the exercise type (K).

[0072] (c4) Individual activity level based on breath analysis results (EEref,U) is an estimated activity level calculated using the analysis results of a breath gas analyzer. It is one of the standards (gold standard) for measuring activity, and has a higher estimation accuracy than individual activity level (EEmets,U) based on exercise intensity (METs). EEref,U[kcal]=(3.94VO2+1.11VCO2)×(exercise time[min])(Weir formula) It is calculated according to the above formula. Note that VO2 is the amount of oxygen and VCO2 is the amount of carbon dioxide.

[0073] (c5) Exercise type-specific individual activity amount based on exhaled breath analysis results (EEref,U,K) is the individual activity amount using the exhaled breath analysis results calculated based on the exhaled breath analysis results (VO2 and VCO2) at the point when the oxygen intake (VO2) measurement value of the exhaled breath gas analyzer reaches a steady state during exercise of exercise type (K).

[0074] Next, (d) other data will be described with reference to Fig. 8. (d) other data includes the following data. (d1) Estimated movement type (Kest) (d2) Individual exercise intensity correction coefficient (Rk)

[0075] (d1) Estimated type of exercise (Kest) is the type of exercise the user is performing that is estimated based on detection information from a sensor attached to the user's body.

[0076] (d2) The individual-specific exercise intensity correction coefficient (Rk) is the ratio (proportion) of the "individual-specific activity amount corresponding to the type of exercise based on the breath analysis results (EEref,U,K)" to the "activity amount corresponding to the type of exercise based on the exercise intensity (METs) (EEmets,U,K)." Rk = (EEref,U,K) / (EEmets,U,K) It is calculated according to the above formula.

[0077] [4. (Example 1) Configuration of user terminal and details of processing to be executed] Next, the configuration of the user terminal 30 and details of the processes executed will be described as a first embodiment of the present disclosure.

[0078] As described with reference to FIGS. 2 to 4, the user terminal 30 is worn on the body of the user 11 who is undergoing rehabilitation. As explained above, the process of the present disclosure consists of two phases: (Phase 1) Data acquisition phase for in-hospital rehabilitation analysis (Phase 2) Out-of-hospital rehabilitation implementation phase The processes executed in these two phases will be described in detail below.

[0079] [4-1. (Phase 1) Details of the data acquisition phase for in-hospital rehabilitation analysis] First, the process executed in the "(first phase) phase of acquiring data for rehabilitation analysis in hospital" will be described. As described with reference to FIG. 2, the first phase is performed in rehabilitation in a hospital room or ward in step S01, or in rehabilitation using a rehabilitation center in a hospital in step S02. While undergoing rehabilitation, the user (patient) 11 utilizes an exhaled gas analyzer 20 to perform an exhaled gas analysis. Furthermore, the user 11 wears the user terminal 30 and inputs to the user terminal 30 sensor detection information from the sensor 12 worn on the body of the user 11, such as an acceleration sensor, gyro, geomagnetic sensor, or air pressure sensor.

[0080] The user terminal 30 analyzes the expiratory gas analysis results obtained using the expiratory gas analysis device 20 and the sensor detection information obtained via the sensor 12, generates exercise intensity information corresponding to various types of exercise specific to each individual user (patient) 11, and stores the generated data in the user terminal 30. FIG. 2 shows the "user-specific exercise intensity database 40 corresponding to exercise type."

[0081] This user-specific exercise intensity database 40 corresponding to exercise type records user-specific exercise intensity corresponding to various types of exercise performed by the user (patient) 11, such as walking (walking speed = 4.0 km / h on flat ground), running (speed = 7.0 km / h on flat ground), and aero bike (registered trademark) (load = 120 W).

[0082] FIG. 9 is a diagram illustrating the configuration and processing of the user terminal 30 and the exhaled gas analyzer 20 that execute the processing of the "(first phase) in-hospital rehabilitation analysis data acquisition phase."

[0083] The exhaled gas analyzer 20 is connected to a mask attached to the mouth of the user 11 performing rehabilitation exercises, and analyzes the exhaled breath of the user 11 . 9, the exhaled gas analyzer 20 includes an activity amount acquisition unit 21. The activity amount acquisition unit 21 analyzes the exhaled breath of the user 11 to generate an “exhaled breath analysis result-based individual-corresponding activity amount (EEref,U) d21” and outputs the same to the user terminal 30.

[0084] As described above, the individual activity amount based on the breath analysis results (EEref,U) is an estimated activity amount calculated using the analysis results of the breath gas analyzer. It is one of the standards (gold standard) for measuring activity, and has a higher estimation accuracy than individual activity level (EEmets,U) based on exercise intensity (METs). EEref,U[kcal]=(3.94VO2+1.11VCO2)×(exercise time[min])(Weir formula) It is calculated according to the above formula.

[0085] The user terminal 30 is a terminal that is worn by a user 11, who is a rehabilitation participant, on the body while the user 11 is performing rehabilitation exercise. The sensor detection information input unit 31 of the user terminal 30 acquires sensor detection information d31 from sensors attached to the body of the user 11, such as an acceleration sensor, gyro, geomagnetic sensor, air pressure sensor, etc., and outputs it to the motion information estimation unit 32. In addition, the d in the reference symbol (d31) stands for data.

[0086] The exercise information estimation unit 32 estimates the type of exercise of the user 11 based on the input sensor detection information d31. For example, the type of exercise that the user 11 is performing may be walking (walking speed = 4.0 km / h on flat ground), running (speed = 7.0 km / h on flat ground), aero bike (registered trademark) (load = 120 W), etc.

[0087] The exercise information estimation unit 32 outputs the estimated exercise type (Kest), which is the estimation result, to the steady state activity amount analysis unit 33 and the exercise type-corresponding standard exercise intensity acquisition unit . Furthermore, the data is also output to a database of exercise type-specific exercise intensity specific to the user and registered in the database.

[0088] The steady state activity amount analysis unit 33 receives the following data. (a) breath analysis result-based individual activity amount (EEref,U) d21 generated by the activity amount acquisition unit 21; (b) an estimated exercise type (Kest) d32 indicating the type of exercise being performed by the user estimated by the exercise information estimation unit 32;

[0089] The steady-state activity amount analysis unit 33 generates the breath analysis result-based exercise type / individual corresponding activity amount (EEref, U, Kest) d33 based on these data. In addition, the type of movement (K) is shown as (Kest) since it is an estimated result.

[0090] As explained above with reference to Figure 7, "Exercise type-specific individual activity amount based on exhaled breath analysis results (EEref,U,K)" is an individual activity amount using exhaled breath analysis results calculated based on the exhaled breath analysis results (VO2 and VCO2) at the point when the oxygen intake (VO2) measurement value of the exhaled breath gas analyzer reaches a steady state during exercise of exercise type (K).

[0091] Exercise type and individual activity amount based on breath analysis results (EEref,U,K) are EEref,U,K[kcal]=(3.94VO2+1.11VCO2)×(exercise time[min])(Weir formula) It is calculated according to the above formula. Note that VO2 is the amount of oxygen and VCO2 is the amount of carbon dioxide. This breath analysis result-based exercise type-specific individual corresponding activity amount (EEref,U,K) has a higher estimation accuracy than the exercise intensity (METs)-based exercise type-specific activity amount (EEmets,U,K).

[0092] The steady state activity amount analysis section 33 outputs the calculated breath analysis result-based exercise type / individual-based activity amount (EEref, U, Kest) d33 to the individual-based exercise intensity correction coefficient calculation section 37.

[0093] Next, a process executed by the exercise type-corresponding standard exercise intensity acquisition unit 36, which is another output destination of the estimated exercise type (Kest) d32 generated by the exercise information estimation unit 32, will be described.

[0094] The exercise type-based standard exercise intensity acquisition unit 36 ​​searches the exercise type-based standard exercise intensity (METs, K) database 34 based on the estimated exercise type (Kest) d32 input from the exercise information estimation unit 32, and acquires the standard exercise intensity (METs, K) registered in association with the estimated exercise type (Kest). The exercise type-based standard exercise intensity (METs, K) d34 shown in FIG. 9 is acquired.

[0095] In FIG. 9, the exercise type-specific standard exercise intensity (METs, K) database 34 is shown as part of the configuration of the user terminal 30. However, the exercise type-specific standard exercise intensity (METs, K) database 34 may be a database of an external server. In this case, the user terminal 30 accesses the external server via a communication unit to obtain the exercise type-specific standard exercise intensity (METs, K) d34.

[0096] The standard exercise intensity (METs, K) database 34 for exercise type stores standard exercise intensity (METs) values ​​associated with various exercise types (walking speed = 4.0 km / h on flat ground), running (speed = 7.0 km / h on flat ground running), stationary bikes (e.g., Aero Bike (registered trademark)) (load = 120 W), etc.). An example of registered data in the exercise type-specific standard exercise intensity (METs, K) database 34 is shown in FIG.

[0097] As shown in FIG. 10, the following data is registered in the exercise type-specific standard exercise intensity (METs, K) database 34 in association with each other. (a) Exercise type (K) (b) Standard exercise intensity for each type of exercise (METs, K)

[0098] In addition, (a) type of exercise (K) includes (major categories) such as walking, running, stationary bike (e.g., Aero Bike (registered trademark)), etc., and (individual activities) that describe detailed information such as the walking or running speed, the condition of the surface on which the walking or running is performed, and the load on the stationary bike (e.g., Aero Bike (registered trademark)).

[0099] As explained above with reference to FIG. 6, the standard exercise intensity (METs, K) corresponding to the exercise type is an exercise intensity index value that indicates how many times the calories (=activity amount) consumed at rest is consumed for exercise types (K) such as walking (walking speed = 4.0 km / h on flat ground), running (speed = 7.0 km / h running on flat ground), and aerobics (registered trademark) (load = 120 W), with METs = 1 at rest. This standard exercise intensity (METs, K) for each type of exercise is publicly available data.

[0100] The exercise type-corresponding standard exercise intensity acquisition unit 36 ​​shown in FIG. 9 searches the exercise type-corresponding standard exercise intensity (METs, K) database 34 having the registered data shown in FIG. 10 based on the estimated exercise type (Kest) input from the exercise information estimation unit 32, and acquires the standard exercise intensity (METs, K) registered in association with the same or most similar exercise type (K) as the estimated exercise type (Kest).

[0101] The exercise type-based standard exercise intensity acquisition unit 36 ​​outputs the standard exercise intensity (METs, K) acquired from the exercise type-based standard exercise intensity (METs, K) database 34 to the exercise intensity-based exercise type / individual corresponding activity amount calculation unit 37 as the “estimated exercise type-based standard exercise intensity (METs, Kest) d36” shown in FIG. 9. It should be noted that the "standard exercise intensity (METs, Kest) d36 corresponding to estimated exercise type" shown in FIG. 9 is expressed using (Kest) since it is data based on the estimated exercise type (Kest).

[0102] The exercise-intensity-based exercise-type / individual-corresponding activity amount calculation unit 37 receives the following two pieces of data. (a) the estimated exercise type-corresponding standard exercise intensity (METs, Kest) d36 output by the exercise type-corresponding standard exercise intensity acquisition unit 36; (b) personal weight information d35 of the user obtained from the personal information database 35;

[0103] An example of data recorded in the personal information database 35 is shown in the lower part of Fig. 10. As shown in Fig. 10, the personal information database 35 records weight information of individual users.

[0104] The exercise-intensity-based exercise-type / individual-adapted activity amount calculation unit 37 inputs the above data (a) and (b) and calculates the exercise-intensity-based exercise-type / individual-adapted activity amount (EEmets, U, Kest) d37.

[0105] As described above with reference to FIG. 7(c3), the exercise intensity-based exercise type-individual corresponding activity amount (EEmets,U,K) is the exercise intensity (METs)-based individual corresponding activity amount corresponding to the exercise type (K). The exercise intensity (METs)-based individual activity amount (EEmets,U) is an individual activity amount (calories burned) calculated based on the standard exercise intensity (METs), the user's (U) weight, and exercise time, as described with reference to Figure 7 (c2). EEmets,U[kcal]=(METs)×(body weight[kg])×(exercise time[hr])×1.05 It is calculated according to the above formula.

[0106] The exercise-intensity-based exercise-type / individual-corresponding activity amount calculation unit 37 calculates the exercise intensity-based exercise type / individual-corresponding activity amount according to the above formula, i.e., EEmets,U[kcal]=(METs)×(body weight[kg])×(exercise time[hr])×1.05 The amount of activity (calories burned) for each individual is calculated using the above formula.

[0107] The amount of activity (EE) calculated according to this formula is the value when the user is performing a specific type of exercise (Kest), It is calculated as exercise intensity-based exercise type and individual corresponding activity amount (EEmets, U, Kest) d37.

[0108] As shown in FIG. 9, the exercise-intensity-based exercise-type / individual-adjusted activity amount calculation unit 37 outputs the calculated exercise-intensity-based exercise-type / individual-adjusted activity amount (EEmets, U, Kest) d37 to the individual-adjusted exercise intensity correction coefficient calculation unit 38.

[0109] The individual-adapted exercise intensity correction coefficient calculation unit 38 receives the following data: (a) Exercise type and individual activity amount (EEref, U, Kest) d33 based on the breath analysis result calculated by the steady-state activity amount analysis unit 33; (b) the exercise intensity-based exercise type / individual-corresponding activity amount (EEmets,U,Kest) d37 calculated by the exercise intensity-based exercise type / individual-corresponding activity amount calculation unit 37;

[0110] The individual-adapted exercise intensity correction coefficient calculation unit 38 calculates an individual-adapted exercise intensity correction coefficient (Rk) d38 based on the above two types of input data.

[0111] As explained above with reference to Figure 8, the individual-specific exercise intensity correction coefficient (Rk) is the ratio (proportion) of the "exhaled breath analysis result-based exercise type-based individual-specific activity amount (EEref,U,K)" to the "exercise intensity (METs)-based exercise type-based activity amount (EEmets,U,K)." Rk = (EEref,U,K) / (EEmets,U,K) It is calculated according to the above formula.

[0112] The individual-corresponding exercise intensity correction coefficient calculation unit 38 calculates the individual-corresponding exercise intensity correction coefficient based on the above-mentioned input data, i.e., (a) Exercise type and individual corresponding activity amount (EEref, U, Kest) d33 based on the breath analysis result calculated by the steady-state activity amount analysis unit 33; (b) the exercise intensity-based exercise type / individual-corresponding activity amount (EEmets,U,Kest) d37 calculated by the exercise intensity-based exercise type / individual-corresponding activity amount calculation unit 37; Based on these data, Rk=(EEref,U,Kest) / (EEmets,Kest) Calculate the individual exercise intensity correction coefficient (Rk) according to the above formula.

[0113] The individual-adapted exercise intensity correction coefficient calculation unit 38 outputs the calculated individual-adapted exercise intensity correction coefficient (Rk) d 38 to the exercise type / individual-adapted exercise intensity calculation unit 39 .

[0114] The exercise type / individual exercise intensity calculation unit 39 receives the following data: (a) the individual-adjusted exercise intensity correction coefficient (Rk) d38 calculated by the individual-adjusted exercise intensity correction coefficient calculation unit 38; (b) the exercise-intensity-based exercise-type / individual-corresponding activity amount d37 calculated by the exercise-intensity-based exercise-type / individual-corresponding activity amount calculation unit 37; (c) personal weight information d35 of the user obtained from the personal information database 35; The exercise type / individual exercise intensity calculation unit 39 uses these input data to calculate the exercise type / individual exercise intensity (METs, U, Kest) d39.

[0115] As described above with reference to FIG. 6(b4), the exercise type-individual exercise intensity (METs, U, K) is the individual exercise intensity (METs, U) corresponding to the exercise type (K).

[0116] As described with reference to Fig. 6(b3), the individual exercise intensity (METs, U) is a value indicating the exercise intensity of an individual user (U) calculated by dividing the "calculated activity amount using the breath analysis result (EEref)" obtained from the analysis result of the breath gas analyzer worn by the user who is exercising by the user's weight [kg] and exercise time [hr]. The unit is [kcal / kg / hr]. METs,U=(EEref) / ((body weight [kg])×(exercise time [hr])) It is.

[0117] Based on the above formula, the exercise type and individual corresponding exercise intensity (METs, U, K) are: METs,U,K=(EEref,U,K) / ((body weight [kg])×(exercise time [hr])) (Formula 1) It can be shown as:

[0118] In addition, the individual-adjusted exercise intensity correction coefficient (Rk) d38 calculated by the individual-adjusted exercise intensity correction coefficient calculation unit 38 is, as described above, Rk=(EEref,U,K) / (EEmets,U,K) (Formula 2) It is.

[0119] From the above (Equation 1) and (Equation 2), the following (Equation 3) is derived. METs,U,K=((EEmets,U,K)×(Rk)) / ((body weight [kg])×(exercise time [hr]))...(Formula 3)

[0120] The exercise type and individual exercise intensity calculation unit 39 calculates the exercise time information measured by a timer (not shown) and the following input data, namely: (a) the individual-adjusted exercise intensity correction coefficient (Rk) d38 calculated by the individual-adjusted exercise intensity correction coefficient calculation unit 38; (b) personal weight information d35 of the user obtained from the personal information database 35; The exercise type / individual exercise intensity calculation unit 39 uses these input data to calculate the exercise type / individual exercise intensity (METs, U, Kest) d39. Based on these input data, the exercise type and individual corresponding exercise intensity (METs, U, K) are calculated according to the above (Equation 3).

[0121] As described above with reference to FIG. 6(b4), the exercise type-individual exercise intensity (METs, U, K) is the individual exercise intensity (METs, U) corresponding to the exercise type (K). As explained above with reference to Fig. 6(b3), the individual exercise intensity (METs, U) is a value indicating the exercise intensity of an individual user (U) calculated by dividing the "calculated activity amount using the breath analysis result (EEref)" obtained from the analysis result of the breath gas analyzer worn by the user who is exercising by the user's weight [kg] and exercise time [hr]. The unit is [kcal / kg / hr]. METs,U=(EEref) / ((body weight [kg])×(exercise time [hr])) It is.

[0122] This exercise type / individual corresponding exercise intensity (METs, U, K) is an exercise intensity specific to the user, and is a different value from the published standard exercise intensity (METs) or the standard exercise intensity corresponding to the exercise type (METs, K). In other words, the exercise intensity is unique to the user and is calculated based on the results of an analysis of exhaled gases during actual exercise by the user and the user's body weight.

[0123] As shown in FIG. 9, the exercise type / individual-specific exercise intensity (METs, U, Kest) d39 calculated by the exercise type / individual-specific exercise intensity calculation unit 39 is recorded in an exercise type / user-specific exercise intensity database 40.

[0124] An example of registered data in the exercise type / user specific exercise intensity database 40 is shown in FIG. As shown in FIG. 11, the following data is associated and registered in the exercise type / user specific exercise intensity (METs, U, Kest) database 40. (a) Exercise type (K(Kest)) (b) Exercise type and individual user-specific exercise intensity (METs, U, Kest)

[0125] In addition, (a) type of exercise (K (Kest)) includes (major categories) such as walking, running, stationary bike (e.g., Aero Bike (registered trademark)), etc., and (individual activities) that describe detailed information such as the walking or running speed, the condition of the surface on which the walking or running is performed, and the load on the stationary bike (e.g., Aero Bike (registered trademark)).

[0126] Moreover, since all the data registered in the database is based on the type of exercise estimated by the exercise type estimation unit 32, it is shown as an estimated exercise type (Kest). In the database of FIG. 11, the estimated exercise type (Kest) d32 estimated by the exercise type estimation unit 32 shown in FIG. 9 is registered in "(a) exercise type (K(Kest))".

[0127] The "(b) Exercise type, individual user-specific exercise intensity (METs, U, Kest)" registered in this exercise type user-specific exercise intensity (METs, U, Kest) database 40 is, as described above, a user-specific exercise intensity calculated based on the results of the expiratory gas analysis during the user's actual exercise and the user's body weight.

[0128] Therefore, this exercise intensity reflects the actual physical condition of the user more accurately than the published standard value, the standard exercise intensity for each type of exercise (METs, K). By programming and evaluating the exercises to be performed during rehabilitation based on the exercise intensity registered in this database, it is possible to plan and evaluate optimal rehabilitation and exercise according to the user's physical condition.

[0129] [4-2. (Phase 2) Processing of rehabilitation implementation phase outside the hospital] Next, the process executed in the "(second phase) rehabilitation execution phase outside the hospital" will be described.

[0130] The second phase is executed in the home rehabilitation of step S03b and the maintenance-phase home rehabilitation of step S04, as described with reference to FIG. 3 and FIG. A user (patient) 11 wears a user terminal 30 while undergoing rehabilitation.

[0131] The memory section of the user terminal 30 stores an exercise type user-specific exercise intensity (METs, U, Kest) database 40 generated during the processing of the "(First Phase) Data Acquisition Phase for Rehabilitation Analysis in the Hospital" described with reference to FIG. 9. The exercise type / user specific exercise intensity (METs, U, Kest) database 40 has the registered data configuration shown in Fig. 11. That is, as described with reference to Fig. 11, the database is registered with the following data in association with each other. (a) Exercise type (K(Kest)) (b) Exercise type and individual user-specific exercise intensity (METs, U, Kest)

[0132] (Phase 2) In the rehabilitation execution phase outside the hospital, the data recorded in this database is used to evaluate the rehabilitation exercises being performed by the user 11.

[0133] The configuration and processing of the user terminal 30 that executes the processing of the "(second phase) rehabilitation execution phase outside the hospital" will be described with reference to FIG.

[0134] The user terminal 30 is a terminal that is worn by a user 11, who is a rehabilitation participant, on the body while the user 11 is performing rehabilitation exercise. The sensor detection information input unit 31 of the user terminal 30 acquires sensor detection information d31 from sensors attached to the body of the user 11, such as an acceleration sensor, gyro, geomagnetic sensor, air pressure sensor, etc., and outputs it to the motion information estimation unit 32.

[0135] The exercise information estimation unit 32 estimates the type of exercise of the user 11 based on the input sensor detection information d31. For example, the type of exercise that the user 11 is performing may be walking (walking speed = 4.0 km / h on flat ground), running (speed = 7.0 km / h on flat ground), aero bike (registered trademark) (load = 120 W), etc.

[0136] The exercise information estimation unit 32 outputs the estimated exercise type (Kest), which is the estimation result, to the exercise type / individual-adapted exercise intensity acquisition unit 51.

[0137] The exercise type / individual-based exercise intensity acquisition unit 51 searches the exercise type / user-specific exercise intensity (METs, U, Kest) database 40 based on the estimated exercise type (Kest) d32 input from the exercise information estimation unit 32, and acquires the exercise type and individual-based user-specific exercise intensity (METs, U, Kest) d51 registered in association with the estimated exercise type (Kest).

[0138] The type of exercise and individual user-specific exercise intensity (METs, U, Kest) d51 acquired from the database by the exercise type / individual exercise intensity acquisition unit 51 are output to a maximum value-corresponding oxygen uptake rate calculation unit 52.

[0139] The maximum value-corresponding oxygen uptake rate calculation section 52 obtains from the exercise type user-specific exercise intensity (METs, U, Kest) database 40 the maximum value among the individual user-specific exercise intensity (METs, U, Kest) registered in this database.

[0140] The maximum value of the individual user specific exercise intensity (METs, U, Kest) registered in the exercise type user specific exercise intensity (METs, U, Kest) database 40 is Exercise type: User-specific maximum exercise intensity (METsmax,U,Kest).

[0141] The maximum value corresponding oxygen intake rate calculation unit 52 is (a) Exercise type and individual user-specific exercise intensity (METs, U, Kest) d51 acquired from the exercise type / individual exercise intensity acquisition unit 51; (b) the maximum exercise type user-specific exercise intensity (METsmax,U,Kest) obtained from the exercise type user-specific exercise intensity (METs,U,Kest) database 40; From these data, the maximum corresponding oxygen uptake rate (%peakVO2) d52 is calculated.

[0142] The peak oxygen uptake rate (%peakVO2) is calculated using the following formula (4). Maximum oxygen uptake rate (%peakVO2) = (exercise type, individual user-specific exercise intensity (METs, U, Kest)) / (exercise type user-specific maximum exercise intensity (METsmax, U, Kest)) (Equation 4)

[0143] In other words, the maximum oxygen uptake rate (%peakVO2) can be calculated by the ratio of the exercise type and the individual user-specific exercise intensity (METs,U,Kest) to the exercise type user-specific maximum exercise intensity (METsmax,U,Kest).

[0144] As explained above with reference to Figure 5, the maximum oxygen intake (peakVO2) is the maximum amount of oxygen (oxygen intake (VO2)) taken in by the body, and the oxygen intake rate corresponding to the maximum value (%peakVO2) is the ratio of the actual oxygen intake (VO2) to the maximum oxygen intake (peakVO2).

[0145] The peak-corresponding oxygen intake rate (% peakVO2) d52 calculated by the peak-corresponding oxygen intake rate calculation section 52 is output to the exercise time integration section 53.

[0146] The exercise time accumulation unit 53 inputs the peak-corresponding oxygen intake rate (%peakVO2) d52 calculated by the peak-corresponding oxygen intake rate calculation unit 52, generates exercise implementation status data d53 for the user 11, and records it in the exercise implementation status record database 54.

[0147] The exercise time integrating section 53 calculates, as the exercise implementation status data d53 of the user 11, the exercise time performed by the user 11 in predetermined division units of a predefined maximum corresponding oxygen uptake rate (%peakVO2).

[0148] The exercise time integrating unit 53 generates exercise implementation status data d53 classified into predefined maximum corresponding oxygen uptake rates (%peakVO2) for each predefined data generation period (e.g., one week, one day, etc.), and records the data in the exercise implementation status record database 54. A timer (not shown) is used to measure the exercise time.

[0149] An example of recorded data in the exercise implementation status record database 54 is shown in FIG. As shown in FIG. 13, the exercise implementation status record database 54 records the exercise time performed by the user 11 in predetermined division units of the maximum oxygen uptake rate (%peakVO2). The exercise implementation status record database 54 shown in FIG. 13 is configured to further record the exercise time corresponding to the type of exercise (Kest).

[0150] 13 is an example in which record data is generated and recorded on a weekly basis. That is, the exercise time performed by the user 11 in one week is recorded in a predetermined division unit of the maximum corresponding oxygen uptake rate (%peakVO2), and further, it is a data recording example in which it is recorded by exercise type unit.

[0151] Returning to FIG. 12, the process executed by the user terminal 30 will be described. As described above, the exercise time accumulation unit 53 generates exercise implementation status data d53 classified into predefined maximum corresponding oxygen intake rate (%peakVO2) categories for each predefined data generation period (e.g., one week, one day, etc.) and records the data in the exercise implementation status record database 54.

[0152] The exercise implementation status analysis unit 56 acquires data recorded in the exercise implementation status record database 54, compares the acquired data with an exercise prescription provided in advance by a rehabilitation supervisor such as a doctor, generates an exercise implementation status analysis result d56, and outputs it to the display unit 57.

[0153] The exercise prescription provided in advance by a rehabilitation supervisor such as a doctor is recorded in the storage unit of the user terminal 30 as an exercise prescription information database 55 . An example of data in the exercise prescription information database 55 stored in the storage unit of the user terminal 30 will be described with reference to FIG.

[0154] As shown in FIG. 14, the exercise prescription information database 55 records the exercise time that the user 11 should perform in predetermined division units of the peak corresponding oxygen uptake rate (%peakVO2), similar to the exercise implementation status record database 54 described above with reference to FIG. 13. The exercise prescription information database 55 shown in FIG. 14 is an example in which exercise goal times are recorded on a weekly basis, similar to the exercise implementation status record database 54 shown in FIG. 13 described above.

[0155] The exercise implementation status analysis unit 56 acquires the following data and performs a comparison process. (a) Actual exercise time performed by the user 11 recorded in the exercise implementation record database 54 (unit of maximum corresponding oxygen uptake rate (%peakVO2)) (b) Target exercise time to be performed by the user 11 recorded in the exercise prescription information database 55 (unit of maximum corresponding oxygen intake rate (%peakVO2))

[0156] The exercise implementation status analysis unit 56 compares the above two pieces of data and performs analysis processing to determine whether the actual exercise time of the user 11 has reached the target time, and further whether the actual exercise time is excessive compared to the target time, and so on. Based on the analysis result, the exercise implementation status analysis result d56 is generated and output to the display unit 57.

[0157] A specific example of the exercise implementation status analysis result d56 displayed on the display unit 57 will be described with reference to FIG.

[0158] FIG. 15 shows the following two examples of display data as specific examples of the exercise implementation status analysis result d56 displayed on the display unit 57. (1) When the actual exercise time is almost the same as the target time (2) If the actual exercise time is shorter than the target time

[0159] (1) When the actual exercise time is almost the same as the target time, for example, the following message is displayed, as shown in FIG. 15(1). "This week, I achieved all of my exercise goals. Let's keep it up next week."

[0160] On the other hand, (2) when the actual exercise time is shorter than the target time, as shown in (2a), "I haven't yet met my exercise goal time this week. I still have time." Such a message is displayed, and the user: "Check what exercise you are missing" When this message display area is tapped, the specific deficit time and exercise content for each exercise intensity content are displayed, as shown in (2b).

[0161] By looking at the displayed data, the user 11 can check whether the rehabilitation exercises he or she performed are appropriate in accordance with the exercise prescription. For example, it becomes possible to check the insufficient exercises by exercise intensity, and to perform the exercises appropriate for each exercise intensity.

[0162] [5. Sequence of processing executed by user terminal] Next, a process sequence executed by the user terminal 30 will be described.

[0163] As explained above, the process of the present disclosure consists of two phases: (Phase 1) Data acquisition phase for in-hospital rehabilitation analysis (Phase 2) Out-of-hospital rehabilitation implementation phase The processing sequences executed by the user terminal 30 in each of these two phases will be described below in order.

[0164] [5-1. (Phase 1) Sequence of processing to be performed by the user device during the data acquisition phase for rehabilitation analysis in the hospital] First, a sequence of processes executed by the user terminal 30 in the "(first phase) in-hospital rehabilitation analysis data acquisition phase" will be described.

[0165] FIG. 16 is a diagram showing a flowchart illustrating a sequence of processes executed by user terminal 30 in the "(first phase) in-hospital rehabilitation analysis data acquisition phase."

[0166] 16 can be executed according to a program stored in a storage unit of the user terminal 30. For example, it can be executed as a program execution process by a processor such as a CPU having a program execution function. The process of each step in the flow will be explained below in order.

[0167] (Step S121) First, in step S121, the user terminal 30 inputs sensor detection information, The type of exercise the user is performing is estimated, i.e., the estimated exercise type (Kest) is determined.

[0168] This process is executed by the motion information estimation unit 32 shown in FIG. The exercise information estimation unit 32 estimates the type of exercise of the user 11 based on the input sensor detection information d31. For example, the type of exercise that the user 11 is performing may be walking (walking speed = 4.0 km / h on flat ground), running (speed = 7.0 km / h on flat ground), aero bike (registered trademark) (load = 120 W), etc.

[0169] (Step S122) Next, in step S122, the user terminal 30 generates an exercise type and individual-corresponding activity amount (EEref, U, Kest) based on the exhaled breath analysis result, based on the estimated exercise type (Kest) and the exhaled breath gas analysis result.

[0170] This process is executed by the steady-state activity amount analysis section 33 shown in FIG. The steady state activity amount analysis unit 33 analyzes the following data, that is, (a) breath analysis result-based individual activity amount (EEref,U) d21 generated by the activity amount acquisition unit 21; (b) An estimated exercise type (Kest) indicating the type of exercise being performed by the user estimated by the exercise information estimation unit 32 By inputting these data, the breath analysis result-based exercise type and individual corresponding activity amount (EEref, U, Kest) are generated based on these data.

[0171] "Exhaled breath analysis result-based individual activity level for each exercise type (EEref,U,K)" is the individual activity level calculated based on the exhaled breath analysis results (VO2 and VCO2) at the point when the oxygen intake (VO2) measurement value of the exhaled breath gas analyzer reaches a steady state while exercising in the exercise type (K).

[0172] (Step S123) Next, in step S123, the user terminal 30 selects an entry for an exercise type that matches or is most similar to the estimated exercise type (Kest) from the exercise type-specific standard exercise intensity (METs, K) database 34, and determines the exercise type-specific standard exercise intensity (METs, K) of the selected entry as the estimated exercise type-specific standard exercise intensity (METs, Kest).

[0173] This process is executed by the exercise type-based standard exercise intensity obtaining unit 36 ​​shown in FIG. The exercise type-corresponding standard exercise intensity acquisition unit 36 ​​searches the exercise type-corresponding standard exercise intensity (METs, K) database 34 having the registration data shown in FIG. 10 based on the estimated exercise type (Kest) input from the exercise information estimation unit 32, acquires the standard exercise intensity (METs, K) registered in association with the same or most similar exercise type (K) as the estimated exercise type (Kest), and determines this as the estimated exercise type-corresponding standard exercise intensity (METs, Kest).

[0174] (Step S124) Next, in step S124, the user terminal 30 calculates an exercise-intensity-based exercise-type-and-individual-corresponding activity amount (EEmets,U,Kest) based on the estimated exercise-type-corresponding standard exercise intensity (METs,Kest) and the user's body weight.

[0175] This process is executed by the exercise-intensity-based exercise-type / individual-adapted activity amount calculation unit 37 shown in FIG.

[0176] The exercise intensity-based exercise type / individual activity amount calculation unit 37 is (a) the estimated exercise type-corresponding standard exercise intensity (METs, Kest) d36 output by the exercise type-corresponding standard exercise intensity acquisition unit 36; (b) personal weight information d35 of the user obtained from the personal information database 35; Using the above input information (a) and (b), EEmets,U[kcal]=(METs)×(body weight[kg])×(exercise time[hr])×1.05 Using the above formula, the exercise intensity-based exercise type-individual activity amount (EEmets, U, Kest) d37, which is the individual activity amount (calories burned), is calculated.

[0177] (Step S125) Next, in step S125, the user terminal 30 (a) Exercise type and individual activity amount based on breath analysis results (EEref,U,Kest) (b) Exercise intensity-based exercise type and individual activity amount (EEmets,U,Kest), Based on each of these data, Generate an individual exercise intensity correction coefficient (Rk).

[0178] This process is executed by the individual exercise intensity correction coefficient calculation unit 38 shown in FIG. The individual-adapted exercise intensity correction coefficient calculation unit 38 calculates the individual-adapted exercise intensity correction coefficient based on the above two types of input data (a) and (b) using the following formula, i.e., Rk = (EEref,U,K) / (EEmets,U,K) The individual exercise intensity correction coefficient (Rk) is calculated using the above formula.

[0179] (Step S126) Next, in step S126, the user terminal 30 calculates the type of exercise and the individual-suitable exercise intensity (METs, U, Kest) based on the individual-suitable exercise intensity correction coefficient (Rk) and the user's body weight information.

[0180] This process is executed by the exercise type / individual exercise intensity calculation unit 39 shown in FIG. The exercise type / individual exercise intensity calculation unit 39 receives the following data: (a) the individual-adjusted exercise intensity correction coefficient (Rk) d38 calculated by the individual-adjusted exercise intensity correction coefficient calculation unit 38; (b) personal weight information d35 of the user obtained from the personal information database 35; The exercise type / individual exercise intensity calculation unit 39 uses these input data to calculate the exercise type / individual exercise intensity (METs, U, Kest) d39.

[0181] As previously described with reference to FIG. 9, the exercise type and individual corresponding exercise intensity (METs, U, K) are METs,U,K=(EEref,U,K) / ((body weight [kg])×(exercise time [hr])) (Formula 1) It can be shown as:

[0182] In addition, the individual-adjusted exercise intensity correction coefficient (Rk) d38 calculated by the individual-adjusted exercise intensity correction coefficient calculation unit 38 is, as described above, Rk=(EEref,U,K) / (EEmets,U,K) (Formula 2) It is.

[0183] From the above (Equation 1) and (Equation 2), the following (Equation 3) is derived. METs,U,K=((EEmets,U,K)×(Rk)) / ((body weight [kg])×(exercise time [hr]))...(Formula 3)

[0184] The exercise type and individual exercise intensity calculation unit 39 calculates the exercise time information measured by the timer and the following input data, namely: (a) the individual-adjusted exercise intensity correction coefficient (Rk) d38 calculated by the individual-adjusted exercise intensity correction coefficient calculation unit 38; (b) personal weight information d35 of the user obtained from the personal information database 35; The exercise type / individual exercise intensity calculation unit 39 uses these input data to calculate the exercise type / individual exercise intensity (METs, U, Kest) d39. Based on these input data, the exercise type and individual corresponding exercise intensity (METs, U, K) are calculated according to the above (Equation 3).

[0185] As described above with reference to FIG. 6(b4), the exercise type-individual exercise intensity (METs, U, K) is the individual exercise intensity (METs, U) corresponding to the exercise type (K). As explained above with reference to Fig. 6(b3), the individual exercise intensity (METs, U) is a value indicating the exercise intensity of an individual user (U) calculated by dividing the "calculated activity amount using the breath analysis result (EEref)" obtained from the analysis result of the breath gas analyzer worn by the user who is exercising by the user's weight [kg] and exercise time [hr]. The unit is [kcal / kg / hr]. METs,U=(EEref) / ((body weight [kg])×(exercise time [hr])) It is.

[0186] This exercise type / individual corresponding exercise intensity (METs, U, K) is an exercise intensity specific to the user, and is a different value from the published standard exercise intensity (METs) or the standard exercise intensity corresponding to the exercise type (METs, K). In other words, the exercise intensity is unique to the user and is calculated based on the results of an analysis of exhaled gases during actual exercise by the user and the user's body weight.

[0187] (Step S127) Finally, in step S127, the user terminal 30 stores the calculated exercise type and individual-specific exercise intensity (METs, U, Kest) in the exercise type and individual-specific user-specific exercise intensity database 40.

[0188] This process is executed by the exercise type / individual exercise intensity calculation unit 39 shown in FIG. As a result, the exercise-type user-specific exercise intensity (METs, U, Kest) database 40 described above with reference to Fig. 11 is generated. The following data is associated and registered in the exercise-type user-specific exercise intensity (METs, U, Kest) database 40. (a) Exercise type (K(Kest)) (b) Exercise type and individual user-specific exercise intensity (METs, U, Kest)

[0189] The “(b) type of exercise, individual user-specific exercise intensity (METs, U, Kest)” registered in this database is, as described above, the user-specific exercise intensity calculated based on the results of the exhaled gas analysis during the user’s actual exercise and the user’s body weight.

[0190] Therefore, this exercise intensity reflects the actual physical condition of the user more accurately than the published standard value, the standard exercise intensity for each type of exercise (METs, K). By determining and evaluating the exercise to be performed as rehabilitation based on the exercise intensity registered in this database, it is possible to plan and evaluate optimal rehabilitation according to the user's physical condition.

[0191] (5-1-2. Example of processing in which exercise type information is input from exercise equipment without estimating the type of exercise) In the above-described processing sequence, the type of exercise being performed by the user 11 is estimated based on detection information from a sensor attached to the user. However, when using exercise equipment such as a stationary bike (e.g., an Aero Bike (registered trademark)), exercise type information, such as the load setting of the Aero Bike (registered trademark), can be obtained directly from the Aero Bike (registered trademark). In such a case, the process of estimating the type of exercise using a sensor can be omitted.

[0192] With reference to FIG. 17, an example of exercise using a stationary bike (eg, an aero bike (registered trademark)) will be described. A user 11 rides on an exercise bike (registered trademark) and pedals the exercise bike (registered trademark) while an exhaled gas analysis is performed by an exhaled gas analyzer 20. The analysis results of the exhaled gas analyzer 20 are output to a user terminal 30 worn by the user 11.

[0193] The Aero Bike (registered trademark) has a configuration that allows the amount of resistance to be controlled. In the graph shown in FIG. 17, the horizontal axis represents time (minutes) and the vertical axis represents the load (W). The example shown in the figure is an example of a ramp load test using an exercise bike (registered trademark). The ramp load test involves using an exercise bike (registered trademark) to gradually increase the load at a constant rate, and ending when the user (subject) can no longer pedal.

[0194] As shown in the figure, after a four-minute rest period from 0 to 4 minutes, a four-minute low-load period from 4 to 8 minutes has elapsed, and then the load is gradually increased. In this ramp test, the oxygen intake at the time when the breath analysis result-based exercise type and individual corresponding activity level (EEref, U, K) is at its maximum is the maximum oxygen intake = peakVO2.

[0195] The maximum value of the exercise type and individual corresponding activity level (EEref,U,K) based on the breath analysis results is reached when the load on the Aero Bike (registered trademark) is gradually increased and the user (subject) is no longer able to pedal. The oxygen intake at this point is the maximum oxygen intake level (peakVO2).

[0196] The maximum value of the exercise type and individual compatible exercise intensity (METs, U, K) corresponds to the exercise intensity at the time of measuring the maximum oxygen intake = peak VO2, and by searching for the maximum, the maximum exercise intensity (METs) that the user can perform can be obtained.

[0197] FIG. 18 is a flowchart explaining the processing sequence for performing exercise using the exercise bike (registered trademark) shown in FIG. 17, inputting exercise type information from the exercise equipment, and acquiring the exercise type and individual-compatible exercise intensity (METs, U, K). The process of each step of the flow will be explained.

[0198] (Step S131) First, in step S131, a ramp stress test is started. Specifically, the process of acquiring and recording the breath analysis result-based exercise type and individual corresponding activity amount (EEref, U, K) is started.

[0199] This process is performed by applying the configuration of the exhaled gas analyzer 20 shown in Fig. 9 and the steady-state activity amount analysis unit 33 of the user terminal 30. However, the exercise type (K) is directly input from the exercise bike (registered trademark). For example, the process of acquiring the exercise type and individual corresponding activity amount (EEref,U,K) based on the exhaled breath analysis result corresponding to the exercise type (K) including the load information of the exercise bike (registered trademark) and the process of recording are performed.

[0200] (Step S132) Next, in step S132, it is determined whether the lamp load test has been completed. As mentioned above, the activity ends when the user (subject) 11 can no longer row. If not, the process returns to step S131 to continue the lamp test. If the user (subject) 11 is no longer able to row and it is determined that the process is to end, the process proceeds to step S133.

[0201] (Step S133) In step S133, the type of exercise and individual-compatible exercise intensity (METs, U, K) are calculated according to the following formula. METs,U,K=(EEref,U,K) / ((body weight [kg])×(exercise time [hr]))

[0202] This process is executed by the exercise type / individual exercise intensity calculation unit 39 shown in FIG. The exercise type and individual exercise intensity calculation unit 39 shown in FIG. (a) Individual activity amount (EEref,U,K) calculated by the steady-state activity amount analysis unit 33; (b) weight information obtained from personal information database 35; (c) exercise time obtained from the Aero Bike®; Using this information, the exercise type and individual corresponding exercise intensity (METs, U, K) are calculated according to the above formula.

[0203] An exercise type / individual-adapted exercise intensity calculation unit 39 shown in FIG. 9 stores the calculated exercise type / individual-adapted exercise intensity (METs, U, K) in an exercise type-adapted user-specific exercise intensity database 40 .

[0204] In this way, when using exercise equipment such as an exercise bike (registered trademark), information on the type of exercise, such as the load setting of the exercise bike (registered trademark), can be obtained directly from the exercise bike (registered trademark). Therefore, the estimation process of the type of exercise using a sensor can be omitted, and the type of exercise and individual-compatible exercise intensity (METs, U, K) can be generated and recorded in the database.

[0205] As mentioned above, in this ramp test, the oxygen intake at the maximum point of the exercise type and individual corresponding activity amount based on the breath analysis result (EEref, U, K) is the maximum oxygen intake = peakVO2. The maximum value of the exercise type and individual corresponding activity level (EEref,U,K) based on the breath analysis results is reached when the load on the Aero Bike (registered trademark) is gradually increased and the user (subject) is no longer able to pedal. The oxygen intake at this point is the maximum oxygen intake level (peakVO2).

[0206] The maximum value of the exercise type and individual activity amount based on the breath analysis result (EEref,U,K) Exercise type and individual activity level based on maximum exhalation analysis results (EErefmax,U,K) Let us assume that. In the exercise-type user-specific exercise intensity database 40, an exercise-type user-specific exercise intensity maximum value (METsmax,U,K) is registered according to the following calculation formula. METsmax,U,K=(EErefmax,U,K) / ((body weight [kg])×(exercise time [hr]))

[0207] [5-2. (Phase 2) Sequence of processing executed by the user device during the rehabilitation execution phase outside the hospital] Next, a sequence of processes executed by the user terminal 30 in the "(second phase) rehabilitation execution phase outside the hospital" will be described.

[0208] FIG. 19 is a diagram showing a flowchart illustrating a sequence of processes executed by the user terminal 30 in the "(second phase) rehabilitation execution phase outside the hospital".

[0209] 19 can be executed according to a program stored in a storage unit of the user terminal 30. For example, it can be executed as a program execution process by a processor such as a CPU having a program execution function. The process of each step in the flow will be explained below in order.

[0210] (Step S141) First, in step S141, the user terminal 30 inputs sensor detection information, The type of exercise the user is performing is estimated, i.e., the estimated exercise type (Kest) is determined.

[0211] This process is executed by the motion information estimation unit 32 shown in FIG. The exercise information estimation unit 32 estimates the type of exercise of the user 11 based on the input sensor detection information d31. For example, the type of exercise that the user 11 is performing may be walking (walking speed = 4.0 km / h on flat ground), running (speed = 7.0 km / h on flat ground), aero bike (registered trademark) (load = 120 W), etc.

[0212] (Step S142) Next, in step S142, the user terminal 30 selects an entry of an exercise type that matches or is most similar to the estimated exercise type (Kest) from the exercise type-specific user-specific exercise intensity (METs, U, Kest) database 40, and obtains the exercise type-individual corresponding exercise intensity (METs, U, Kest) of the selected entry.

[0213] This process is executed by the exercise type / individual-adapted exercise intensity acquisition unit 51 shown in FIG.

[0214] The exercise type / individual-specific exercise intensity acquisition unit 51 searches the exercise type-specific user-specific exercise intensity (METs, U, Kest) database 40 having the registration data shown in FIG. 11 based on the estimated exercise type (Kest) input from the exercise information estimation unit 32, and acquires the exercise type / individual-specific exercise intensity (METs, U, Kest) registered in association with the same or most similar exercise type (K) as the estimated exercise type (Kest).

[0215] (Step S143) Next, in step S143, the user terminal 30 calculates the peak corresponding oxygen uptake rate (%peakVO2) based on the estimated exercise type / individual corresponding exercise intensity (METs, U, Kest) and the user's body weight.

[0216] This process is executed by the maximum value-corresponding oxygen intake calculation section 52 shown in FIG. The maximum value corresponding oxygen intake amount calculation unit 52 is (a) Exercise type and individual user-specific exercise intensity (METs, U, Kest) d51 acquired from the exercise type / individual exercise intensity acquisition unit 51; (b) the maximum exercise type user-specific exercise intensity (METsmax,U,Kest) obtained from the exercise type user-specific exercise intensity (METs,U,Kest) database 40; From these data, the maximum corresponding oxygen uptake rate (%peakVO2) d52 is calculated.

[0217] As explained above, the peak oxygen uptake rate (%peakVO2) is calculated using the following formula (4). Maximum oxygen uptake rate (%peakVO2) = (exercise type, individual user-specific exercise intensity (METs, U, Kest)) / (exercise type user-specific maximum exercise intensity (METsmax, U, Kest)) (Equation 4)

[0218] In other words, the maximum oxygen uptake rate (%peakVO2) can be calculated by the ratio of the exercise type and the individual user-specific exercise intensity (METs,U,Kest) to the exercise type user-specific maximum exercise intensity (METsmax,U,Kest).

[0219] (Step S144) Next, in step S144, the user terminal 30 generates exercise implementation status data based on the peak corresponding oxygen uptake rate (%peakVO2) and the exercise time of each exercise, and records the generated exercise implementation status data in the exercise implementation status record database.

[0220] This process is executed by the exercise time integrating unit 53 shown in FIG. The exercise time accumulation unit 53 inputs the peak-corresponding oxygen intake rate (%peakVO2) d52 calculated by the peak-corresponding oxygen intake rate calculation unit 52, generates exercise implementation status data d53 for the user 11, and records it in the exercise implementation status record database 54.

[0221] The exercise time accumulation unit 53 generates exercise implementation status data d53 classified into predefined maximum corresponding oxygen intake rate (%peakVO2) categories for each predefined data generation period (e.g., one week, one day, etc.) and records the data in the exercise implementation status record database 54. As described above, the exercise implementation status record database 54 has the record data shown in Fig. 13. As shown in Fig. 13, the exercise implementation status record database 54 records the exercise time performed by the user 11 in predetermined division units of the peak corresponding oxygen uptake rate (%peakVO2). The exercise implementation status record database 54 shown in FIG. 13 is configured to further record the exercise time corresponding to the type of exercise (Kest).

[0222] (Step S145) Next, in step S145, the user terminal 30 compares and analyzes the exercise implementation status data recorded in the exercise implementation status record database 54 with the exercise target time recorded in the exercise prescription information database 55 to generate an exercise implementation status analysis result.

[0223] This process is executed by the exercise implementation status analysis unit 56 shown in FIG. The exercise implementation status analysis unit 56 acquires data recorded in the exercise implementation status record database 54, compares the acquired data with an exercise prescription provided in advance by a rehabilitation supervisor such as a doctor, and generates an exercise implementation status analysis result d56.

[0224] As described above with reference to FIGS. 12 and 14, the exercise prescription provided in advance by a rehabilitation supervisor such as a doctor is recorded in an exercise prescription information database 55 in the storage unit of the user terminal 30.

[0225] The exercise implementation status analysis unit 56 performs analysis processing to determine whether the actual exercise time of the user 11 has reached the target time, and whether the actual exercise time is longer than the target time, and generates an exercise implementation status analysis result d56 based on the analysis result.

[0226] (Step S146) Finally, in step S146, the user terminal 30 displays the exercise implementation status analysis result generated in step S145 on the display unit.

[0227] This process is a display process using the display unit 57 shown in FIG. As described above with reference to FIG. 15, the display unit 57 displays display data as shown in FIGS. 15(1) and 15(2) as the exercise implementation status analysis result d56.

[0228] By looking at the displayed data, the user 11 can check whether the rehabilitation exercises he or she performed are appropriate in accordance with the exercise prescription. For example, it becomes possible to check the insufficient exercises by exercise intensity, and to perform the exercises appropriate for each exercise intensity.

[0229] [6. (Example 2) Example of communication between user terminal and hospital terminal] Next, as a second embodiment, an embodiment in which communication is performed between a user terminal and a hospital terminal will be described.

[0230] This embodiment realizes the process described above with reference to FIG. As described above, FIG. 4 is a diagram for explaining a processing example of the "(second phase) rehabilitation execution phase outside the hospital". The example shown in FIG. 4 is a processing example in which the user terminal 30 and the hospital terminal 70 communicate with each other. A user 11, who is a person performing rehabilitation, wears a user terminal 30 and inputs sensor detection information from a sensor 12 attached to the body of the user 11, such as an acceleration sensor, gyro, geomagnetic sensor, or air pressure sensor, to the user terminal 30.

[0231] The data processing unit of the user terminal 30 transmits the sensor detection information acquired via the sensor 12 directly to the hospital terminal 70, or transmits the analysis results. The hospital terminal 70 executes the same data analysis process as the process executed by the user terminal 30 described above with reference to FIG. Furthermore, based on the analysis result, advice information and the like for the user 11 is generated and transmitted to the user terminal 30.

[0232] The user terminal 30 displays the advice information received from the hospital terminal 70. The user 11 can check, based on this displayed information, whether or not appropriate rehabilitation is being performed.

[0233] FIG. 20 is a diagram showing an example of the configuration of each device when the above-mentioned process, that is, communication between the user terminal 30 and the hospital terminal 70 is performed. The configurations of the user terminal 30 and the hospital terminal 70 shown in FIG. 20 and the processes executed therein will be described.

[0234] The user terminal 30 is a terminal that is worn by a user 11, who is a rehabilitation participant, on the body while the user 11 is performing exercise as rehabilitation. The sensor detection information input unit 31 of the user terminal 30 acquires sensor detection information d31 from sensors attached to the body of the user 11, such as an acceleration sensor, gyro, geomagnetic sensor, air pressure sensor, etc., and outputs it to the motion information estimation unit 32.

[0235] The exercise information estimation unit 32 estimates the type of exercise of the user 11 based on the input sensor detection information d31. For example, the type of exercise that the user 11 is performing may be walking (walking speed = 4.0 km / h on flat ground), running (speed = 7.0 km / h on flat ground), aero bike (registered trademark) (load = 120 W), etc.

[0236] The exercise information estimation unit 32 outputs the estimated exercise type (Kest), which is the estimation result, to the exercise type / individual-adapted exercise intensity acquisition unit 51.

[0237] The exercise type / individual-based exercise intensity acquisition unit 51 searches the exercise type / user-specific exercise intensity (METs, U, Kest) database 40 based on the estimated exercise type (Kest) d32 input from the exercise information estimation unit 32, and acquires the exercise type and individual-based user-specific exercise intensity (METs, U, Kest) d51 registered in association with the estimated exercise type (Kest).

[0238] The type of exercise and individual user-specific exercise intensity (METs, U, Kest) d51 acquired from the database by the exercise type / individual exercise intensity acquisition unit 51 are output to a maximum value-corresponding oxygen uptake rate calculation unit 52.

[0239] The maximum value-corresponding oxygen uptake rate calculation section 52 obtains from the exercise type user-specific exercise intensity (METs, U, Kest) database 40 the maximum value among the individual user-specific exercise intensity (METs, U, Kest) registered in this database.

[0240] The maximum value of the individual user specific exercise intensity (METs, U, Kest) registered in the exercise type user specific exercise intensity (METs, U, Kest) database 40 is Exercise type: User-specific maximum exercise intensity (METsmax,U,Kest).

[0241] The maximum value corresponding oxygen intake rate calculation unit 52 is (a) Exercise type and individual user-specific exercise intensity (METs, U, Kest) d51 acquired from the exercise type / individual exercise intensity acquisition unit 51; (b) the maximum exercise type user-specific exercise intensity (METsmax,U,Kest) obtained from the exercise type user-specific exercise intensity (METs,U,Kest) database 40; From these data, the maximum corresponding oxygen uptake rate (%peakVO2) d52 is calculated.

[0242] The peak oxygen uptake rate (%peakVO2) is calculated using the following formula (4). Maximum oxygen uptake rate (%peakVO2) = (exercise type, individual user-specific exercise intensity (METs, U, Kest)) / (exercise type user-specific maximum exercise intensity (METsmax, U, Kest)) (Equation 4)

[0243] In other words, the maximum oxygen uptake rate (%peakVO2) can be calculated by the ratio of the exercise type and the individual user-specific exercise intensity (METs,U,Kest) to the exercise type user-specific maximum exercise intensity (METsmax,U,Kest).

[0244] As explained above with reference to Figure 5, the maximum oxygen intake (peakVO2) is the maximum amount of oxygen (oxygen intake (VO2)) taken in by the body, and the oxygen intake rate corresponding to the maximum value (%peakVO2) is the ratio of the actual oxygen intake (VO2) to the maximum oxygen intake (peakVO2).

[0245] The peak-corresponding oxygen intake rate (% peakVO2) d52 calculated by the peak-corresponding oxygen intake rate calculation section 52 is output to the exercise time integration section 53.

[0246] The exercise time accumulation unit 53 inputs the peak-corresponding oxygen intake rate (%peakVO2) d52 calculated by the peak-corresponding oxygen intake rate calculation unit 52, generates exercise implementation status data d53 for the user 11, and records it in the exercise implementation status record database 54.

[0247] The exercise implementation status data of the user 11 recorded in the exercise implementation status record database 54 is transmitted periodically, for example once a week, to the hospital terminal 70 via the communication unit 61. This is exercise implementation status data d54 shown in FIG.

[0248] The communication unit 71 of the hospital terminal 70 receives the exercise implementation status data d54 sent from the user terminal 30 and transfers it to the exercise implementation status analysis unit 72. The exercise implementation status analysis unit 72 acquires the exercise implementation status data d54 received from the user terminal 30, compares the acquired data with an exercise prescription for the user 11 that was created in advance by the hospital, generates an exercise implementation status analysis result d72, and transmits it to the user terminal 30 via the communication unit 71.

[0249] The exercise prescription for the user 11 created in advance at the hospital is recorded as an exercise prescription information database 73 in the storage unit of the hospital terminal 70. The exercise prescription information database 73 stores data similar to the data in the exercise prescription information database 55 stored in the storage unit of the user terminal 30 described above with reference to FIG.

[0250] The exercise implementation status analysis unit 72 of the hospital terminal 70 acquires the following data and performs a comparison process. (a) The actual exercise time performed by the user 11 recorded in the exercise implementation status data d54 received from the user terminal 30 (unit of maximum corresponding oxygen uptake rate (%peakVO2)) (b) A target exercise time to be performed by the user 11 recorded in the exercise prescription information database 73 (unit of maximum corresponding oxygen uptake rate (%peakVO2))

[0251] The exercise implementation status analysis unit 72 compares the above two pieces of data and performs analysis processing to determine whether the actual exercise time of the user 11 has reached the target time, and further whether the actual exercise time is excessive compared to the target time, and generates an exercise implementation status analysis result d72 based on the analysis result.

[0252] The exercise implementation status analysis result d72 generated by the exercise implementation status analysis unit 72 of the hospital terminal 70 is transmitted to the user terminal 30 via the communication unit 71. The communication unit 61 of the user terminal 30 outputs the exercise implementation status analysis result d72 received from the hospital terminal 70 to the display unit 57.

[0253] The exercise implementation status analysis result d72 displayed on the display unit 57 of the user terminal 30 is, for example, the data described above with reference to FIG. FIG. 15 shows the following two examples of display data. (1) When the actual exercise time is almost the same as the target time (2) If the actual exercise time is shorter than the target time

[0254] (1) When the actual exercise time is almost the same as the target time, for example, the following message is displayed, as shown in FIG. 15(1). "This week, I achieved all of my exercise goals. Let's keep it up next week."

[0255] On the other hand, (2) when the actual exercise time is shorter than the target time, as shown in (2a), "I haven't yet met my exercise goal time this week. I still have time." Such a message is displayed, and the user: "Check what exercise you are missing" When this message display area is tapped, the specific deficit time and exercise content for each exercise intensity content are displayed, as shown in (2b).

[0256] By looking at the displayed data, the user 11 can check whether the rehabilitation exercises he or she performed are appropriate in accordance with the exercise prescription. For example, it becomes possible to check the insufficient exercises by exercise intensity, and to perform the exercises appropriate for each exercise intensity.

[0257] Next, a processing sequence executed by the user terminal 30 in this embodiment will be described with reference to the flowchart shown in FIG. 21 can be executed according to a program stored in a storage unit of the user terminal 30. For example, it can be executed as a program execution process by a processor such as a CPU having a program execution function. The process of each step in the flow will be explained below in order.

[0258] (Step S151) First, in step S151, the user terminal 30 inputs sensor detection information, The type of exercise the user is performing is estimated, i.e., the estimated exercise type (Kest) is determined.

[0259] This process is executed by the motion information estimation unit 32 shown in FIG. The exercise information estimation unit 32 estimates the type of exercise of the user 11 based on the input sensor detection information d31. For example, the type of exercise that the user 11 is performing may be walking (walking speed = 4.0 km / h on flat ground), running (speed = 7.0 km / h on flat ground), aero bike (registered trademark) (load = 120 W), etc.

[0260] (Step S152) Next, in step S152, the user terminal 30 selects an entry of an exercise type that matches or is most similar to the estimated exercise type (Kest) from the exercise type-specific user-specific exercise intensity (METs, U, Kest) database 40, and obtains the exercise type-individual corresponding exercise intensity (METs, U, Kest) of the selected entry.

[0261] This process is executed by the exercise type / individual-adapted exercise intensity obtaining unit 51 shown in FIG.

[0262] The exercise type / individual-specific exercise intensity acquisition unit 51 searches the exercise type-specific user-specific exercise intensity (METs, U, Kest) database 40 having the registration data shown in FIG. 11 based on the estimated exercise type (Kest) input from the exercise information estimation unit 32, and acquires the exercise type / individual-specific exercise intensity (METs, U, Kest) registered in association with the same or most similar exercise type (K) as the estimated exercise type (Kest).

[0263] (Step S153) Next, in step S153, the user terminal 30 calculates the peak corresponding oxygen uptake rate (%peakVO2) based on the estimated exercise type / individual corresponding exercise intensity (METs, U, Kest) and the user's body weight.

[0264] This process is executed by the maximum value-corresponding oxygen intake calculation section 52 shown in FIG. The maximum value corresponding oxygen intake amount calculation unit 52 is (a) Exercise type and individual user-specific exercise intensity (METs, U, Kest) d51 acquired from the exercise type / individual exercise intensity acquisition unit 51; (b) the maximum exercise type user-specific exercise intensity (METsmax,U,Kest) obtained from the exercise type user-specific exercise intensity (METs,U,Kest) database 40; From these data, the maximum corresponding oxygen uptake rate (%peakVO2) d52 is calculated.

[0265] As explained above, the peak oxygen uptake rate (%peakVO2) is calculated using the following formula (4). Maximum oxygen uptake rate (%peakVO2) = (exercise type, individual user-specific exercise intensity (METs, U, Kest)) / (exercise type user-specific maximum exercise intensity (METsmax, U, Kest)) (Equation 4)

[0266] In other words, the maximum oxygen uptake rate (%peakVO2) can be calculated by the ratio of the exercise type and the individual user-specific exercise intensity (METs,U,Kest) to the exercise type user-specific maximum exercise intensity (METsmax,U,Kest).

[0267] (Step S154) Next, in step S154, the user terminal 30 generates exercise implementation status data based on the peak corresponding oxygen uptake rate (%peakVO2) and the exercise time of each exercise, and records the generated exercise implementation status data in the exercise implementation status record database.

[0268] This process is executed by the exercise time integrating unit 53 shown in FIG. The exercise time accumulation unit 53 inputs the peak-corresponding oxygen intake rate (%peakVO2) d52 calculated by the peak-corresponding oxygen intake rate calculation unit 52, generates exercise implementation status data d53 for the user 11, and records it in the exercise implementation status record database 54.

[0269] The exercise time accumulation unit 53 generates exercise implementation status data d53 classified into predefined maximum corresponding oxygen intake rate (%peakVO2) categories for each predefined data generation period (e.g., one week, one day, etc.) and records the data in the exercise implementation status record database 54. As described above, the exercise implementation status record database 54 has the record data shown in Fig. 13. As shown in Fig. 13, the exercise implementation status record database 54 records the exercise time performed by the user 11 in predetermined division units of the peak corresponding oxygen uptake rate (%peakVO2). The exercise implementation status record database 54 shown in FIG. 13 is configured to further record the exercise time corresponding to the type of exercise (Kest).

[0270] (Step S155) Next, in step S155, the user terminal 30 transmits the exercise implementation status data recorded in the exercise implementation status record database 54 to the hospital terminal 70.

[0271] (Step S156) Finally, in step S156, the user terminal 30 displays the exercise implementation status analysis result received from the hospital terminal 70 on the display unit.

[0272] This process is a display process using the display unit 57 shown in FIG. As described above with reference to FIG. 15, the display unit 57 displays display data as shown in FIGS. 15(1) and 15(2) as the exercise implementation status analysis results.

[0273] By looking at the displayed data, the user 11 can check whether the rehabilitation exercises he or she performed are appropriate in accordance with the exercise prescription. For example, it becomes possible to check the insufficient exercises by exercise intensity, and to perform the exercises appropriate for each exercise intensity.

[0274] Next, a processing sequence executed by the hospital terminal 70 will be described with reference to the flowchart shown in FIG. 22 can be executed according to a program stored in a storage unit of the hospital terminal 70. For example, it can be executed as a program execution process by a processor such as a CPU having a program execution function. The process of each step in the flow will be explained below in order.

[0275] (Step S161) First, in step S161, the hospital terminal 70 receives the exercise implementation status data recorded in the exercise implementation status record database 54 from the user terminal 30.

[0276] (Step S162) Next, in step S162, the hospital terminal 70 compares and analyzes the exercise implementation status data received from the user terminal 30 with the exercise goal time recorded in the exercise prescription information database 73 to generate an exercise implementation status analysis result.

[0277] This process is executed by the exercise implementation status analysis unit 72 shown in FIG. The exercise implementation status analysis unit 72 performs a comparison process between the exercise implementation status data received from the user terminal 30 and an exercise prescription that is prepared in advance by a rehabilitation supervisor such as a doctor and recorded in an exercise prescription information database 73.

[0278] The exercise implementation status analysis unit 72 performs analysis processing to determine whether the actual exercise time of the user 11 has reached the target time, and whether the actual exercise time is longer than the target time, and generates an exercise implementation status analysis result d72 based on the analysis result.

[0279] (Step S163) Finally, in step S163, the hospital terminal 70 transmits the exercise implementation status analysis result generated in step S162 to the user terminal 30 via the communication unit 71.

[0280] After this transmission process, the process of step S156 in the flow shown in FIG. 21 is executed. That is, in step S156, the exercise implementation status analysis result received from the hospital terminal 70 is displayed on the display unit. By looking at the displayed data, the user 11 can check whether the rehabilitation exercises he or she performed are appropriate in accordance with the exercise prescription. For example, it becomes possible to check the insufficient exercises by exercise intensity, and to perform the exercises appropriate for each exercise intensity.

[0281] [7. Other Examples] Next, an alternative embodiment to the above embodiment will be described. Several examples are described below. Example 3: Example in which an electrocardiogram (ECG) measurement is prompted based on the results of exercise load analysis (Example 4) Example of presenting walking and running route information using a map (Example 5) Example of updating exercise prescription

[0282] [7-1. (Example 3) Example of encouraging measurement of electrocardiogram (ECG) based on analysis results of exercise load] First, as a third embodiment, an embodiment in which measurement of an electrocardiogram (ECG) is prompted based on the analysis result of an exercise load will be described.

[0283] When the user 11 is performing exercise as part of rehabilitation after being discharged from the hospital, excessive exercise may increase the burden on the heart, leading to a dangerous condition. The third embodiment is an embodiment for preventing such a risk.

[0284] After the user 11 is discharged from the hospital, while the user 11 is performing rehabilitation exercise, the pulse rate of the user 11 is obtained, and if it is detected that the pulse rate is outside a specified range, warning information is output to prompt the user to take an electrocardiogram (ECG). The warning information may be displayed on the display unit of the user terminal 30, or may be configured to utilize vibration, sound, or the like.

[0285] FIG. 23 is a block diagram showing the configuration of a user terminal 30 that executes the process according to the third embodiment. An exercise prescription information database 64 is recorded in the storage section of the user terminal 30 shown in FIG.

[0286] An example of the data configuration of the exercise prescription information database 64 used in this embodiment will be described with reference to FIG. The exercise prescription information database 64 used in this embodiment records the data described above with reference to FIG. 14, i.e., the pulse rate range (normal range) and upper heart rate limit (upper normal limit) for the user 11, which are generated based on the judgment of a rehabilitation supervisor such as a doctor, in accordance with the exercise time that the user 11 should perform, in a predetermined division unit of the maximum corresponding oxygen uptake rate (%peakVO2).

[0287] Returning to FIG. 23, the configuration and processing of the user terminal 30 will be described. The sensor detection value input unit 61 inputs a heart rate value and a pulse rate value from a sensor provided on the user 11 who is performing exercise as rehabilitation.

[0288] Immediately after the start of rehabilitation, the user 11 wears a pulse detection sensor and measures only the pulse value. The pulse value d61a acquired by the sensor detection value input unit 61 is input to the pulse upper limit approach determination unit 62.

[0289] The pulse upper limit approach judgment unit 62 compares the pulse value d61a input from the sensor detection value input unit 61 with the pulse rate specified range (normal value range) for the user 11 recorded in the exercise prescription information database 64, and judges whether the pulse value d61a is within the pulse rate specified range (normal value range) registered in the database.

[0290] If the pulse value d61a is within a pulse rate prescribed range (normal value range) registered in the database, the control unit 65 outputs to the instruction information generating unit 65 determination information indicating that the pulse value d61a is within the normal range. The indication information generating unit 65 generates indication information d65 indicating that the value is normal, and outputs it to the output unit (display unit or the like) 66.

[0291] On the other hand, if the pulse upper limit approach judgment unit 62 judges that the pulse value d61a input from the sensor detection value input unit 61 is not within the pulse rate specified range (normal value range) registered in the database, it outputs judgment information indicating that it is outside the normal range to the instruction information generation unit 65. The instruction information generating unit 65 generates instruction information d65 such as a message encouraging the user 11 to wear a heart rate monitor for detecting a heart rate value, or an alarm sound or lamp light, and outputs it to an output unit (display unit, etc.) 66.

[0292] Specifically, for example, display data as shown in FIG. 25(1) is output to the output unit (display unit) 66 of the user terminal 30. In response to this instruction information d65, the user 11 wears a heart rate monitor for detecting a heart rate value and continues the exercise as rehabilitation.

[0293] Next, the process to be performed after the heart rate monitor is attached to detect the heart rate will be described. The sensor detection value input unit 61 acquires the heart rate value of the user 11 from a heart rate meter worn by the user 11 . As a heart rate monitor for detecting the heart rate, for example, a heart rate monitor using the lead II method that measures the potential difference between the left and right hands, or a wearable device type heart rate monitor can be used.

[0294] The heart rate value d61b acquired by the sensor detection value input unit 61 is input to the heart rate upper limit approach determination unit 63. The upper heart rate asymptotic judgment unit 63 compares the heart rate value d61b input from the sensor detection value input unit 61 with the upper heart rate value (upper normal value) for the user 11 recorded in the exercise prescription information database 64, and judges whether the heart rate value d61b is below the upper heart rate value (upper normal value) registered in the database.

[0295] If the heart rate value d61b is equal to or lower than the upper heart rate limit value (upper normal limit value) registered in the database, determination information indicating that it is within the normal range is output to the instruction information generating unit 65. The indication information generating unit 65 generates indication information d65 indicating that the value is normal, and outputs it to the output unit (display unit or the like) 66.

[0296] On the other hand, if the heart rate upper limit asymptotic judgment unit 63 judges that the heart rate value d61b input from the sensor detection value input unit 61 is not below the heart rate upper limit value (upper normal value) registered in the database, it outputs judgment information indicating that the heart rate exceeds the upper limit to the instruction information generation unit 65. The instruction information generating unit 65 generates instruction information d65 such as a message urging the user 11 to stop exercising, or an alarm sound, a lamp light, or the like, and outputs it to an output unit (display unit, etc.) 66.

[0297] Specifically, for example, display data as shown in FIG. 25(2) is output to the output unit (display unit) 66 of the user terminal 30. In response to this instruction information d65, the user 11 stops exercising. With this configuration, the user 11 can prevent excessive stress on the heart caused by continuing exercise, and can carry out safe rehabilitation.

[0298] Next, a processing sequence of the third embodiment will be described with reference to the flowchart shown in FIG. The processing of each step will be explained in sequence below.

[0299] (Step S181) First, in step S181, the user terminal 30 acquires a pulse value.

[0300] This process is executed by the sensor detection value input unit 61 shown in FIG. The user 11 is performing rehabilitation exercise while wearing a pulse detection sensor. A pulse value d61a acquired by the sensor detection value input unit 61 is input to a pulse upper limit approach determination unit 62.

[0301] (Step S182) Next, in step S182, the user terminal 30 compares the pulse value d61a input from the sensor detection value input unit 61 with the specified pulse rate range (normal value range) for the user 11 recorded in the exercise prescription information database 64, and determines whether the pulse value d61a is within the specified pulse rate range (normal value range) registered in the database.

[0302] If the pulse value d61a is within the pulse rate specified range (normal value range) registered in the database, the process returns to step S181, and the process of obtaining the pulse value continues. In this case, judgment information indicating that the pulse value is within the normal range may be output to the instruction information generation unit 65, and the instruction information generation unit 65 may generate instruction information d65 indicating that the value is normal and output it to the output unit (display unit, etc.) 66.

[0303] On the other hand, if it is determined in step S182 that the pulse value d61a input from the sensor detection value input unit 61 is not within the pulse rate prescribed range (normal value range) registered in the database, the process proceeds to step S183.

[0304] (Step S183) If it is determined in step S182 that the pulse value d61a is not within the pulse rate prescribed range (normal value range), the process proceeds to step S183.

[0305] In this case, in step S183, the user terminal 30 outputs judgment information indicating that the value is outside the normal range to the instruction information generation unit 65, and the instruction information generation unit 65 generates instruction information d65 such as a message urging the user 11 to wear a heart rate monitor to detect the heart rate value, or an alarm sound, a lamp light, etc., and outputs it to the output unit (display unit, etc.) 66.

[0306] Specifically, for example, display data as shown in FIG. 25(1) is output to the output unit (display unit) 66 of the user terminal 30. In response to this instruction information d65, the user 11 wears a heart rate monitor for detecting a heart rate value and continues the exercise as rehabilitation.

[0307] (Step S184) The user 11 continues exercising as rehabilitation while wearing a heart rate monitor for detecting the heart rate value. In step S184, the user terminal 30 acquires the heart rate value of the user 11 from the heart rate meter worn by the user 11.

[0308] This process is executed by the sensor detection value input unit 61 shown in FIG. The user 11 is performing rehabilitation exercise while wearing a heart rate monitor. The heart rate value d61b acquired by the sensor detection value input unit 61 is input to the heart rate upper limit approach determination unit 63.

[0309] (Step S185) Next, in step S185, the user terminal 30 compares the heart rate value d61b input from the sensor detection value input unit 61 with the upper heart rate limit value (upper normal limit value) for the user 11 recorded in the exercise prescription information database 64, and determines whether the heart rate value d61b is equal to or lower than the upper heart rate limit value (upper normal limit value) registered in the database.

[0310] If the heart rate value d61b is equal to or lower than the upper heart rate limit (upper normal limit) registered in the database, the process returns to step S184, and the process of obtaining the heart rate value continues. In this case, judgment information indicating that the heart rate value is within the normal range may be output to the instruction information generation unit 65, and the instruction information generation unit 65 may generate instruction information d65 indicating that the value is normal and output it to the output unit (display unit, etc.) 66.

[0311] On the other hand, if it is determined in step S185 that the heart rate value d61b input from the sensor detection value input unit 61 is not equal to or lower than the upper heart rate limit value (upper normal value) registered in the database, the process proceeds to step S186.

[0312] (Step S186) If it is determined in step S185 that the heart rate value d61b is not equal to or lower than the upper heart rate limit (upper normal limit), the process proceeds to step S186.

[0313] In this case, in step S186, the user terminal 30 outputs judgment information indicating that the heart rate value d61b is not below the upper heart rate limit value (upper normal limit) to the instruction information generation unit 65, and the instruction information generation unit 65 generates instruction information d65 such as a message urging the user 11 to stop exercising, or a warning sound, a lamp light, etc., and outputs it to the output unit (display unit, etc.) 66.

[0314] Specifically, for example, display data as shown in FIG. 25(2) is output to the output unit (display unit) 66 of the user terminal 30. In response to this instruction information d65, the user 11 stops exercising. With this configuration, the user 11 can prevent excessive stress on the heart caused by continuing exercise, and can carry out safe rehabilitation.

[0315] [7-2. (Example 4) Example of presenting walking and running route information using a map] Next, as a fourth embodiment, an embodiment in which route information for walking or running is presented using a map will be described.

[0316] The fourth embodiment is an embodiment in which, when the user 11 walks or runs as rehabilitation exercise, optimal walking or running route information is provided using a map. Specifically, for example, a map is displayed on the display unit of the user terminal 30 as shown in FIG. 27, and optimal walking or running route information is provided to the user 11.

[0317] FIG. 28 is a diagram for explaining the configuration and processing of the user terminal 30 and the geographic information server 90 which execute the processing of the fourth embodiment. The process of the fourth embodiment using the user terminal 30 and the geographic information server 90 will be described with reference to FIG.

[0318] The user terminal 30 is a terminal that is worn by a user 11, who is a rehabilitation participant, on the body while the user 11 is performing rehabilitation exercise. The sensor detection information input unit 81 of the user terminal 30 acquires sensor detection information d81 from sensors attached to the body of the user 11, such as position sensors, acceleration sensors, gyros, geomagnetic sensors, and air pressure sensors, and outputs it to the motion information estimation unit 82.

[0319] Furthermore, in this embodiment, the sensor detection information (location information) d81a of the location sensor included in the sensor detection information d81, i.e., the sensor detection information (location information) d81a which is location information indicating the location of the user 11, is transmitted to the geographic information providing server 90 via the communication unit 87.

[0320] Next, the processing of the exercise information estimation unit 82 and subsequent units of the user terminal 30 will be described. The exercise information estimation unit 82 estimates the type of exercise of the user 11 based on the input sensor detection information d81. For example, the type of exercise that the user 11 is performing may be walking (walking speed = 4.0 km / h on flat ground), running (speed = 7.0 km / h on flat ground), or aero bike (registered trademark) (load = 120 W).

[0321] The exercise information estimation unit 82 outputs the estimated exercise type (Kest), which is the estimation result, to the exercise type / individual-adapted exercise intensity acquisition unit 83. The exercise type / individual-specific exercise intensity acquisition unit 83 searches the exercise type / user-specific exercise intensity (METs, U, Kest) database 40 based on the estimated exercise type (Kest) d82 input from the exercise information estimation unit 82, and acquires the exercise type and individual-specific user-specific exercise intensity (METs, U, Kest) d83 registered in correspondence with the estimated exercise type (Kest).

[0322] The type of exercise and individual user-specific exercise intensity (METs, U, Kest) d83 acquired from the database by the exercise type / individual exercise intensity acquisition unit 83 are output to a maximum value-corresponding oxygen uptake rate calculation unit 84.

[0323] The maximum value-corresponding oxygen uptake rate calculation section 84 obtains from the exercise-type user-specific exercise intensity (METs, U, Kest) database 40 the maximum value among the individual-corresponding user-specific exercise intensity (METs, U, Kest) registered in this database.

[0324] The maximum value of the individual user specific exercise intensity (METs, U, Kest) registered in the exercise type user specific exercise intensity (METs, U, Kest) database 40 is Exercise type: User-specific maximum exercise intensity (METsmax,U,Kest).

[0325] The maximum value corresponding oxygen intake rate calculation unit 84 is (a) Exercise type and individual user-specific exercise intensity (METs, U, Kest) d83 acquired from the exercise type / individual exercise intensity acquisition unit 83; (b) the maximum exercise type user-specific exercise intensity (METsmax,U,Kest) obtained from the exercise type user-specific exercise intensity (METs,U,Kest) database 40; From these data, the maximum corresponding oxygen uptake rate (%peakVO2)d84 is calculated.

[0326] The peak oxygen uptake rate (%peakVO2) is calculated using the following formula (4). Maximum oxygen uptake rate (%peakVO2) = (exercise type, individual user-specific exercise intensity (METs, U, Kest)) / (exercise type user-specific maximum exercise intensity (METsmax, U, Kest)) (Equation 4)

[0327] In other words, the maximum oxygen uptake rate (%peakVO2) can be calculated by the ratio of the exercise type and the individual user-specific exercise intensity (METs,U,Kest) to the exercise type user-specific maximum exercise intensity (METsmax,U,Kest).

[0328] As explained above with reference to Figure 5, the maximum oxygen intake (peakVO2) is the maximum amount of oxygen (oxygen intake (VO2)) taken in by the body, and the oxygen intake rate corresponding to the maximum value (%peakVO2) is the ratio of the actual oxygen intake (VO2) to the maximum oxygen intake (peakVO2).

[0329] The peak-corresponding oxygen intake rate (%peakVO2) d84 calculated by the peak-corresponding oxygen intake rate calculation section 84 is output to the exercise prescription corresponding action route information search section 86.

[0330] The exercise prescription corresponding behavior route information search unit 86 inputs the maximum value corresponding oxygen intake rate (%peakVO2) d84 calculated by the maximum value corresponding oxygen intake rate calculation unit 84, and further refers to the exercise prescription information recorded in the exercise prescription information database 85 to generate exercise prescription information d86a that achieves the maximum value corresponding oxygen intake rate (%peakVO2). In addition, the exercise prescription information database 85 stores data similar to the data previously described with reference to FIG.

[0331] The exercise prescription information d86a for achieving the maximum oxygen uptake rate (%peakVO2) generated by the exercise prescription corresponding action route information search unit 86 is transmitted to the geographic information providing server 90 via the communication unit 87.

[0332] The geographic information providing server 90 receives the following two pieces of information from the user terminal 30: (a) Sensor detection information (location information) d81a indicating the user's current location; (b) Exercise prescription information d86a for achieving the maximum oxygen intake rate (%peakVO2) generated by the exercise prescription corresponding action route information search unit 86;

[0333] The geographic information providing server 90 inputs these two pieces of information via a communication unit 91, and transfers the input information to an exercise prescription corresponding action route information generating unit 92.

[0334] The exercise prescription corresponding action route information generating unit 92 uses the input information (a) and (b) and map information stored in the geographic information database 93, etc. to generate exercise prescription corresponding action route information d92.

[0335] In addition to map information, the geographic information database 93 also stores detailed information about roads and the like on the map. For example, as shown in FIG. 29, information on the gradient of roads on a map, stairs, bus route information, and further information on the location of each road are recorded.

[0336] The exercise prescription corresponding action route information generating unit 92 generates exercise prescription corresponding action route information d92 using the input information (a) and (b) and map information stored in a geographic information database 93 including detailed information of roads on a map as shown in FIG. 29.

[0337] The exercise prescription corresponding behavior route information d92 is composed of geographical route information that allows exercise that matches or is similar to the exercise prescription information d86a that achieves the maximum corresponding oxygen intake rate (%peakVO2) generated by the exercise prescription corresponding behavior route information search unit 86 of the user terminal 30. Specifically, the data includes route information on a map along which a user can travel, as shown in FIG.

[0338] The geographic information providing server 90 transmits the exercise prescription corresponding action route information d92 generated by the exercise prescription corresponding action route information generating unit 92 to the user terminal 30 via the communication unit 91.

[0339] The user terminal 30 receives the exercise prescription corresponding action route information d92 transmitted by the geographic information providing server 90 via the communication unit 87, and transfers it to the exercise prescription corresponding route information search unit 86.

[0340] The exercise prescription corresponding route information search unit 86 generates display data d86b based on the exercise prescription corresponding action route information d92 received from the geographic information providing server 90 and the exercise prescription information recorded in the exercise prescription information database 85, and displays it on the display unit 88.

[0341] The display data d86b generated by the exercise-prescription-compatible route information search unit 86 is display data including information indicating the type of exercise and route that the user should perform on a map as shown in FIG.

[0342] The user 11 can check the exercise he or she is going to perform, specifically, his or her walking route and walking speed, by looking at this display data, and can perform appropriate rehabilitation exercise.

[0343] [7-3. (Example 5) Example of updating exercise prescription] Next, as a fifth embodiment, an example in which an update process of an exercise prescription is performed will be described.

[0344] After the user 11 is discharged from the hospital, the period during which the user 11 performs rehabilitation exercises may be long, and the effects of rehabilitation vary from person to person, so the exercises to be performed as rehabilitation may differ from the exercise prescription information set at the time of discharge. In such a case, a rehabilitation supervisor such as a doctor at a hospital needs to update the exercise prescription and provide the updated exercise prescription information to the user 11 on a regular basis. The fifth embodiment is an embodiment that enables such an exercise prescription update process.

[0345] The configuration and processing for executing the exercise prescription update processing will be described with reference to FIG. 30 and subsequent figures. FIG. 30 is a diagram for explaining the configuration and processing of the user terminal 30 and the hospital terminal 70 which execute the exercise prescription update processing of the fifth embodiment.

[0346] The configuration of the user terminal 30 is substantially the same as the configuration of the user terminal 30 shown in FIG. 20 previously explained as the second embodiment, and the same reference numbers as in FIG. 20 are used for the respective components. The configurations of the user terminal 30 and the hospital terminal 70 shown in FIG. 30 and the processes executed therein will be described.

[0347] The user terminal 30 is a terminal that is worn by a user 11, who is a rehabilitation participant, on the body while the user 11 is performing exercise as rehabilitation. The sensor detection information input unit 31 of the user terminal 30 acquires sensor detection information d31 from sensors attached to the body of the user 11, such as an acceleration sensor, gyro, geomagnetic sensor, air pressure sensor, etc., and outputs it to the motion information estimation unit 32.

[0348] The exercise information estimation unit 32 estimates the type of exercise currently being performed by the user 11 based on the input sensor detection information d31. The exercise information estimation unit 32 outputs the estimated exercise type (Kest), which is the estimation result, to the exercise type / individual-adapted exercise intensity acquisition unit 51.

[0349] The exercise type / individual-based exercise intensity acquisition unit 51 searches the exercise type / user-specific exercise intensity (METs, U, Kest) database 40 based on the estimated exercise type (Kest) d32 input from the exercise information estimation unit 32, and acquires the exercise type and individual-based user-specific exercise intensity (METs, U, Kest) d51 registered in association with the estimated exercise type (Kest).

[0350] The type of exercise and individual user-specific exercise intensity (METs, U, Kest) d51 acquired from the database by the exercise type / individual exercise intensity acquisition unit 51 are output to a maximum value-corresponding oxygen uptake rate calculation unit 52.

[0351] The maximum value-corresponding oxygen uptake rate calculation section 52 obtains from the exercise type user-specific exercise intensity (METs, U, Kest) database 40 the maximum value among the individual user-specific exercise intensity (METs, U, Kest) registered in this database. The maximum value corresponding oxygen intake rate calculation unit 52 is (a) Exercise type and individual user-specific exercise intensity (METs, U, Kest) d51 acquired from the exercise type / individual exercise intensity acquisition unit 51; (b) the maximum exercise type user-specific exercise intensity (METsmax,U,Kest) obtained from the exercise type user-specific exercise intensity (METs,U,Kest) database 40; From these data, the maximum corresponding oxygen uptake rate (%peakVO2) d52 is calculated.

[0352] The peak-corresponding oxygen intake rate (% peakVO2) d52 calculated by the peak-corresponding oxygen intake rate calculation section 52 is output to the exercise time integration section 53. The exercise time integrating section 53 receives the peak-corresponding oxygen intake rate (%peakVO2) d52 calculated by the peak-corresponding oxygen intake rate calculating section 52 and generates exercise implementation status data d53 of the user 11.

[0353] The exercise implementation status data d53 of the user 11 generated by the exercise time integrating section 53 is input to the exercise implementation status analyzing section 56 and is also transmitted to the hospital terminal 70 via the communication section 61.

[0354] The hospital terminal 70 receives the exercise implementation status data d53 transmitted from the user terminal 30 via the communication unit 71, and records the received exercise implementation status data d53 in the exercise implementation status record database 75.

[0355] An example of the exercise implementation status record database 75 stored in the storage unit of the hospital terminal 70 is shown in FIG. As shown in FIG. 31, exercise implementation status record database 75 stored in the storage unit of hospital terminal 70 records exercise implementation status record data for each user. The exercise implementation status record data for each user includes the exercise time performed by each user in a predetermined division unit of the maximum oxygen uptake rate (%peakVO2). In addition, the exercise time corresponding to the type of exercise (K) is also recorded.

[0356] The example shown in Fig. 31 is an example in which record data is generated and recorded on a weekly basis. That is, the exercise time performed by each user during one week is recorded in a predetermined division unit of the maximum corresponding oxygen uptake rate (%peakVO2), and further, it is a data recording example in which it is recorded by exercise type unit.

[0357] The exercise prescription update unit 77 of the hospital terminal 70 analyzes the exercise implementation status data d53 received from the user terminal 30. When analyzing the exercise implementation status data, the exercise prescription update unit 77 of the hospital terminal 70 updates the exercise prescription information for the user 11 recorded in the exercise prescription information database 76 as necessary.

[0358] That is, as shown in FIG. 30, the exercise prescription update unit 77 reads out the pre-update exercise prescription d76 for the user 11 recorded in the exercise prescription information database 76, and generates a new updated exercise prescription d77 in accordance with the analysis results of the exercise implementation status data d53 received from the user terminal 30, and records the new updated exercise prescription d77 in the exercise prescription information database 76.

[0359] FIG. 32 shows an example of the exercise prescription information database 76 stored in the storage unit of the hospital terminal 70. As shown in FIG. 32, the exercise prescription information database 76 records the exercise time that each user should perform in a predetermined division unit of the peak corresponding oxygen uptake rate (%peakVO2), similar to the exercise implementation status record database 75 described above with reference to FIG. 31. The exercise prescription information database 76 shown in FIG. 32 is an example in which exercise goal times are recorded on a weekly basis, similar to the exercise implementation status record database 75 shown in FIG. 31 described above.

[0360] The exercise prescription update process in the exercise prescription update unit 77 is executed under the confirmation of a rehabilitation supervisor such as a doctor. Specifically, for example, exercise prescription information for each user is displayed on the exercise prescription operation UI unit 78, and a rehabilitation supervisor such as a doctor checks the displayed data and performs a process of changing, i.e., updating, the exercise prescription as necessary.

[0361] FIG. 33 is a display example of exercise prescription information for each user displayed on the exercise prescription operation UI section 78. In FIG. A rehabilitation supervisor such as a doctor checks the displayed data, and if he or she determines that the exercise prescription needs to be changed, that is, updated, he or she clicks on the update icon on the far right. By clicking, detailed exercise prescription information for the individual user, for example as shown in FIG. 34, is displayed.

[0362] The individualized exercise prescription information shown in FIG. 34 shows the current (12th week) exercise prescription in the middle section and past (1st to 11th weeks) exercise results in the lower section. The current (12th week) exercise prescription in the middle section is information showing the time (minutes) of exercise that the user (person undergoing rehabilitation) should perform on a weekly basis, divided into categories according to exercise load. The past exercise results (1st to 11th weeks) in the lower section are information showing the time (minutes (min)) of exercise actually performed by the user (person undergoing rehabilitation) on a weekly basis, categorized by exercise load.

[0363] Point A shown in the past exercise results (weeks 1 to 11) in the lower section is the point at which it is confirmed that the exercise load transitioned from 80% to 70% between weeks 3 and 4. This point A is a point at which, when the user (person undergoing rehabilitation) exercises at the same exercise intensity, the cardiopulmonary function of the user is improving and the exercise load is decreasing.

[0364] Point B indicates the point at which the exercise prescription was switched from menu A to menu B. This point B indicates the time when the exercise prescription was updated, and by configuring the exercise prescription menu to be clearly indicated for each week, it becomes easy to confirm the impact of updating the exercise prescription.

[0365] Fig. 35 shows specific examples of exercise prescription menu A and exercise prescription menu B. In this way, each menu is information showing the time (minutes (min)) of exercise that the user should perform for each exercise load.

[0366] When the "Confirm" icon shown in the past exercise results (1st to 11th weeks) in the lower part of FIG. 34 is clicked, the specific exercise content for that week is displayed. For example, as shown in FIG. 36, detailed information indicating the content of the exercise the user actually performed that week is displayed.

[0367] If a rehabilitation supervisor such as a doctor checks the displayed data and determines that it is necessary to change, i.e., update, the exercise prescription, he / she clicks on the “change icon” on the far right of the current (12th week) exercise prescription in the middle row of the displayed data shown in Figure 34.

[0368] This click process displays a UI with a display screen for changing the exercise prescription, that is, for updating the exercise prescription. FIG. 37 shows a specific example of a UI for update processing.

[0369] As shown in FIG. 37, the UI for update processing displays a table in which the exercise time (minutes) that the user should exercise on a weekly basis can be set by dividing it into exercise load units. This table contains recommendation data ((A) Recommendation by the System) that is automatically calculated by the system based on the user's exercise history, etc., as well as a manual input field ((B) Manual Input) for a doctor or other rehabilitation supervisor.

[0370] A rehabilitation supervisor such as a doctor can select data recommended by the system (A) or can input arbitrary data into the manual input field ((B) manual input). Furthermore, by selecting either (A) or (B) and clicking the confirmation icon on the far right, the updated exercise prescription for the current week is decided.

[0371] Operation information in the exercise prescription operation UI section 78 is input to the exercise prescription update section 77, which performs update processing of the exercise prescription in accordance with the operation information in the exercise prescription operation UI section 78.

[0372] The exercise prescription update unit 77 records the new updated exercise prescription d77 generated according to the operation information in the exercise prescription operation UI unit 78 in the exercise prescription information database 76 and transmits it to the user terminal 30 via the communication unit 71. The user terminal 30 receives the updated exercise prescription d77 transmitted by the hospital terminal 70 via the communication unit 61, and inputs it to the exercise implementation status analysis unit 56.

[0373] The exercise implementation status analysis unit 56 compares the exercise implementation status data d53 of the user 11 generated by the exercise time accumulation unit 53 with the latest updated exercise prescription d77 received from the hospital terminal 70, generates an exercise implementation status analysis result d56, and outputs it to the display unit 57.

[0374] When the exercise prescription information is updated, the display data becomes, for example, the display data shown in FIG. 38(1) shows an initial screen of display data when exercise prescription information has been updated, notifying the user 11, who is carrying out rehabilitation, that the exercise prescription information has been updated. FIG. 38(2) is a display screen of updated exercise prescription information which is transitioned to by touching “Check contents” shown in (1).

[0375] By looking at this display data, the user 11 who is carrying out rehabilitation can know that the exercise prescription information has been updated by the hospital, and can further check the specific updated exercise prescription information.

[0376] [8. Examples of hardware configurations of information processing devices] Next, an example of the hardware configuration of the user terminal 30 and the hospital terminal 70 used in the processing of the present disclosure, and further an information processing device constituting the geographic information providing server 90 will be described. FIG. 39 is a diagram showing an example of a hardware configuration of an information processing device that constitutes each of these devices.

[0377] The hardware configuration shown in FIG. 39 will be described. A CPU (Central Processing Unit) 201 functions as a data processing unit that executes various processes according to a program stored in a ROM (Read Only Memory) 202 or a storage unit 208. For example, the CPU executes processes according to the sequences described in the above-mentioned embodiments. A RAM (Random Access Memory) 203 stores programs and data executed by the CPU 201. The CPU 201, ROM 202, and RAM 203 are connected to one another via a bus 204.

[0378] The CPU 201 is connected to an input / output interface 205 via a bus 204, and the input / output interface 205 is connected to an input unit 206 consisting of various switches, a keyboard, a touch panel, a mouse, a microphone, and further a situation data acquisition unit such as a sensor, and an output unit 207 consisting of a display, a speaker, etc.

[0379] The CPU 201 receives commands, status data, and the like from an input unit 206, executes various processes, and outputs the results of the processes to an output unit 207, for example. The storage unit 208 connected to the input / output interface 205 is formed of, for example, a hard disk, and stores various data and programs executed by the CPU 201. The communication unit 209 functions as a transmission / reception unit for data communication via a network such as the Internet or a local area network, and communicates with external devices.

[0380] A drive 210 connected to the input / output interface 205 drives removable media 211, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory such as a memory card, and executes recording or reading of data.

[0381] [9. Summary of the Configuration of the Present Disclosure] The embodiments of the present disclosure have been described in detail above with reference to specific embodiments. However, it is obvious that a person skilled in the art can modify or substitute the embodiments without departing from the gist of the present disclosure. In other words, the present invention has been disclosed in the form of an example, and should not be interpreted as being limited. In order to judge the gist of the present disclosure, the claims should be taken into consideration.

[0382] The technology disclosed in this specification can have the following configurations. (1) an exercise type estimation unit that estimates an exercise type performed by a user based on sensor detection information; A database storing the user's unique exercise intensity corresponding to the type of exercise; an exercise type / individual exercise intensity acquisition unit that acquires, from the database, an exercise type / individual exercise intensity that is specific to the user and corresponds to the exercise type estimated by the exercise type estimation unit; An information processing device having an exercise implementation status analysis unit that analyzes exercise implementation status data generated based on the exercise type and individual exercise intensity obtained from the database, and generates an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with a previously generated exercise prescription.

[0383] (2) The database is: a user-specific exercise intensity database corresponding to an exercise type, the database storing the user-specific exercise intensity corresponding to the exercise type; The exercise implementation status analysis unit The information processing device described in (1) analyzes exercise implementation status data generated based on the exercise type and individual corresponding exercise intensity obtained from the exercise type corresponding user specific exercise intensity database, and generates an exercise implementation status analysis result indicating whether the exercise performed by the user is in accordance with a previously generated exercise prescription.

[0384] (3) The exercise type-specific user-specific exercise intensity database includes: The information processing device according to (2), which is a database storing exercise intensity obtained by analyzing breath analysis result data obtained by having the user wear an exhaled gas analyzer and exercise.

[0385] (4) The user: A user who performs rehabilitation exercise according to a previously generated exercise prescription; The exercise implementation status analysis unit Exercise implementation status data generated based on the exercise type and individual corresponding exercise intensity; An information processing device according to any one of (1) to (3), which compares stored data in an exercise prescription information database that stores the previously generated exercise prescription, and generates an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with the exercise prescription.

[0386] (5) The information processing device comprises: an exercise implementation status record database storing the exercise implementation status data; The exercise implementation status analysis unit The information processing device described in (4) obtains exercise implementation status data of the user from the exercise implementation status record database, and generates an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with an exercise prescription.

[0387] (6) The information processing device, The exercise type and the individual exercise intensity acquired by the exercise type and individual exercise intensity acquisition unit are input, A maximum oxygen intake rate calculation unit for calculating a maximum oxygen intake rate corresponding to a type of exercise performed by the user; an exercise time integration unit that generates, as exercise implementation status data, an exercise time integration result of an exercise corresponding to each of the maximum value corresponding oxygen intake rates calculated by the maximum value corresponding oxygen intake rate calculation unit; The exercise implementation status analysis unit An information processing device described in any of (1) to (5), which generates an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with an exercise prescription based on the exercise implementation status data generated by the exercise time accumulation unit.

[0388] (7) The exercise intensity is The information processing device according to any one of (1) to (6), wherein the information processing device is a METs (Metabolic equivalents).

[0389] (8) The database comprises: The information processing device according to (7), which is a database storing user-specific METs, which is exercise intensity corresponding to the user-specific type of exercise.

[0390] (9) The user-specific METs, which is the exercise intensity corresponding to the user-specific exercise type, is The information processing device according to (8), wherein the data is breath analysis result data obtained by having the user wear an exhaled gas analyzer and perform exercise, and METs calculated taking into account the user's body weight.

[0391] (10) The exercise implementation status analysis unit The information processing device according to any one of (1) to (9), further comprising: a display unit configured to output an exercise implementation status analysis result indicating whether or not the exercise being performed by the user is in accordance with a previously generated exercise prescription.

[0392] (11) An exercise type estimation unit that estimates an exercise type performed by a user based on sensor detection information; a steady-state activity amount analysis unit that inputs the estimated type of exercise estimated by the exercise type estimation unit and the user's breath gas analysis result to calculate the exercise type and individual corresponding activity amount based on the breath analysis result; an exercise-intensity-based exercise-type / individual-corresponding activity amount calculation unit that acquires a standard exercise intensity corresponding to the exercise type estimated by the exercise-type estimation unit from an exercise-type-based standard exercise intensity database that stores standard exercise intensities corresponding to the exercise types, and calculates an exercise-intensity-based exercise type / individual-corresponding activity amount based on the acquired standard exercise intensity and the user's body weight; (a) the type of exercise and the amount of individual activity based on the breath analysis results; (b) the exercise type and individual activity amount based on the exercise intensity; The information processing device has an exercise type / individual exercise intensity calculation unit that calculates an exercise type / individual exercise intensity, which is an exercise intensity corresponding to the user's exercise type, based on the above data (a) and (b).

[0393] (12) The information processing device further comprises: (a) the type of exercise and the amount of individual activity based on the breath analysis results; (b) the exercise type and individual activity amount based on the exercise intensity; a personal exercise intensity correction coefficient calculation unit that inputs the above data (a) and (b) and calculates a personal exercise intensity correction coefficient corresponding to the user; The exercise type and individual exercise intensity calculation unit The information processing device according to (11), further comprising: calculating an exercise type and an individual exercise intensity, which are the exercise intensity corresponding to the user, using the individual exercise intensity correction coefficient.

[0394] (13) The exercise type and individual exercise intensity calculation unit The information processing device according to (12), further comprising: calculating the type of exercise and the individual-compatible exercise intensity by utilizing weight information of the user.

[0395] (14) The exercise type and individual exercise intensity calculation unit The information processing device according to any one of (11) to (13), wherein the calculated exercise type / individual corresponding exercise intensity is recorded in an exercise type-user specific exercise intensity database.

[0396] (15) An information processing system having a user terminal and a hospital terminal, The user terminal, an exercise type estimation unit that estimates an exercise type performed by a user based on sensor detection information; A database storing the user's unique exercise intensity corresponding to the type of exercise; an exercise type / individual exercise intensity acquisition unit that acquires, from the database, an exercise type / individual exercise intensity that is specific to the user and corresponds to the exercise type estimated by the exercise type estimation unit; a communication unit that transmits exercise implementation status data generated based on the exercise type and individual exercise intensity obtained from the database to the hospital terminal; The hospital terminal includes: an exercise implementation status analysis unit that analyzes the exercise implementation status data received from the user terminal and generates an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with a previously generated exercise prescription; a communication unit that transmits the exercise implementation status analysis result generated by the exercise implementation status analysis unit to the user terminal; The user terminal, An information processing system that displays the exercise implementation status analysis result received from the hospital terminal on a display unit.

[0397] (16) An information processing system having a user terminal and a geographic information providing server, The user terminal, an exercise type estimation unit that estimates an exercise type performed by a user based on sensor detection information; A database storing the user's unique exercise intensity corresponding to the type of exercise; an exercise type / individual exercise intensity acquisition unit that acquires, from the database, an exercise type / individual exercise intensity that is specific to the user and corresponds to the exercise type estimated by the exercise type estimation unit; a peak oxygen intake rate calculation unit that inputs the exercise type and individual exercise intensity acquired by the exercise type and individual exercise intensity acquisition unit and calculates a peak oxygen intake rate corresponding to the exercise type performed by the user; a communication unit that generates exercise prescription information for realizing the maximum value corresponding oxygen intake rate based on the maximum value corresponding oxygen intake rate calculated by the maximum value corresponding oxygen intake rate calculation unit, and transmits the generated exercise prescription information to the geographic information providing server; The geographic information providing server includes: an exercise prescription corresponding action route information generating unit that analyzes the exercise prescription information received from the user terminal and generates exercise prescription corresponding action route information for implementing the exercise prescription information; A communication unit that transmits the exercise prescription corresponding action route information to the user terminal, The user terminal, An information processing system that displays the exercise prescription corresponding action route information received from the geographic information providing server on a display unit.

[0398] (17) An information processing method executed in an information processing device, an exercise type estimating step in which an exercise type estimating unit estimates an exercise type performed by a user based on sensor detection information; an exercise type / individual exercise intensity acquisition step in which an exercise type / individual exercise intensity acquisition unit acquires, from a database, an exercise type / individual exercise intensity that is an exercise intensity specific to the user corresponding to the exercise type estimated by the exercise type estimation unit; An information processing method that executes an exercise implementation status analysis step in which an exercise implementation status analysis unit analyzes exercise implementation status data generated based on the exercise type and individual-specific exercise intensity obtained from the database, and generates an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with a previously generated exercise prescription.

[0399] (18) An information processing method executed in an information processing device, an exercise type estimating step in which an exercise type estimating unit estimates an exercise type performed by a user based on sensor detection information; A steady-state activity amount analysis step in which a steady-state activity amount analysis unit inputs the estimated type of exercise estimated by the exercise type estimation unit and the user's exhaled gas analysis result to calculate an exercise type and individual corresponding activity amount based on the exhaled gas analysis result; an exercise-intensity-based exercise-type / individual-corresponding activity amount calculation step in which an exercise-intensity-based exercise-type / individual-corresponding activity amount calculation unit acquires a standard exercise intensity corresponding to the exercise type estimated by the exercise-type estimation unit from an exercise-type-corresponding standard exercise intensity database storing standard exercise intensities corresponding to exercise types, and calculates an exercise-intensity-based exercise type / individual-corresponding activity amount based on the acquired standard exercise intensity and the user's body weight; The exercise type and individual exercise intensity calculation section (a) the type of exercise and the amount of individual activity based on the breath analysis results; (b) the exercise type and individual activity amount based on the exercise intensity; The information processing method includes a step of calculating an exercise type and individual exercise intensity, which is an exercise intensity corresponding to the user's exercise type, based on the data (a) and (b).

[0400] (19) A program for causing an information processing device to execute information processing, an exercise type estimating step of causing an exercise type estimating unit to estimate an exercise type performed by a user based on sensor detection information; an exercise type / individual exercise intensity acquisition step of causing an exercise type / individual exercise intensity acquisition unit to acquire, from a database, an exercise type / individual exercise intensity that is an exercise intensity specific to the user corresponding to the exercise type estimated by the exercise type estimation unit; A program that causes an exercise implementation status analysis unit to execute an exercise implementation status analysis step of analyzing exercise implementation status data generated based on the exercise type and individual-specific exercise intensity obtained from the database, and generating an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with a previously generated exercise prescription.

[0401] (20) A program for causing an information processing device to execute information processing, an exercise type estimating step of causing an exercise type estimating unit to estimate an exercise type performed by a user based on sensor detection information; a steady-state activity amount analysis step of inputting the estimated type of exercise estimated by the exercise type estimation unit and the result of the breath gas analysis of the user to a steady-state activity amount analysis unit to calculate the type of exercise and the individual activity amount based on the breath analysis result; an exercise-intensity-based exercise type / individual-corresponding activity amount calculation step of causing an exercise-intensity-based exercise type / individual-corresponding activity amount calculation unit to acquire a standard exercise intensity corresponding to the exercise type estimated by the exercise type estimation unit from an exercise type-corresponding standard exercise intensity database storing standard exercise intensities corresponding to exercise types, and to calculate an exercise-intensity-based exercise type / individual-corresponding activity amount based on the acquired standard exercise intensity and the user's body weight; Exercise type and individual exercise intensity calculation section (a) the type of exercise and the amount of individual activity based on the breath analysis results; (b) the exercise type and individual activity amount based on the exercise intensity; A program for executing an exercise type / individual exercise intensity calculation step for calculating an exercise type / individual exercise intensity, which is an exercise intensity for the user corresponding to the exercise type, based on each of the data (a) and (b) above.

[0402] The series of processes described in the specification can be executed by hardware, software, or a combination of both. When executing processes by software, a program recording the processing sequence can be installed and executed in a memory in a computer built into dedicated hardware, or the program can be installed and executed in a general-purpose computer capable of executing various processes. For example, the program can be pre-recorded on a recording medium. In addition to installing the program from the recording medium to the computer, the program can be received via a network such as a LAN (Local Area Network) or the Internet, and installed on a recording medium such as a built-in hard disk.

[0403] In addition, the various processes described in the specification may not only be executed in chronological order as described, but may also be executed in parallel or individually depending on the processing capabilities of the devices executing the processes or as necessary. In addition, in this specification, a system refers to a logical collective configuration of multiple devices, and is not limited to devices in the same housing. [Industrial Applicability]

[0404] As described above, according to the configuration of one embodiment of the present disclosure, a configuration is realized that enables a user performing rehabilitation to appropriately perform rehabilitation while checking whether the exercise he or she is performing is appropriate in accordance with an exercise prescription. Specifically, for example, the device includes an exercise type estimation unit that estimates the type of exercise performed by a user based on detection information from a sensor worn by the user on the body, a database that stores user-specific exercise intensities corresponding to the types of exercise, an exercise type / individual-adapted exercise intensity acquisition unit that acquires from the database the exercise type / individual-adapted exercise intensity, which is the user-specific exercise intensity corresponding to the type of exercise estimated by the exercise type estimation unit, and an exercise implementation status analysis unit that analyzes exercise implementation status data generated based on the exercise type / individual-adapted exercise intensity acquired from the database and generates an exercise implementation status analysis result indicating whether the exercise performed by the user is in accordance with a previously generated exercise prescription, and outputs the generated exercise implementation status analysis result to a display unit. This configuration realizes a configuration that enables a rehabilitation performing user to appropriately perform rehabilitation while checking whether the exercise he or she is performing is appropriate exercise in accordance with an exercise prescription. [Explanation of symbols]

[0405] 11 users 12 Sensors 20. Breath gas analyzer 21 Activity data acquisition department 30 User terminal 31 Sensor detection value input section 32 Movement type estimation section 33 Steady-state activity analysis section Standard exercise intensity database for 34 types of exercise 35 Personal Information Database 36 Exercise type and individual exercise intensity acquisition section 37 Exercise intensity-based exercise type and individual activity amount calculation section 38 Individual exercise intensity correction coefficient calculation section 39 Exercise type and individual exercise intensity calculation section 40 exercise types User specific exercise intensity database 51 Exercise type and individual exercise intensity acquisition section 52 Maximum oxygen intake rate calculation section 53 Exercise time calculation unit 54 Exercise implementation status record database 55 Exercise prescription information database 56 Exercise implementation status analysis section 57 Display section 61 Communications Department 62 Pulse rate upper limit asymptotic determination section 63 Heart rate upper limit asymptotic determination section 64 Exercise Prescription Information Database 65 Instruction information generation unit 66 Output section (display section) 70 Hospital terminal 71 Communications Department 72 Exercise implementation status analysis section 75 Exercise implementation status record database 76 Exercise Prescription Information Database 77 Exercise Calligraphy Update Department 78 Exercise prescription operation UI 81 Sensor detection value input section 82 Movement type estimation section 83 Exercise type and individual exercise intensity acquisition section 84 Maximum oxygen intake rate calculation section 85 Exercise Prescription Information Database 86 Exercise prescription corresponding action route search section 87 Communications Department 90 Geographical information server 91 Communications Department 92 Exercise prescription corresponding action route information generation unit 201 CPU 202 ROM 203 RAM 204 Bus 205 Input / Output Interface 206 Input section 207 Output section 208 Storage section 209 Communications Department 210 Drive 211 Removable Media

Claims

1. an exercise type estimation unit that estimates an exercise type performed by a user based on sensor detection information; A database storing the user's unique exercise intensity corresponding to the type of exercise; an exercise type / individual exercise intensity acquisition unit that acquires, from the database, an exercise type / individual exercise intensity that is an exercise intensity specific to the user corresponding to the exercise type estimated by the exercise type estimation unit; an exercise implementation status analysis unit that analyzes exercise implementation status data generated based on the type of exercise and individual-specific exercise intensity acquired from the database, and generates an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with a previously generated exercise prescription; The exercise type and individual exercise intensity stored in the database are: (a) an estimated type of exercise estimated by the exercise type estimation unit and an exhaled breath analysis result-based exercise type and individual activity amount calculated based on an exhaled breath gas analysis result of the user; and (b) an exercise type / individual corresponding activity amount based on exercise intensity calculated based on a standard exercise intensity corresponding to the exercise type and the user's body weight; An information processing device that calculates an exercise type and an exercise intensity corresponding to the user using an individual exercise intensity correction coefficient corresponding to the user calculated using each of the data (a) and (b) above.

2. The database includes: a user-specific exercise intensity database corresponding to an exercise type, the database storing the user-specific exercise intensity corresponding to the exercise type; The exercise implementation status analysis unit 2. The information processing device according to claim 1, further comprising: an information processing device that analyzes exercise implementation status data generated based on the exercise type and individual exercise intensity obtained from the exercise type-specific user-specific exercise intensity database; and generates an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with a previously generated exercise prescription.

3. The exercise type-specific user-specific exercise intensity database includes:

3. The information processing device according to claim 2, wherein the database stores exercise intensity obtained by analyzing breath analysis result data obtained by having the user wear an exhaled gas analyzer and exercise.

4. The user: A user who performs rehabilitation exercise according to a previously generated exercise prescription; The exercise implementation status analysis unit Exercise implementation status data generated based on the exercise type and individual exercise intensity; 2. The information processing device according to claim 1, wherein the information processing device compares the stored data in an exercise prescription information database that stores the previously generated exercise prescription, and generates an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with the exercise prescription.

5. The information processing device includes: an exercise implementation status record database storing the exercise implementation status data; The exercise implementation status analysis unit The information processing device according to claim 4 , wherein the information processing device acquires exercise implementation status data of the user from the exercise implementation status record database, and generates an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with an exercise prescription.

6. The information processing device includes: inputting the type of exercise and the individual-adapted exercise intensity acquired by the type of exercise and individual-adapted exercise intensity acquisition unit; A maximum oxygen intake rate calculation unit for calculating a maximum oxygen intake rate according to a type of exercise performed by the user; an exercise time integration unit that generates, as exercise implementation status data, an exercise time integration result of an exercise corresponding to each of the maximum value corresponding oxygen intake rates calculated by the maximum value corresponding oxygen intake rate calculation unit; The exercise implementation status analysis unit The information processing device according to claim 1 , further comprising: a step of generating an exercise implementation status analysis result indicating whether or not the exercise being performed by the user is in accordance with an exercise prescription, based on the exercise implementation status data generated by the exercise time integrating unit.

7. The exercise intensity is The information processing device according to claim 1 , which is a METs (Metabolic equivalents).

8. The database includes: The information processing device according to claim 7 , further comprising a database storing user-specific METs, which are exercise intensities corresponding to the user-specific types of exercise.

9. The user-specific METs, which is the exercise intensity corresponding to the user-specific exercise type, is 9. The information processing device according to claim 8, wherein the METs is calculated taking into consideration breath analysis result data obtained by having the user wear an exhaled gas analyzer and perform exercise, and a body weight of the user.

10. The exercise implementation status analysis unit The information processing device according to claim 1 , further comprising: a display unit configured to output an exercise implementation status analysis result indicating whether or not the exercise being performed by the user is in accordance with a previously generated exercise prescription.

11. an exercise type estimation unit that estimates an exercise type performed by a user based on sensor detection information; a steady-state activity amount analysis unit that inputs the estimated type of exercise estimated by the exercise type estimation unit and the result of the breath gas analysis of the user to calculate an exercise type and an individual-corresponding activity amount based on the breath analysis result; an exercise-intensity-based exercise-type / individual-corresponding activity amount calculation unit that acquires a standard exercise intensity corresponding to the exercise type estimated by the exercise-type estimation unit from an exercise-type-corresponding standard exercise intensity database that stores standard exercise intensities corresponding to the exercise types, and calculates an exercise-intensity-based exercise type / individual-corresponding activity amount based on the acquired standard exercise intensity and the user's body weight; (a) the type of exercise and the amount of individual activity based on the breath analysis result; (b) the exercise type and individual activity amount based on the exercise intensity; an individual-adjusted exercise intensity correction coefficient calculation unit that inputs the above-mentioned (a) and (b) and calculates an individual-adjusted exercise intensity correction coefficient corresponding to the user; An information processing device having an exercise type / individual exercise intensity calculation unit that calculates an exercise type / individual exercise intensity, which is an exercise intensity corresponding to the user corresponding to an exercise type, using the individual exercise intensity correction coefficient.

12. The exercise type and individual exercise intensity calculation unit The information processing device according to claim 11 , wherein the exercise type and individual exercise intensity are calculated by utilizing weight information of the user.

13. The exercise type and individual exercise intensity calculation unit The information processing device according to claim 11 , wherein the calculated exercise type / individual corresponding exercise intensity is recorded in a user-specific exercise intensity corresponding to exercise type database.

14. An information processing system having a user terminal and a hospital terminal, The user terminal, an exercise type estimation unit that estimates an exercise type performed by a user based on sensor detection information; A database storing the user's unique exercise intensity corresponding to the type of exercise; an exercise type / individual exercise intensity acquisition unit that acquires, from the database, an exercise type / individual exercise intensity that is an exercise intensity specific to the user corresponding to the exercise type estimated by the exercise type estimation unit; a communication unit that transmits exercise implementation status data generated based on the exercise type and individual exercise intensity acquired from the database to the hospital terminal; The exercise type and individual exercise intensity stored in the database are: (a) an estimated type of exercise estimated by the exercise type estimation unit and an exhaled breath analysis result-based exercise type and individual activity amount calculated based on an exhaled breath gas analysis result of the user; and (b) an exercise type / individual corresponding activity amount based on exercise intensity calculated based on a standard exercise intensity corresponding to the exercise type and the user's body weight; the type of exercise and the exercise intensity corresponding to the user are calculated using the individual exercise intensity correction coefficient corresponding to the user calculated using each of the data (a) and (b); The hospital terminal includes: an exercise implementation status analysis unit that analyzes the exercise implementation status data received from the user terminal and generates an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with a previously generated exercise prescription; a communication unit that transmits the exercise implementation status analysis result generated by the exercise implementation status analysis unit to the user terminal; The user terminal, An information processing system that displays the exercise implementation status analysis result received from the hospital terminal on a display unit.

15. An information processing system having a user terminal and a geographic information providing server, The user terminal, an exercise type estimation unit that estimates an exercise type performed by a user based on sensor detection information; A database storing the user's unique exercise intensity corresponding to the type of exercise; an exercise type / individual exercise intensity acquisition unit that acquires, from the database, an exercise type / individual exercise intensity that is an exercise intensity specific to the user corresponding to the exercise type estimated by the exercise type estimation unit; a maximum oxygen intake rate calculation unit that inputs the type of exercise and the individual exercise intensity acquired by the exercise type / individual exercise intensity acquisition unit and calculates a maximum oxygen intake rate corresponding to the type of exercise performed by the user; a communication unit that generates exercise prescription information for realizing the maximum value corresponding oxygen intake rate based on the maximum value corresponding oxygen intake rate calculated by the maximum value corresponding oxygen intake rate calculation unit, and transmits the generated exercise prescription information to the geographic information providing server; The geographic information providing server includes: an exercise prescription corresponding action route information generating unit that analyzes the exercise prescription information received from the user terminal and generates exercise prescription corresponding action route information for implementing the exercise prescription information; A communication unit that transmits the exercise prescription corresponding action route information to the user terminal, The user terminal, An information processing system that displays the exercise prescription corresponding action route information received from the geographic information providing server on a display unit.

16. An information processing method executed in an information processing device, an exercise type estimating step in which an exercise type estimating unit estimates an exercise type performed by a user based on sensor detection information; an exercise type / individual exercise intensity acquisition step in which an exercise type / individual exercise intensity acquisition unit acquires, from a database, an exercise type / individual exercise intensity that is an exercise intensity specific to the user corresponding to the exercise type estimated by the exercise type estimation unit; an exercise implementation status analysis unit executes an exercise implementation status analysis step of analyzing exercise implementation status data generated based on the exercise type and individual-specific exercise intensity acquired from the database, and generating an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with a previously generated exercise prescription; The exercise type and individual exercise intensity stored in the database are: (a) an estimated type of exercise estimated by the exercise type estimation unit and an exhaled breath analysis result-based exercise type and individual activity amount calculated based on an exhaled breath gas analysis result of the user; and (b) an exercise type / individual corresponding activity amount based on exercise intensity calculated based on a standard exercise intensity corresponding to the exercise type and the user's body weight; An information processing method in which the type of exercise and the exercise intensity corresponding to the user are calculated using an individual exercise intensity correction coefficient corresponding to the user calculated using each of the data (a) and (b) above.

17. An information processing method executed in an information processing device, an exercise type estimating step in which an exercise type estimating unit estimates an exercise type performed by a user based on sensor detection information; a steady-state activity amount analysis step in which a steady-state activity amount analysis unit inputs the estimated type of exercise estimated by the exercise type estimation unit and the result of the breath gas analysis of the user, and calculates an exercise type and an individual-corresponding activity amount based on the breath analysis result; an exercise-intensity-based exercise-type / individual-adapted activity amount calculation step in which an exercise-intensity-based exercise-type / individual-adapted activity amount calculation unit acquires a standard exercise intensity corresponding to the exercise type estimated by the exercise-type estimation unit from an exercise-type-based standard exercise intensity database storing standard exercise intensities corresponding to the exercise types, and calculates an exercise-intensity-based exercise type / individual-adapted activity amount based on the acquired standard exercise intensity and the user's body weight; The exercise type and individual exercise intensity calculation unit (a) the type of exercise and the amount of individual activity based on the breath analysis result; (b) the exercise type and individual activity amount based on the exercise intensity; an individual-adjusted exercise intensity correction coefficient calculation unit that inputs the above-mentioned (a) and (b) and calculates an individual-adjusted exercise intensity correction coefficient corresponding to the user; The information processing method includes a calculation step of calculating an exercise type and individual adapted exercise intensity, which is an exercise intensity adapted to the user corresponding to an exercise type, using the individual adapted exercise intensity correction coefficient.

18. A program for causing an information processing device to execute information processing, an exercise type estimating step of causing an exercise type estimating unit to estimate an exercise type performed by a user based on sensor detection information; an exercise type / individual exercise intensity acquisition step of causing an exercise type / individual exercise intensity acquisition unit to acquire, from a database, an exercise type / individual exercise intensity that is an exercise intensity specific to the user corresponding to the exercise type estimated by the exercise type estimation unit; execute an exercise implementation status analysis step in which the exercise implementation status analysis unit analyzes exercise implementation status data generated based on the exercise type and individual-specific exercise intensity acquired from the database, and generates an exercise implementation status analysis result indicating whether the exercise being performed by the user is in accordance with a previously generated exercise prescription; The exercise type and individual exercise intensity stored in the database are: (a) an estimated type of exercise estimated by the exercise type estimation unit and an exhaled breath analysis result-based exercise type and individual activity amount calculated based on an exhaled breath gas analysis result of the user; and (b) an exercise type / individual corresponding activity amount based on exercise intensity calculated based on a standard exercise intensity corresponding to the exercise type and the user's body weight; A program in which an exercise type and an exercise intensity corresponding to the user are calculated using an individual exercise intensity correction coefficient corresponding to the user calculated using each of the data (a) and (b) above.

19. A program for causing an information processing device to execute information processing, an exercise type estimating step of causing an exercise type estimating unit to estimate an exercise type performed by a user based on sensor detection information; a steady-state activity amount analysis step of inputting the estimated type of exercise estimated by the exercise type estimation unit and the result of the breath gas analysis of the user to a steady-state activity amount analysis unit to calculate an exercise type and an individual-corresponding activity amount based on the breath analysis result; an exercise-intensity-based exercise type / individual-adapted activity amount calculation step of causing an exercise-intensity-based exercise type / individual-adapted activity amount calculation unit to acquire a standard exercise intensity corresponding to the exercise type estimated by the exercise type estimation unit from an exercise type-based standard exercise intensity database storing standard exercise intensities corresponding to exercise types, and to calculate an exercise-intensity-based exercise type / individual-adapted activity amount based on the acquired standard exercise intensity and the user's body weight; The exercise type and individual exercise intensity calculation section (a) the type of exercise and the amount of individual activity based on the breath analysis result; (b) the exercise type and individual activity amount based on the exercise intensity; an individual-adjusted exercise intensity correction coefficient calculation unit that inputs the above-mentioned (a) and (b) and calculates an individual-adjusted exercise intensity correction coefficient corresponding to the user; A program for executing an exercise type / individual exercise intensity calculation step for calculating an exercise type / individual exercise intensity, which is the user-adapted exercise intensity corresponding to the exercise type, using the individual exercise intensity correction coefficient.

Images