JP7209199B2 - MUSCLE STRENGTH MANAGEMENT SYSTEM AND MUSCLE STRENGTH MANAGEMENT METHOD - Google Patents

Description

The present invention relates to a muscle strength management system and a muscle strength management method.

For example, Patent Literature 1 discloses a life management system that analyzes a user's mental and physical conditions so that the user's goals can be achieved.

JP-A-2005-74107

It is expected that the user will perform appropriate exercise for the purpose of preventing sarcopenia and efficiently increasing or maintaining muscle strength. However, the conventional life management system cannot efficiently assist the user in building or maintaining muscle strength.

SUMMARY OF THE INVENTION Accordingly, an object of the present invention is to provide a muscle strength management system and a muscle strength management method that can efficiently assist a user in building or maintaining muscle strength.

In order to achieve the above object, a muscle strength management system according to an aspect of the present invention includes a measurement unit that measures a feature amount of physical ability of a user; an analysis unit that evaluates physical ability and determines recommended content including exercise content recommended to the user based on the result of the evaluation; and a presentation unit that presents the recommended content determined by the analysis unit to the user. and

In addition, a muscle strength management method according to an aspect of the present invention includes steps of measuring a feature amount of a user's physical ability, evaluating the physical ability of the user by analyzing the detected feature amount, and performing the evaluation. Based on the results, the step of determining recommended content including exercise content recommended to the user, and the step of presenting the determined recommended content to the user.

Further, one aspect of the present invention can be implemented as a program that causes a computer to execute the muscle strength management method. Alternatively, it can be implemented as a computer-readable non-temporary recording medium storing the program.

ADVANTAGE OF THE INVENTION According to this invention, the reinforcement|strengthening or maintenance of a user's muscular strength can be assisted efficiently.

FIG. 1 is a diagram showing an outline of a muscle strength management system according to an embodiment. FIG. 2 is a block diagram showing the functional configuration of the muscle strength management system according to the embodiment. FIG. 3 is a flow chart showing the operation of the muscle strength management system according to the embodiment. FIG. 4 is a diagram showing a physical ability estimation table stored by the muscle strength management system according to the embodiment. FIG. 5 is a diagram showing an exercise recommendation table generated by the muscle strength management system according to the embodiment. FIG. 6 is a diagram showing an example of a target value input screen by a user displayed by the muscle strength management system according to the embodiment. FIG. 7 is a diagram showing the relationship between physical conditions and exercise intensity. FIG. 8 is a diagram showing a meal recommendation table generated by the muscle strength management system according to the embodiment. FIG. 9 is a diagram showing an example of recommended exercise contents for a user displayed by the muscle strength management system according to the embodiment. FIG. 10 is a diagram showing an example of exercise content recommended to the user and future prediction displayed by the muscle strength management system according to the embodiment. FIG. 11 is a diagram showing an example of exercise content recommended to a user and advertisement information displayed by the muscle strength management system according to the embodiment. FIG. 12 is a diagram showing an example of meal content recommended to a user and advertisement information displayed by the muscle strength management system according to the embodiment. FIG. 13 is a diagram showing order history information stored by the muscle strength management system according to the embodiment. FIG. 14 is a diagram showing an example of a provider database managed by the muscle strength management system according to the embodiment.

Hereinafter, a muscle strength management system and a muscle strength management method according to embodiments of the present invention will be described in detail with reference to the drawings. It should be noted that each of the embodiments described below is a specific example of the present invention. Therefore, the numerical values, shapes, materials, components, arrangement and connection of components, steps, order of steps, etc. shown in the following embodiments are examples and are not intended to limit the present invention. Therefore, among the constituent elements in the following embodiments, constituent elements not described in independent claims will be described as optional constituent elements.

Each figure is a schematic diagram and is not necessarily strictly illustrated. Therefore, for example, scales and the like do not necessarily match in each drawing. Moreover, in each figure, the same code|symbol is attached|subjected about the substantially same structure, and the overlapping description is abbreviate|omitted or simplified.

(Embodiment)
[overview]
First, an overview of a muscle strength management system according to an embodiment will be described with reference to FIG. FIG. 1 is a diagram showing an outline of a muscle strength management system 1 according to this embodiment.

The muscle strength management system 1 shown in FIG. 1 measures the feature amount of the physical ability of the user 10 and analyzes the measured feature amount to evaluate the physical ability of the user 10 . The feature amount of physical ability is, for example, at least one of muscle strength, muscle mass, walking speed, and walking balance. Also, the feature amount of physical ability may include cognitive function. Further, the muscle strength management system 1 determines recommended content based on the evaluation results, and presents the determined recommended content to the user 10 . The recommended content includes exercise content and meal content recommended for the user 10 .

Further, in the muscle strength management system 1 according to the present embodiment, the vital data of the user 10 is measured in addition to the feature amount of physical ability. The vital data is, for example, at least one of the user's 10 weight, blood pressure, pulse, urine pH, and urine sugar. The vital data may include the body fat percentage of the user 10 and the like.

The measurement of the feature amount and the vital data is performed while the user 10 leads a normal life, for example, using the camera 12 and the toilet 13 provided in the user's 10 residence 11 . In other words, the feature amount and vital data relating to the physical ability of the user 10 are measured without the user 10 being particularly conscious of it. Note that the user 10 may consciously measure the feature quantity and vital data using a weight scale, blood pressure monitor, or the like.

The measured feature amount and vital data are transmitted to the server device 30 via a network such as a LAN (Local Area Network) or the Internet. The server device 30 evaluates the physical ability of the user 10 by analyzing the feature amount and vital data, and determines recommended content based on the evaluation result.

The determined recommended content is transmitted to the terminal device 40 or the like carried by the user 10 via the network. The terminal device 40 presents the recommended content to the user 10 in the form of an image or sound. Accordingly, it is possible to propose to the user 10 appropriate exercise content and appropriate meal content for the user 10 in order to increase or maintain muscle strength. In this manner, the muscle strength management system 1 according to the present embodiment can efficiently assist the user 10 in increasing or maintaining the muscle strength.

[Constitution]
A specific configuration of the muscle strength management system 1 according to the present embodiment will be described below with reference to FIG. 2 . FIG. 2 is a block diagram showing the functional configuration of the muscle strength management system 1 according to this embodiment.

As shown in FIG. 2 , muscle strength management system 1 includes measuring device 20 , server device 30 , and terminal device 40 . The measuring device 20, the server device 30, and the terminal device 40 are connected so as to be able to communicate with each other via the Internet or the like.

[Measuring device]
The measuring device 20 is a device that measures the feature quantity of the physical ability of the user 10 . The measuring device 20 is implemented by, for example, a microcomputer and various sensor devices, and installed in the residence 11 of the user 10 . As shown in FIG. 2 , the measurement device 20 includes a communication section 21 , a storage section 22 and a measurement section 23 .

The communication unit 21 is realized by one or more communication interfaces for wireless communication or wired communication. Wireless communication is, for example, communication based on communication standards such as Wi-Fi (registered trademark), Bluetooth (registered trademark), or ZigBee (registered trademark), but is not limited to these.

The communication unit 21 transmits and receives information and signals by communicating with each of the server device 30 and the terminal device 40 . For example, the communication unit 21 transmits to the server device 30 the feature amount of the physical ability of the user 10 and the vital data obtained by the measurement by the measurement unit 23 .

The storage unit 22 is a semiconductor memory such as a flash memory or a non-volatile storage device such as a HDD (Hard Disk Drive). The storage unit 22 stores time-series data of feature amounts measured by the measurement unit 23 . The storage unit 22 also stores time-series data of vital data measured by the measurement unit 23 . The storage unit 22 further stores an exercise history of the user 10 generated based on the amount of activity measured by the measurement unit 23 . The storage unit 22 may store the evaluation results and recommended content transmitted from the server device 30 .

The measurement unit 23 measures the feature amount of the physical ability of the user 10 . The measurement unit 23 also measures the vital data and activity amount of the user 10 . As shown in FIG. 2 , the measuring section 23 includes a detecting section 24 , a vital measuring section 25 , an estimating section 26 and an activity measuring section 27 .

The detection unit 24 detects actions of the user 10 . Specifically, the detection unit 24 includes an imaging unit 24a and an acceleration sensor 24b. Note that the detection unit 24 does not have to include at least one of the imaging unit 24a and the acceleration sensor 24b.

The imaging unit 24a is realized by the camera 12 shown in FIG. 1, for example. The imaging unit 24a generates a moving image by photographing the user 10. FIG. Specifically, the imaging unit 24a captures the walking motion of the user 10 . For example, as shown in FIG. 1, the camera 12 is installed at the entrance of the residence 11 and photographs the user 10 who enters and exits the residence 11 . Alternatively, the camera 12 may be installed in a hallway, stairs, room, or the like within the dwelling 11 . The moving image captured by the camera 12 (image capturing unit 24a) includes the walking motion of the user 10 .

The acceleration sensor 24b is carried by the user 10 and detects acceleration according to the movement of the user 10. FIG. For example, the acceleration sensor 24b is attached to a body part such as the arm, waist, leg, neck, or head of the user 10 . For example, the acceleration sensor 24b is fixed to a fixture attached to a part of the user's 10 body. The attachment is, for example, a wristband or belt. The acceleration sensor 24b is fixed to the body part of the user 10 by attaching the fixture to the body part. The number of acceleration sensors 24b attached to the user 10 is not limited to one, and may be plural. The acceleration sensor 24b detects the movement of the attached part and generates three-dimensional acceleration data. The three-dimensional acceleration data indicates, for example, the acceleration of the user 10 in the front-rear direction, the up-down direction, and the left-right direction.

The vital measurement unit 25 measures the vital data of the user 10 . For example, the vital measurement unit 25 is realized by at least one of a weight scale, a body fat scale, a sphygmomanometer, a pulse monitor, a urinalysis analyzer, and the like. The weight scale and the body fat scale are embedded in the floor in front of the washbasin of the residence 11, for example, and measure the weight, body fat percentage, and the like of the user 10 who gets on the scale. This makes it possible to measure the weight of the user 10 without making the user 10 aware of it when the user 10 is grooming himself or herself. Also, the urinalysis meter is attached to, for example, the toilet 13 shown in FIG. 1, and measures at least one of urinary pH and urinary sugar of the user 10 . The sphygmomanometer and pulse meter are, for example, wristband-type measuring devices that can be worn on the arm of the user 10 and measure the blood pressure and pulse of the user 10 .

The estimating unit 26 estimates a feature amount of physical ability of the user 10 based on the motion detected by the detecting unit 24 . For example, the estimation unit 26 estimates the feature amount using the moving image obtained by the imaging unit 24a. Specifically, the feature amount of walking of the user 10 is acquired by analyzing the moving image. The feature value of walking is an example of the feature value of physical ability. at least one of the amount of change;

A characteristic amount of walking and each of muscle strength and muscle mass have a predetermined correlation. For this reason, the estimating unit 26 refers to the first correspondence information indicating the correspondence relationship between the feature amount of walking and the muscle strength and muscle amount, thereby estimating at least one of the muscle strength and the muscle amount of the user 10 from the feature amount of walking. decide. The first correspondence information indicating the correspondence relationship between the feature amount of walking and the muscle strength and muscle mass is pre-stored in the storage unit 22, for example. Note that the first correspondence information may indicate the correspondence relationship between the feature amount of walking and the cognitive function.

Also, for example, the estimation unit 26 estimates the feature quantity using the acceleration detected by the acceleration sensor 24b. When the acceleration sensor 24b is attached to the waist of the user 10, the movement of the waist of the user 10 during walking is detected. There is a predetermined correlation between the movement of the hips and the characteristic amount of walking such as walking balance and walking speed. Therefore, the estimation unit 26 determines the feature amount of walking by referring to the second correspondence information indicating the correspondence relationship between the movement of the waist and the feature amount of walking. The second correspondence information indicating the correspondence relationship between the movement of the waist and the feature amount of walking is pre-stored in the storage unit 22, for example. When the walking feature amount is determined, the estimating unit 26 determines muscle strength and muscle mass by referring to the first correspondence information based on the determined walking feature amount.

Note that the storage unit 22 may store correspondence information indicating a correspondence relationship between the acceleration data or the movement of the waist and the muscle strength and muscle mass. The storage unit 22 may store correspondence information indicating the correspondence relationship between the movement of the arms, legs or neck and muscle strength, regardless of the movement of the waist. At least one piece of correspondence information may be stored in the database unit 32 of the server device 30 .

The estimator 26 is implemented by, for example, a microcomputer. Specifically, the estimating unit 26 is realized by a nonvolatile memory storing a program, a volatile memory that is a temporary storage area for executing the program, an input/output port, a processor that executes the program, and the like. .

The active mass measurement unit 27 measures the active mass of the user 10 . The active mass measurement unit 27 is an active mass meter, but may be a pedometer that measures the number of steps of the user 10 . The activity meter or pedometer is always carried by the user 10 and measures the number of steps or the amount of activity of the user 10 in a day. The measured number of steps or amount of activity is accumulated in the storage unit 22 as an exercise history. The exercise history is obtained, for example, by continuously measuring the number of steps or amount of activity for each day over a plurality of days.

In this embodiment, measuring device 20 is not an integrated single device. For example, the imaging unit 24a and the acceleration sensor 24b of the detection unit 24 are configured by separate devices from the storage unit 22 and the estimation unit 26, respectively. Note that the measuring device 20 may be an integrated single device.

[Server device]
The server device 30 is a device that evaluates the physical ability of the user 10 by analyzing the feature amount measured by the measurement device 20, and determines the recommended content to be recommended to the user 10 based on the evaluation result. . The server device 30 is, for example, computer equipment. As shown in FIG. 2 , it includes a server device 30 , a communication section 31 , a database section 32 , an analysis section 33 and a selection section 34 .

The communication unit 31 is realized by one or more communication interfaces that perform wireless communication or wired communication. The communication unit 31 transmits and receives information and signals by communicating with each of the measuring device 20 and the terminal device 40 . For example, the communication unit 31 receives feature amounts and vital data that are measured by the measuring device 20 and transmitted via the communication unit 21 . The communication unit 31 transmits the evaluation result by the analysis unit 33 and the recommendation content determined by the analysis unit 33 to the measurement device 20 or the terminal device 40 . The communication unit 31 also receives information acquired by the input unit 42 of the terminal device 40 .

The database unit 32 is a storage unit that stores a database used by the muscle strength management system 1 to evaluate physical ability and determine recommended content. A specific example of the database will be described later. Further, the database unit 32 may store time-series data of each of the feature amount of physical ability and the vital data of the user 10 . Furthermore, the database unit 32 may store time-series data of each of the physical ability feature amounts and vital data of each of the plurality of users 10 . For example, by using data of others who have features similar to those of the user 10, it is possible to improve the accuracy of predicting future changes in physical ability. The database unit 32 is realized by a non-volatile storage device such as a semiconductor memory or HDD.

The analysis unit 33 analyzes the feature amount measured by the measurement unit 23 to evaluate (assess) the physical ability of the user 10 . The analysis unit 33 determines the content of recommendation to be made to the user 10 based on the result of the physical ability evaluation. Specifically, the analysis unit 33 determines exercise content and meal content recommended to the user 10 based on the result of the physical ability evaluation. The analysis unit 33 refers to the database stored in the database unit 32 to evaluate physical ability and determine recommended content.

For example, the analysis unit 33 evaluates the physical ability of the user 10 based on the time-series data of the feature amount measured by the measurement unit 23 . Specifically, the analysis unit 33 analyzes changes in the feature amount based on time-series data of the feature amount. For example, the analysis unit 33 can determine whether or not the exercise content and meal content recommended to the user 10 in the past are appropriate by analyzing the exercise history and changes in the feature amount.

Specifically, the analysis unit 33 determines whether or not the exercise content recommended to the user 10 has been practiced based on the exercise history. When the exercise content is practiced, the analysis unit 33 determines whether or not the change in the feature amount is a change expected from the recommended exercise content. If the change in the feature amount is not the expected change, or if the recommended exercise content is not practiced, the analysis unit 33 changes the recommended exercise content and meal content for the user 10 . If the change in feature amount is an expected change, the analysis unit 33 does not change the exercise content and meal content recommended to the user 10 . In this way, it is possible to provide feedback as to whether or not the recommended content is appropriate based on changes in the feature amount, so that more suitable recommended content can be recommended to the user 10 .

Moreover, in the present embodiment, the analysis unit 33 determines the recommended content further based on the vital data. Specifically, the analysis unit 33 determines the upper limit of the exercise intensity of the user 10 based on the vital data, and determines the exercise content with the exercise intensity lower than the upper limit as the exercise content included in the recommended content.

Further, the analysis unit 33 analyzes the time-series data of the feature amount of the physical ability and the exercise history of the user 10 to predict the future transition of the physical ability of the user 10 . For example, the analysis unit 33 predicts future changes in the physical ability of the user 10 when exercising according to the exercise content included in the recommended content and when not exercising. The analysis unit 33 predicts future changes by referring to the database stored in the database unit 32 . The evaluation result and prediction result of physical ability and the determined recommendation content are transmitted to the terminal device 40 via the communication unit 31 .

The analysis unit 33 and the selection unit 34 are realized by, for example, a microcomputer. Specifically, the analysis unit 33 and the selection unit 34 include a nonvolatile memory in which the program is stored, a volatile memory that is a temporary storage area for executing the program, an input/output port, a processor that executes the program, and the like. is realized by The analysis unit 33 and the selection unit 34 may be realized by sharing the same hardware resource.

The selection unit 34 selects one or more business operators from a plurality of business operators related to the recommended content based on a predetermined rule. Each of the plurality of business operators is a business operator that provides products or services that can be used by the user 10 . The plurality of business operators include dealers who sell equipment, equipment, tools, or clothes used by the user 10 for exercise, rental companies who rent these, or gyms or Businesses such as sports clubs are included. In addition, the plurality of businesses includes businesses that operate restaurants that provide meals or food to the user 10, or food or food delivery companies.

In this embodiment, the user 10 is presented with the advertising information of the business selected by the selection unit 34 . Specific processing for selecting a business operator will be described later.

[Terminal device]
The terminal device 40 is a device that presents information to the user 10 . In addition, the terminal device 40 receives input of information from the user 10 . For example, the terminal device 40 is a mobile terminal that can be carried by the user 10, such as a smart phone. Alternatively, the terminal device 40 may be a display device such as a television installed in the residence 11 of the user 10, or an audio output device such as a smart speaker. As shown in FIG. 2 , the terminal device 40 includes a communication section 41 , an input section 42 , a presentation section 43 and a storage section 44 .

The communication unit 41 is realized by one or more communication interfaces that perform wireless communication or wired communication. The communication unit 41 transmits and receives information and signals by communicating with each of the measuring device 20 and the server device 30 . For example, the communication unit 41 receives the evaluation result by the analysis unit 33 of the server device 30 and the recommended content determined by the analysis unit 33 . The communication unit 41 further receives information indicating the business selected by the selection unit 34 or advertisement information of the selected business. Also, the communication unit 41 transmits information acquired by the input unit 42 to the server device 30 .

The input unit 42 receives input from the user 10 . The input unit 42 is, for example, a touch sensor or physical buttons. Note that the input unit 42 may be a voice input device such as a microphone. As shown in FIG. 2, the input unit 42 has an acquisition unit 42a and a reception unit 42b.

The acquisition unit 42a acquires target values of exercise intensity and amount of exercise. The target value acquired by the acquisition unit 42 a is transmitted to the server device 30 via the communication unit 41 . The analysis unit 33 of the server device 30 determines exercise content included in the recommended content further based on the target value acquired by the acquisition unit 42a.

The accepting unit 42b accepts orders for products or services from the user 10 . The order received by the receiving unit 42b is transmitted to the server device 30 via the communication unit 41. FIG. Alternatively, the order received by the receiving unit 42b may be transmitted directly to the business operator's server device (not shown) or the like via the communication unit 41. FIG.

The presentation unit 43 presents the recommended content determined by the analysis unit 33 to the user 10 . The presenting unit 43 further presents to the user 10 the transition of the feature amount of physical ability predicted by the analyzing unit 33 . In addition, the presentation unit 43 presents advertisement information of businesses related to the recommended content.

As shown in FIG. 2, the presentation unit 43 has a display unit 43a. The display unit 43a is implemented by, for example, a liquid crystal display panel or an organic EL (Electroluminescence) display panel. The display unit 43a displays an image representing each of the recommended content, the transition of the feature amount, and the advertisement information. The display unit 43a generates and displays GUI (Graphical User Interface) objects such as selection buttons for receiving selections and operations from the user 10, for example.

Note that the presentation unit 43 may have a speaker for outputting sound instead of the display unit 43a or in addition to the display unit 43a. The presentation unit 43 may output audio representing the content to be presented to the user 10 .

The storage unit 44 is a non-volatile storage device such as flash memory. The storage unit 44 stores evaluation results and recommended content transmitted from the server device 30 . The storage unit 44 also stores information received by the input unit 42 . The storage unit 44 stores, for example, images to be displayed on the display unit 43a.

An example of the configuration of the muscle strength management system 1 has been described above based on FIG. 2, but the configuration of the muscle strength management system 1 is not limited to the example shown in FIG. For example, two devices out of the measurement device 20, the server device 30 and the terminal device 40 may not be able to communicate directly. For example, communication between the server device 30 and the terminal device 40 may be impossible. In this case, the server device 30 and the terminal device 40 may transmit and receive information and signals via the measuring device 20 .

[motion]
Next, the operation of muscle strength management system 1 according to the present embodiment will be described with reference to FIG. FIG. 3 is a flow chart showing the operation of the muscle strength management system 1 according to this embodiment.

As shown in FIG. 3, the measurement unit 23 first performs measurement processing (S10). Specifically, the detection unit 24 measures the feature amount of the physical ability of the user 10 (S11). More specifically, an image of the user 10 is acquired by the imaging unit 24a capturing an image of the user 10 (S12). Next, the estimation unit 26 estimates the feature amount of the physical ability of the user 10 based on the image obtained by the imaging unit 24a (S13). For example, the estimating unit 26 acquires a walking feature amount such as the walking speed of the user 10 by image processing. Furthermore, the estimating unit 26 estimates the muscle strength and muscle mass of the user 10 based on the correspondence information between the walking feature amount and the muscle strength. Note that the estimation unit 26 may estimate the muscle strength and muscle mass of the user 10 based on the acceleration data obtained by the acceleration sensor 24b instead of or in addition to the imaging by the imaging unit 24a.

Also, the vital measurement unit 25 of the measurement unit 23 measures the vital data of the user 10 (S14). Also, the active mass measuring unit 27 of the measuring unit 23 measures the active mass of the user 10 (S15). The measurement of the feature amount of physical ability (S11), the measurement of vital data (S14), and the measurement of the amount of activity (S15) may be performed at the same time, or any one of them may be performed first. The execution order of these processes is not particularly limited. Moreover, the measurement of the feature amount of physical ability (S11), the measurement of vital data (S14), and the measurement of the amount of activity (S15) may each be performed multiple times. Measured values obtained by a plurality of measurements are stored in at least one of the storage unit 22 and the database unit 32 as time-series data of feature amounts, time-series data of vital data, and exercise history.

Next, the analysis unit 33 determines the recommended content to be recommended to the user 10 based on the measured feature amount of physical ability (S20). Specifically, the analysis unit 33 determines exercise content and meal content recommended to the user 10 .

Next, the presentation unit 43 presents the determined recommended content to the user 10 (S30). Specifically, the display unit 43a displays the determined recommended content. A specific example of display will be described later.

[Determination of exercise content]
Next, a method for determining specific recommended contents will be described. First, an example of a method for determining exercise content will be described with reference to FIGS. 4 to 7. FIG.

FIG. 4 is a diagram showing a physical ability estimation table stored by muscle strength management system 1 according to the present embodiment. A physical ability estimation table is stored in the storage unit 22 of the measuring device 20 . Alternatively, it may be stored in the database section 32 of the server device 30 .

As shown in FIG. 4, the physical ability estimation table is prepared for each demographic attribute such as "female in her 50s" and "male in her 60s." Demographic attributes are, for example, age and gender.

The physical ability estimation table associates one or more reference values with each feature amount of physical ability. In the example shown in FIG. 4, the reference values are associated in five stages from "A" to "E". The reference value at each stage may be represented by one value or may be represented by a certain range.

"A" to "E" correspond to the evaluation results of the feature amount of physical ability. As an example, the order of "A" to "E" indicates that "A" has the highest physical ability and "E" has the lowest physical ability, but the reverse is also possible. For example, in the example shown in FIG. 4, "C" represents average physical ability, "A" and "B" represent higher than average physical ability, and "D" and "E" stands for below average physical ability.

In the present embodiment, analysis unit 33 evaluates the feature amount of user 10 by referring to the physical ability estimation table based on the feature amount measured by measurement unit 23 . Specifically, the analysis unit 33 compares each reference value of the physical ability estimation table corresponding to the age and gender to which the user 10 belongs and the feature amount of the user 10 measured by the measurement unit 23, thereby It is determined to which of "A" to "E" the 10 features correspond. For example, when the muscle strength of the user 10 measured by the measurement unit 23 is a value equal to or greater than P2 and less than P1, the analysis unit 33 determines the evaluation of the muscle strength of the user 10 as "B". The analysis unit 33 evaluates each physical ability feature amount. As a result, for example, as shown in FIG. 5, evaluation results such as "B" and "A" are obtained for each feature quantity of physical ability of the user 10. FIG.

FIG. 5 is a diagram showing an exercise recommendation table generated by the muscle strength management system 1 according to this embodiment. Specifically, FIG. 5 shows the relationship between the physical ability evaluation result by the analysis unit 33 and the exercise content recommended to the user 10 .

Also, the exercise recommendation table shown in FIG. 5 includes the difference from the standard value, the difference from the target value, and the priority order. The difference from the standard value is a value obtained by subtracting the standard value from the feature amount for each feature amount measured by the measuring unit 23 . The standard value is, for example, the reference value of "C", and corresponds to the average value of feature values of the same sex and age. For example, when the difference between the muscle strength and the standard value is a positive value, it means that the muscle strength exceeds the average value of the feature values of the same sex and the same age. A negative value of the difference between the muscle strength and the standard value means that the muscle strength is below the average value of the feature values of the same sex and the same age. In the example shown in FIG. 5, each of muscle strength, muscle mass, walking speed, and cognitive function exceeds the average values of the same sex and the same age.

The difference from the target value is a value obtained by subtracting the target value input by the user 10 from the measured feature quantity. For example, a positive difference between the muscle strength and the target value means that the muscle strength exceeds the target value. A negative difference between the muscle strength and the target value means that the muscle strength is below the target value. In the example shown in FIG. 5, each of muscle strength and walking balance is below the average values of the same sex and the same age.

FIG. 6 is a diagram showing an example of a target value input screen for user 10 displayed by muscle strength management system 1 according to the present embodiment. In the example shown in FIG. 6, the display unit 43a displays a text 50 prompting the user 10 to input a target value, and a GUI object 51 for inputting exercise intensity and exercise amount. A GUI object 51 is, for example, a slider. By operating the slider bar, the user 10 can input the intensity of exercise and the amount of exercise as target values. Note that the GUI object 51 may be a selection button or the like, or may be a text box. A method of inputting target values of exercise intensity and amount of exercise is not particularly limited.

The analysis unit 33 determines the target value of the feature amount of physical ability based on the target values of the exercise intensity and the exercise amount acquired by the acquisition unit 42a. Note that the acquisition unit 42a may cause the user 10 to input the target value of the feature amount of physical ability.

Returning to FIG. 5 , the priority order indicates the order of feature amounts that are considered important when determining the exercise content recommended for the user 10 . The priority order is determined, for example, based on the sum of the difference from the standard value and the difference from the target value. Specifically, the priority order is determined in descending order of the sum of these two differences. For example, in the example shown in FIG. 5, since the sum of the two differences in walking balance is "-1", which is the smallest, the priority order is "1", which is the highest. Since the sum of the two differences in muscle strength is "0", which is the second smallest, the priority order is "2".

Note that the method of determining the priority order is not limited to this. For example, the analysis unit 33 may determine the priority order so as to give a higher rank to the feature amount determined to have low physical ability. Specifically, the priority order may be determined based only on the difference from the standard value. For example, in the example shown in FIG. 5, the walking balance evaluation value is "C", which is the lowest, and therefore the priority order is "1", which is the highest. In this case, if there are a plurality of feature amounts with the same evaluation result, the analysis unit 33 may give a higher rank to the feature amount with a smaller difference from the target value.

In the present embodiment, the analysis unit 33 determines the exercise content based on the priority order and the difference between each of the plurality of feature values and the standard value or the target value. For example, the database unit 32 stores an exercise database in which appropriate exercise contents are associated with each feature amount of physical ability to improve or maintain the corresponding feature amount. In the exercise database, the increase/decrease amount of the feature amount may be associated with the exercise intensity and exercise amount of the exercise content. By referring to the exercise database, the analysis unit 33 determines the exercise content that is appropriate for enhancing the feature value with the high priority order as the exercise content to be recommended to the user 10 . Also, at this time, the analysis unit 33 determines the upper limit of the exercise intensity based on the vital data, and determines the exercise content with the exercise intensity lower than the determined upper limit.

FIG. 7 is a diagram showing the relationship between physical conditions and exercise intensity. In FIG. 7, the horizontal axis represents physical conditions, and the vertical axis represents exercise intensity. As shown in FIG. 7, the range of exercise intensity required to improve or maintain muscle strength differs depending on physical conditions. The physical condition is determined based on the feature amount of physical ability and vital data.

The lower limit of the exercise intensity range corresponds to the minimum amount of exercise required to improve or maintain muscle strength. In other words, even if you exercise at an intensity below the lower limit, it does not contribute to the increase or maintenance of muscle strength. The lower limit depends on physical ability. The higher the physical ability, the higher the lower limit. The lower the physical ability, the lower the lower limit.

Also, the upper limit of the range of exercise intensity is the upper limit within a range where there is no risk of causing health problems due to excessive load on the body. In other words, as long as you exercise at an intensity below the upper limit, the risk of health problems is sufficiently low. The upper limit is determined, for example, based on vital data. For example, if blood pressure or heart rate is high, the upper limit will be low. If blood pressure or heart rate is low, the upper limit will be higher. In the present embodiment, analysis unit 33 determines the upper limit of exercise intensity of user 10 based on vital data.

Note that the analysis unit 33 may correct the upper limit value and the lower limit value based on the personal characteristics of the user 10 . Specifically, the analysis unit 33 may correct at least one of the upper limit value and the lower limit value based on at least one of the time-series data of the feature quantity and the exercise history. For example, the analysis unit 33 determines whether or not the constitution of the user 10 is easy to build muscle based on the time-series data of the feature amount and the exercise history, and changes the lower limit value based on the result of the determination. may

[Determination of meal content]
Next, an example of a method of determining meal content will be described with reference to FIG.

FIG. 8 is a diagram showing a meal recommendation table generated by muscle strength management system 1 according to the present embodiment. Specifically, FIG. 8 shows the relationship between the evaluation result of physical ability by the analysis unit 33 and the meal contents recommended to the user 10 .

The meal recommendation table shown in FIG. 8 includes intake amounts and reference values for each of the calories of meals and a plurality of nutrients. The intake amount is, for example, a reported value obtained based on the input result of the user 10 inputting the content of the meal ingested by the user 10 via the input unit 42 . The reference value is, for example, a value determined for each demographic attribute.

The analysis unit 33 determines recommended values for each of the calorie and the plurality of nutrients based on the difference between the intake amount and the reference value. The recommended value corresponds to the difference between the reported intake amount of the user 10 and the intake amount that the user 10 should take. In other words, the recommended value indicates the amount that should be increased or decreased from the amount currently ingested by the user 10 for each of the calories and multiple nutrients.

In the meal recommendation table, an additional criterion is associated with each combination of the feature amount of physical ability, the calorie of the meal, and a plurality of nutrients. The addition criterion is determined based on the evaluation result of the feature quantity. Additional criteria are used to correct the intake of corresponding calories or nutrients that user 10 should take. Specifically, the analysis unit 33 increases the amount of intake to be taken by the user 10 if the addition criterion is "+". If the additional criterion is "-", the analysis unit 33 reduces the intake amount that the user 10 should take. If the additional reference is "0", the analysis unit 33 does not correct the intake amount that the user 10 should take.

For example, in the case of protein, the intake of the user 10 is "40" and the reference value is "50", so the difference is "-10". In other words, the recommended value is "+10" because the intake of protein is "10" short. In addition, as additional criteria for proteins, "+" is associated with each of muscle strength, walking balance, and cognitive function. Therefore, the analysis unit 33 increases the recommended value from "10" and corrects it to, for example, "+20". The amount of correction at this time is determined, for example, based on the number of "+". This indicates that the user 10 should consume "+20" more than the current protein intake in order to further improve muscle strength, walking balance and cognitive function.

The analysis unit 33 determines the meal content recommended to the user 10 based on the recommended values for each of the calories and the plurality of nutrients. For example, the database unit 32 stores a meal database in which calories and a plurality of nutrients are associated with each meal menu or food item. The analysis unit 33 refers to the meal database to determine an appropriate meal menu or food according to the recommended value as the meal content to be recommended to the user 10 .

Also, for example, the analysis unit 33 determines foods that should not be recommended to the user 10 as excluded foods based on the vital data, and determines meal content using foods other than the excluded foods. For example, when the blood sugar level, which is an example of vital data, is equal to or higher than the threshold, the analysis unit 33 determines foods containing a large amount of sugar as excluded foods. For example, the database unit 32 stores a food database that associates vital data thresholds with excluded foods that should not be ingested when the thresholds are exceeded or below the thresholds. The analysis unit 33 refers to the food database based on the vital data of the user 10 to determine excluded foods, and determines meal content using foods other than the excluded foods.

[Example of recommended content]
Next, a specific example of presentation of recommended content to the user 10 by the muscle strength management system 1 according to the present embodiment will be described.

FIG. 9 is a diagram showing an example of exercise content 60 recommended to user 10 displayed by muscle strength management system 1 according to the present embodiment. In the example shown in FIG. 9, the exercise name "walking" is displayed as the exercise content 60 recommended for the user 10. In the example shown in FIG. Further, as specific contents of the exercise content 60, an exercise intensity 61 indicating a guideline of walking speed and an exercise amount 62 indicating walking time are respectively displayed in text.

Note that the display unit 43a may display an image or video representing a specific operation example of the exercise content 60. FIG. Alternatively, the display unit 43a may display, in addition to the text representing the exercise content 60, the URL (Uniform Resource Locator) of a website that streams images representing specific examples of motion.

As shown in FIG. 10 , the display unit 43 a may display not only the exercise content 60 but also the future prediction 63 estimated by the analysis unit 33 . FIG. 10 is a diagram showing an example of exercise content 60 recommended to user 10 and future prediction 63 displayed by muscle strength management system 1 according to the present embodiment.

In the example shown in FIG. 10, the display unit 43a displays a graph of future prediction 63 of muscle mass. For example, the display unit 43a shows prediction results of future changes in muscle mass when the user 10 does and does not perform the exercise represented by the exercise content 60 .

Further, as shown in FIG. 11, the display unit 43a may display not only the exercise content 60 but also the advertisement information 71 of the business operator selected by the selection unit . FIG. 11 is a diagram showing an example of exercise content 60 recommended to user 10 and advertisement information 71 displayed by muscle strength management system 1 according to the present embodiment.

The advertisement information 71 is information that advertises products or services provided by businesses related to the exercise content 60 . In the example shown in FIG. 11, the advertisement information 71 includes the business name and URL. Furthermore, the display unit 43 a displays a reservation button 72 . The reservation button 72 is displayed for each business, for example. The reservation button 72 is an example of a GUI object for accepting service orders from the user 10 . When the reservation button 72 is selected by the user 10, the reception unit 42b reserves the service for the corresponding business operator.

In addition to the exercise content 60, the display unit 43a may display meal content 80 recommended to the user 10, as shown in FIG. FIG. 12 is a diagram showing an example of meal content 80 recommended to user 10 and advertisement information 81 displayed by muscle strength management system 1 according to the present embodiment.

In the example shown in FIG. 12 , a meal menu of “fish dishes” is displayed as the meal content 80 recommended to the user 10 . Moreover, the advertisement information 81 is information for advertising goods or services provided by a business operator related to the meal content 80 . The advertisement information 81 includes the name of the business operator, the URL, and the meal menu provided by the business operator. For example, the advertisement information 81 includes multiple meal menus, but may include only one meal menu.

The display unit 43a further displays an order button 82. FIG. An order button 82 is displayed for each meal menu included in the advertisement information 81 . The order button 82 is an example of a GUI object for accepting orders for products or services from the user 10 . When the order button 82 is selected by the user 10, the reception unit 42b places a meal order for the corresponding business operator. For example, by registering the residence 11 of the user 10 in advance, the ordered meal can be delivered to the residence 11 and provided to the user 10 .

Note that the meal content 80 may indicate the amount of calories and nutrients to be ingested instead of the meal menu. In addition to the meal menu, the meal content 80 may also include a cooking recipe for making a meal indicated by the meal menu. The advertisement information 81 may be advertisement information of a business that delivers the ingredients included in the cooking recipe.

[Business operator selection]
Here, a method of selecting a business operator performed by the selection unit 34 of the server device 30 will be described.

A rule for selecting operators is, for example, to follow the priority assigned to each operator. The selection unit 34 selects one or more businesses from among the plurality of businesses in descending order of priority. The number of businesses to be selected may be one, a plurality, or a number specified by the user. A priority may be assigned, for example, to each business content of a business operator. For example, multiple priorities may be assigned when one business is engaged in multiple businesses.

In the present embodiment, the user 10 is presented with advertisement information of a business selected by the selection unit 34 from among a plurality of businesses. Advertising information is information that advertises products or services provided by businesses. The selection unit 34 updates rules for selecting businesses based on the history of orders for products or services.

FIG. 13 is a diagram showing order history information managed by the muscle strength management system 1 according to the present embodiment. Order history information is stored in the database unit 32 of the server device 30, for example. As shown in FIG. 13, the history information includes the date and time when the order was received by the receiving unit 42b, the orderer who is the company to whom the order was placed, and the contents of the order.

The selection unit 34 calculates the frequency of orders from the user 10 for each business operator, and updates the order of priority in descending order of frequency. In addition, the selection unit 34 may give higher priority to a new business operator or a business operator to which the user 10 has not placed an order in the past. As an example, the selection unit 34 may select a business operator with the highest order frequency and a new business operator or a business operator with which the user 10 has no ordering experience.

In the example shown in FIG. 13, "AA Restaurant" has received five orders, which is higher in order frequency than "BB Shokudo", which has received only one order. Therefore, the selection unit 34 updates the priority of "AA restaurant" to be higher than that of "BB restaurant".

FIG. 14 is a diagram showing an example of a provider database managed by muscle strength management system 1 according to the present embodiment. The business operator database shown in FIG. 14 shows a list of multiple business operators who can provide products or services to the user 10 .

In the example shown in FIG. 14, in addition to "AA restaurant" and "BB cafeteria", "CC cafe" is included as an operator. Therefore, by comparing with the history information shown in FIG. 13 , the selection unit 34 can determine that “CC café” is an operator with which the user 10 has no ordering experience. As a result, the selection unit 34 can update the priority of "CC café" to be higher than that of "BB cafeteria". It should be noted that the method of selecting a business operator is not limited to the example described above.

[Effects, etc.]
As described above, the muscle strength management system 1 according to the present embodiment includes the measurement unit 23 that measures the feature amount of the physical ability of the user 10, and analyzes the feature amount measured by the measurement unit 23. An analysis unit 33 that evaluates physical ability and determines recommended content including exercise content recommended to the user 10 based on the evaluation result, and a presentation unit that presents the recommended content determined by the analysis unit 33 to the user 10. 43.

As a result, based on the evaluation result of the physical ability obtained by analyzing the feature amount of the physical ability of the user 10, the exercise content recommended for the user 10 is determined and presented. Therefore, it is possible to efficiently assist the user 10 in building or maintaining muscle strength.

Also, for example, the feature amount of physical ability is at least one of muscle strength, muscle mass, walking speed, and walking balance.

As a result, it is possible to express the feature quantity of the physical ability as a quantitative and specific value, so that it is possible to recommend more appropriate exercise content for the user 10 . Therefore, it is possible to efficiently assist the user 10 in building or maintaining muscle strength.

Also, for example, the measuring unit 23 further measures the vital data of the user 10 . The analysis unit 33 determines the recommended content further based on the vital data.

Accordingly, it is possible to determine the health condition of the user 10, such as whether or not the user 10 has a chronic disease, based on the vital data of the user 10. FIG. Therefore, it is possible to recommend an appropriate exercise content within a reasonable range so as not to harm the health of the user 10 .

Also, for example, the vital data is at least one of the weight, blood pressure, pulse rate, urine pH, and urine sugar of the user 10 .

As a result, since the vital data can be represented by specific values, it is possible to recommend more appropriate exercise content for the user 10 . Therefore, it is possible to efficiently assist the user 10 in building or maintaining muscle strength.

Also, for example, the analysis unit 33 determines the upper limit of the exercise intensity of the user 10 based on the vital data, and determines the exercise content with the exercise intensity lower than the upper limit as the exercise content included in the recommended content.

As a result, since the upper limit of exercise intensity is determined based on the vital data, even for the user 10 who should not exercise vigorously, appropriate exercise within a reasonable range is possible so as not to harm the health of the user 10 . Can recommend content.

In addition, for example, the muscle strength management system 1 further includes a storage unit 22 for storing time-series data of feature amounts measured by the measurement unit 23 . The analysis unit 33 evaluates the physical ability of the user 10 by analyzing the time-series data.

Thereby, it is possible to analyze the change in the feature amount of the user 10 based on the time-series data. Therefore, for example, based on the presence or absence and magnitude of change in the feature amount, it is possible to feed back the appropriateness of the recommended content, and it is possible to determine the more suitable recommended content for the user 10 .

Also, for example, the storage unit 22 further stores the exercise history of the user 10 . The analysis unit 33 further analyzes the time-series data and exercise history to predict future changes in the physical ability of the user 10 . The presentation unit 43 further presents the transition predicted by the analysis unit 33 to the user 10 .

As a result, the user 10 can be presented with the possibility of sarcopenia, frailty, and the like, so that the user 10 can be strongly urged to exercise and eat appropriately.

Also, for example, the exercise content included in the recommended content includes exercise intensity and amount of exercise.

As a result, it is possible to specifically present the exercise content that the user 10 should do, so that the user 10 can smoothly perform the recommended exercise content.

In addition, for example, the muscle strength management system 1 further includes an acquisition unit 42a that acquires target values of exercise intensity and exercise amount. The analysis unit 33 determines exercise content included in the recommended content, further based on the target value acquired by the acquisition unit 42a.

As a result, the intention of the user 10 can be reflected in the recommended content by having the user 10 input the target value. For example, if the user 10 does not want to exercise too vigorously, by lowering the target value of exercise intensity, it is possible to recommend appropriate exercise contents according to the target value.

Also, for example, the measurement unit 23 includes a detection unit 24 that detects the motion of the user 10, and an estimation unit 26 that estimates the feature amount of the physical ability of the user 10 based on the motion detected by the detection unit 24. .

Thus, by estimating the feature amount of physical ability, it is possible to indirectly acquire it. For this reason, for example, the user 10 does not need to wear a special measuring device for measuring muscle mass, so the feature amount of physical ability can be easily measured.

Further, for example, the detection unit 24 includes at least one of an imaging unit 24a (camera 12) that captures the user 10 and an acceleration sensor 24b that the user 10 carries. The estimation unit 26 uses at least one of the moving image obtained by the camera 12 and the acceleration detected by the acceleration sensor 24b to estimate the feature quantity.

As a result, the motion of the user 10 can be easily detected using the camera 12 (imaging unit 24a) or the acceleration sensor 24b, so that the feature amount of physical ability can be easily measured.

Also, for example, the analysis unit 33 analyzes the feature amount measured by the measurement unit 23 to further determine the meal content recommended to the user 10 . The recommended content further includes meal content determined by the analysis unit 33 .

As a result, not only the details of exercise but also the details of meals are presented to the user 10, so that it is possible to efficiently assist the user 10 in building or maintaining muscle strength.

Also, for example, the presentation unit 43 further presents advertisement information of a business related to the recommended content.

As a result, by displaying the advertisement information, the user 10 can obtain the goods necessary for actually performing the recommended content, or can easily receive the service. You can raise expectations for action. Therefore, it is possible to more efficiently assist the user in building or maintaining muscle strength.

Further, for example, the advertisement information is information that advertises products or services provided by the business. The muscle strength management system 1 further includes a reception unit 42b that receives orders for products or services from the user 10. FIG.

As a result, it is possible to easily order products or services related to the recommended content, so that it is possible to increase the expectation value that the user 10 will actually implement the recommended content. That is, it is possible to more efficiently assist the user in building or maintaining muscle strength.

In addition, for example, the muscle strength management system 1 further includes a selection unit 34 that selects one or more businesses from a plurality of businesses related to the recommended content based on a predetermined rule. The presentation unit 43 presents the advertisement information of each of the one or more businesses selected by the selection unit 34 . The selection unit 34 updates the rules based on the order history received by the reception unit 42b.

As a result, the advertisement information of the appropriate business is displayed, so that the user 10 can obtain the products necessary for actually carrying out the recommended content, or can easily receive the service. 10 can really raise the bar for expectations.

Further, for example, the muscle strength management method according to the present embodiment includes the steps of measuring the feature amount of the physical ability of the user 10, analyzing the detected feature amount to evaluate the physical ability of the user 10, and performing the evaluation. Based on the result of (1), the step of determining the recommended content including the exercise content recommended to the user 10, and the step of presenting the determined recommended content to the user 10.

Accordingly, it is possible to efficiently assist the user 10 in increasing or maintaining muscle strength.

(others)
Although the muscle strength management system and the muscle strength management method according to the present invention have been described above based on the above embodiments, the present invention is not limited to the above embodiments.

For example, the recommended content recommended to the user 10 may not include meal content.

Also, for example, the measuring unit 23 may not measure at least one of the vital data and the amount of activity of the user 10 .

Also, for example, the feature amount of physical ability may be directly measured. For example, the leg muscle strength of the user 10 may be measured by attaching a muscle strength measuring device to the leg of the user 10 . By directly measuring muscle strength, the measurement accuracy can be improved.

Also, the communication method between the devices described in the above embodiments is not particularly limited. When wireless communication is performed between devices, the wireless communication method (communication standard) is, for example, ZigBee (registered trademark), Bluetooth (registered trademark), or short-range wireless communication such as wireless LAN (Local Area Network). be. Alternatively, the wireless communication method (communication standard) may be communication via a wide area communication network such as the Internet. Also, wire communication may be performed between devices instead of wireless communication. Wired communication is, specifically, communication using power line communication (PLC: Power Line Communication) or wired LAN.

Further, in the above-described embodiments, the processing executed by a specific processing unit may be executed by another processing unit. Also, the order of multiple processes may be changed, or multiple processes may be executed in parallel. Also, the allocation of the components of the muscle strength management system to a plurality of devices is an example. For example, a component included in one device may be included in another device. For example, the terminal device 40 or the server device 30 may have the components included in the measurement device 20 . Specifically, the terminal device 40 may include the measurement unit 23 . Alternatively, the terminal device 40 includes some components included in the measurement unit 23, specifically, at least one of the imaging unit 24a, the acceleration sensor 24b, the vital measurement unit 25, the estimation unit 26, and the activity amount measurement unit 27 may be provided. Further, for example, the server device 30 may include the estimation unit 26 . At least one of the database unit 32, the analysis unit 33, and the selection unit 34 included in the server device 30 may be included in the measurement device 20 or the terminal device 40. Further, for example, the measurement device 20 may include at least one of the input unit 42 and the presentation unit 43 included in the terminal device 40 . Also, the strength management system may be implemented as a single device.

For example, the processing described in the above embodiments may be implemented by centralized processing using a single device (system), or may be implemented by distributed processing using a plurality of devices. good. Also, the number of processors executing the above program may be singular or plural. That is, centralized processing may be performed, or distributed processing may be performed.

Further, in the above embodiments, all or part of the components such as the control unit may be configured with dedicated hardware, or implemented by executing a software program suitable for each component. good too. Each component may be implemented by a program execution unit such as a CPU (Central Processing Unit) or processor reading and executing a software program recorded in a recording medium such as a HDD (Hard Disk Drive) or semiconductor memory. good.

Also, components such as the controller may be configured with one or more electronic circuits. Each of the one or more electronic circuits may be a general-purpose circuit or a dedicated circuit.

One or more electronic circuits may include, for example, a semiconductor device, an IC (Integrated Circuit), or an LSI (Large Scale Integration). An IC or LSI may be integrated on one chip or may be integrated on a plurality of chips. Although they are called ICs or LSIs here, they may be called system LSIs, VLSIs (Very Large Scale Integrations), or ULSIs (Ultra Large Scale Integrations) depending on the degree of integration. An FPGA (Field Programmable Gate Array) that is programmed after the LSI is manufactured can also be used for the same purpose.

Also, general or specific aspects of the invention may be implemented in a system, apparatus, method, integrated circuit or computer program product. Alternatively, the computer program may be implemented by a computer-readable non-temporary recording medium such as an optical disc, HDD, or semiconductor memory. Also, any combination of systems, devices, methods, integrated circuits, computer programs and recording media may be implemented.

In addition, it can be realized by applying various modifications to each embodiment that a person skilled in the art can think of, or by arbitrarily combining the constituent elements and functions of each embodiment without departing from the spirit of the present invention. Forms are also included in the present invention.

1 muscle strength management system 10 users 22, 44 storage unit 23 measurement unit 24 detection unit 24a imaging unit 24b acceleration sensor 25 vital measurement unit 26 estimation unit 32 database unit 33 analysis unit 34 selection unit 42a acquisition unit 42b reception unit 43 presentation unit 43a display Part 60 Exercise content 61 Exercise intensity 62 Exercise amount 63 Future predictions 71, 81 Advertising information 72 Reservation button 80 Meal content 82 Order button

Claims (14)

a measurement unit that measures a plurality of feature amounts of physical ability of the user;
The user's physical ability is evaluated for each feature amount by analyzing a plurality of feature amounts measured by the measurement unit, and the result of the evaluation for each feature amount and the recommended exercise content for the user are calculated. an analysis unit that determines the recommended content including the exercise content based on the priority order for each of the feature values indicating the order of importance when making a decision;
a presentation unit that presents the recommended content determined by the analysis unit to the user ;
The measuring unit
a detection unit that detects the user's motion;
an estimating unit that estimates a feature quantity of the user's physical ability based on the motion detected by the detecting unit;
The detection unit includes at least one of a camera for photographing the user and an acceleration sensor carried by the user,
The estimation unit estimates the feature amount using at least one of a moving image obtained by the camera and acceleration detected by the acceleration sensor.
strength management system. The muscle strength management system according to claim 1, wherein the feature amount of physical ability is at least one of muscle strength, muscle mass, walking speed, and walking balance. The measurement unit further measures the user's vital data,
The muscle strength management system according to claim 1 or 2, wherein the analysis unit determines the recommended content further based on the vital data. The muscle strength management system according to claim 3, wherein the vital data is at least one of weight, blood pressure, pulse, urine pH, and urine sugar of the user. 4. The analysis unit determines an upper limit of exercise intensity for the user based on the vital data, and determines exercise content with an exercise intensity lower than the upper limit as exercise content included in the recommended content. 5. The muscle strength management system according to 4. Furthermore, a storage unit for storing time-series data of the feature amount measured by the measurement unit,
The muscle strength management system according to any one of claims 1 to 5, wherein the analysis unit performs the evaluation by analyzing the time-series data. The storage unit further stores the user's exercise history,
The analysis unit further analyzes the time-series data and the exercise history to predict future transitions in physical ability of the user,
The muscle strength management system according to claim 6, wherein the presenting unit further presents the transition predicted by the analyzing unit to the user. The muscle strength management system according to any one of claims 1 to 7, wherein the exercise content included in the recommended content includes exercise intensity and exercise amount. Furthermore, an acquisition unit that acquires target values of exercise intensity and amount of exercise,
The muscle strength management system according to claim 8, wherein the analysis unit determines the exercise content included in the recommended content further based on the target value acquired by the acquisition unit. The analysis unit analyzes the feature amount measured by the measurement unit to further determine the meal content recommended to the user,
The muscle strength management system according to any one of claims 1 to 9 , wherein said recommended content further includes meal content determined by said analysis unit. The muscle strength management system according to any one of claims 1 to 10 , wherein the presenting unit further presents advertisement information of a business related to the recommended content. The advertising information is information advertising a product or service provided by the business operator,
12. The muscle strength management system according to claim 11 , further comprising a reception unit that receives an order for the product or the service from the user. Furthermore, a selection unit that selects one or more businesses from a plurality of businesses related to the recommended content based on a predetermined rule,
The presentation unit presents the advertisement information of each of the one or more businesses selected by the selection unit;
The muscle strength management system according to claim 12 , wherein the selector updates the rule based on a history of orders received by the receiver. 1. A strength management method implemented by one or more computers, comprising:
a step of measuring a plurality of feature amounts of the user's physical ability by a measuring unit included in any one of the one or more computers ;
An analysis unit included in any one of the one or more computers analyzes a plurality of measured feature amounts to evaluate the physical ability of the user for each feature amount, and evaluate the evaluation for each feature amount. a step of determining recommended content including the exercise content based on the result and the priority order for each of the feature values indicating the order of importance when determining the exercise content recommended for the user;
presenting the determined recommendations to the user ;
The measuring unit
a detection unit that detects the user's motion;
an estimating unit that estimates a feature quantity of the user's physical ability based on the motion detected by the detecting unit;
The detection unit includes at least one of a camera for photographing the user and an acceleration sensor carried by the user,
The estimation unit estimates the feature amount using at least one of a moving image obtained by the camera and acceleration detected by the acceleration sensor.
strength management method.

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