Muscle active state management device, muscle active state management method and muscle active state management program

Abstract

To surely manage the active state of a muscle.SOLUTION: A muscle active state management device comprises: a muscle active state acceleration data acquisition unit which acquires muscle active state acceleration data during a period in which a user moves the body to perform a prescribed movement and is in the muscle active state from an acceleration sensor placed on the midline being the central line of the left and right of the body of the user; a phase segmentation unit which segments the prescribed movement into phases of the movement on the basis of the acquired muscle active state acceleration data; an improvement portion identification unit which identifies at least one of the body portion and mental state of the user requiring improvement by comparing the physical and mental functions of the user with the reference physical and mental functions on the basis of the muscle active state acceleration data for each phase of the segmented movement; an improvement method generation unit which generates an improvement method according to at least specified one of the body portion and mental state of the user requiring improvement; and a proposal unit which proposes the generated improvement method to the user.SELECTED DRAWING: Figure 2A

Description

[Technical field]

[0001] The present invention relates to a muscle performance state management device, a muscle performance state management method, and a muscle performance state management program. [Background technology]

[0002] In the above technical field, Patent Document 1 discloses that a user's measured muscle strength, muscle mass, walking speed, walking bounce, and vital data are analyzed to evaluate the user's physical ability, and the exercise and dietary content to be recommended to the user is determined based on the evaluation results (paragraphs

[0014] to

[0017] ,

[0040] , etc.). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2020 / 208945 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the technology described in Patent Document 1 does not analyze the user's physical ability for each phase of movement, and therefore cannot reliably manage the working state of muscles. [Means for solving the problem]

[0005] In order to achieve the above object, a muscle activity status management device according to the present invention comprises: a muscle activity acceleration data acquisition unit that acquires muscle activity acceleration data from an acceleration sensor disposed on a median line, which is a center line between the left and right sides of the user's body, while the user is moving the body to perform a predetermined movement and is in a muscle activity state; a phase dividing unit that divides the predetermined motion into phases of a motion based on the acquired muscle activity acceleration data; an improvement part specifying unit that specifies at least one of a body part and a mental state of the user that needs improvement by comparing the mental and physical function of the user with a reference mental and physical function based on the muscle activity acceleration data for each of the separated phases of the movement; an improvement method generating unit that generates an improvement method according to at least one of the identified body part and mental state of the user that need improvement; a suggestion unit that suggests the generated improvement method to the user; Equipped with:

[0006] In order to achieve the above object, a muscle activity management method according to the present invention includes: a muscle activity acceleration data acquisition step of acquiring muscle activity acceleration data from an acceleration sensor disposed on a median line, which is a center line between the left and right sides of the user's body, while the user is moving the body to perform a predetermined movement and is in a muscle activity state; a phase dividing step of dividing the predetermined motion into phases of a motion based on the acquired muscle activity acceleration data; an improvement part identification step of identifying at least one of the user's body part and mental state that need to be improved by comparing the user's mental and physical function with a reference mental and physical function based on the muscle activity acceleration data for each of the separated movement phases; an improvement method generating step of generating an improvement method according to at least one of the identified body part and mental state of the user that need improvement; a suggestion step of suggesting the generated improvement method to the user; Includes.

[0007] Furthermore, in order to achieve the above object, the muscle activity management program according to the present invention comprises: a muscle activity acceleration data acquisition step of acquiring muscle activity acceleration data from an acceleration sensor disposed on a median line, which is a center line between the left and right sides of the user's body, while the user is moving the body to perform a predetermined movement and is in a muscle activity state; a phase dividing step of dividing the predetermined motion into phases of a motion based on the acquired muscle activity acceleration data; an improvement part identification step of identifying at least one of the user's body part and mental state that need to be improved by comparing the user's mental and physical function with a reference mental and physical function based on the muscle activity acceleration data for each of the separated movement phases; an improvement method generating step of generating an improvement method according to at least one of the identified body part and mental state of the user that need improvement; a suggestion step of suggesting the generated improvement method to the user; to be executed by the computer. Effect of the Invention

[0008] According to the present invention, the user's physical function is analyzed for each phase of movement, so that the working state of the muscles can be reliably managed. [Brief description of the drawings]

[0009] [Figure 1] FIG. 2 is a diagram for explaining an outline of the operation of the muscle operation state management device according to the first embodiment of the present invention. [Figure 2A] FIG. 1 is a block diagram illustrating a configuration of a muscle operation state management device according to a first embodiment of the present invention. [Figure 2B] FIG. 2 is a diagram illustrating division of an action into movement phases by the muscle operation state management device according to the first embodiment of the present invention. [Figure 3A] FIG. 4 is a diagram illustrating an example of an acceleration data table included in the muscle operation state management device according to the first embodiment of the present invention. [Figure 3B] FIG. 4 is a diagram illustrating an example of a mental state determination table included in the muscle operation state management device according to the first embodiment of the present invention. [Figure 4] FIG. 1 is a diagram illustrating a hardware configuration of a muscle operation state management device according to a first embodiment of the present invention. [Diagram 5]5 is a flowchart illustrating a processing procedure of the muscle operation state management device according to the first embodiment of the present invention. [Figure 6] FIG. 11 is a block diagram illustrating the configuration of a muscle operation state management device according to a second embodiment of the present invention. [Figure 7A] FIG. 11 is a diagram illustrating an example of a mental state improvement table included in the muscle operation state management device according to the second embodiment of the present invention. [Figure 7B] FIG. 11 is a diagram illustrating an example of a body part improvement table included in the muscle operation state management device according to the second embodiment of the present invention. [Figure 8] FIG. 11 is a diagram illustrating a hardware configuration of a muscle operation state management device according to a second embodiment of the present invention. [Figure 9] 10 is a flowchart illustrating a processing procedure of a muscle operation state management device according to a second embodiment of the present invention. [Figure 10] FIG. 11 is a block diagram illustrating the configuration of a muscle operation state management device according to a third embodiment of the present invention. [Figure 11] 13 is a flowchart illustrating a processing procedure of a muscle operation state management device according to a third embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, the embodiments of the present invention will be described in detail with reference to the drawings. However, the configurations, numerical values, process flows, functional elements, etc. described in the following embodiments are merely examples, and are free to be modified or changed, and are not intended to limit the technical scope of the present invention to the following description.

[0011] [First embodiment] A muscle performance management device according to a first embodiment of the present invention will be described with reference to Figs. 1 to 5. Fig. 1 is a diagram for explaining an overview of the operation of the muscle performance management device 100 according to this embodiment. The muscle performance management device 100 is a device that analyzes the muscle performance of a user for each phase of movement, identifies body parts and mental state to be improved, and proposes an improvement method.

[0012] As shown in Fig. 1, for example, assume that user 110 is walking, running, or the like. The muscle operation state management device 100 acquires acceleration data from an acceleration sensor carried by user 110 while user 110 is performing a predetermined movement such as walking or running and is in a muscle operation state. The acceleration sensor is placed on the median line of the body of user 110. The acceleration sensor may be held by user 110 or may be attached to the body of user 110.

[0013] The muscle performance state management device 100 then divides the movement of the user 110 into phases based on the acquired acceleration data. For each divided phase of the movement, the muscle performance state management device 100 compares the mental and physical function (walking movement) of the user 110 with a reference mental and physical function (walking movement) to identify body parts and the like that need improvement. The muscle performance state management device 100 displays the identified body parts and the like on a display screen of a mobile terminal such as a smartphone carried by the user 110. The user 110 can recognize the body parts and mental state that need improvement by looking at the display screen.

[0014] The configuration of the muscle performance management device 100 according to this embodiment will be described with reference to Fig. 2A. The muscle performance management device 100 includes a muscle performance acceleration data acquisition unit 201, a phase isolation unit 202, an improvement part identification unit 203, and a display control unit 204.

[0015] <<Muscle activity state acceleration data acquisition unit 201>> The muscle activity state acceleration data acquisition unit 201 acquires muscle activity state acceleration data from an acceleration sensor arranged on the median line, which is the center line between the left and right sides of the body of the user 110, while the user 110 moves his / her body to perform a predetermined movement and is in a muscle activity state. The muscle activity state acceleration data acquisition unit 201 may acquire muscle activity state acceleration data from the acceleration sensor in real time, or may acquire data recorded in the acceleration sensor after the user 110 has completed the predetermined movement. The muscle activity state acceleration data acquisition unit 201 may also acquire muscle activity state acceleration data from the acceleration sensor via wireless communication or wired communication. Alternatively, the muscle activity state acceleration data acquisition unit 201 may acquire muscle activity state acceleration data recorded in the acceleration sensor via a predetermined computer-readable recording medium.

[0016] Here, the acceleration sensor used is, for example, one built into a mobile terminal such as a smartphone carried by the user 110. However, the acceleration sensor may be, for example, a wearable device attached to the body of the user 110, or a device such as a data logger capable of recording acceleration data.

[0017] For example, when the user 110 uses a smartphone to record acceleration data during a predetermined movement, the user 110 first holds the smartphone on the midline of his or her body. Note that the muscle performance management device 100 may provide instructions to the user 110 by voice, image, or the like via the smartphone so that the user 110 can reliably hold the smartphone on the midline. Then, when the data from the acceleration sensor remains at a constant value for a predetermined period of time, the muscle performance management device 100 determines that the user 110 holds the smartphone on the midline. The muscle performance management device 100 can determine the direction of gravity by acquiring acceleration data in this state.

[0018] The user 110 moves his / her body to perform a predetermined motion while holding the smartphone on the median line. The muscle performance management device 100 may notify the user 110 of the timing to move his / her body via the smartphone. In this manner, the muscle performance acceleration data acquisition unit 201 acquires acceleration data while the user 110 is performing a predetermined motion. The predetermined motion includes, for example, walking, running, standing and sitting, sports motion, etc., but is not limited to these.

[0019] <Phase separation unit 202> The phase separation unit 202 separates a predetermined action into phases of the action based on the acquired muscle activity acceleration data. Here, separation into phases of the action will be described with reference to FIG. 2B. For example, consider a case where the user 110 is walking (220). In this case, the user 110 performs a series of actions from an initial contact (0%) where the right foot touches the ground, through an opposite initial contact (50%) where the opposite left foot touches the ground, to the next initial contact (100%) where the right foot touches the ground again. In response to this, the muscle activity state management device 100 does not detect the action of the user 110, but separates the action of walking into phases, and manages the muscle activity state in the separated phases of the action.

[0020] The phase of movement in the case of walking (220) can be divided into two phases, a stance phase (221) and a swing phase (222). That is, the phase called the stance phase is the period from when the right foot touches the ground at the initial contact (0%), when the left foot touches the ground for contralateral contact (50%), until the toes of the right foot kick off the ground (60%). The phase called the swing phase is the period from when the toes leave the ground (60%) until the next initial contact (100%) when the right foot touches the ground again. In this way, the phase of movement when the user 110 is walking can be divided into two phases (stance phase, swing phase).

[0021] Similarly, in the case of a standing position (230) in which the user 110 moves from sitting in a chair to standing up, the phase of the movement is divided into three phases as follows: a first phase (231) from the sitting position to the buttocks lifting off the floor, a second phase (232) from the buttocks lifting off the floor to the maximum dorsiflexion of the ankle joint, and a third phase (233) from the maximum dorsiflexion to the end of hip joint extension.

[0022] In this manner, the phase separating unit 202 analyzes the acquired muscle activity acceleration data and separates the motion of the user 110 into phases of the motion. Note that the phases to be separated are not limited to the above-mentioned walking cycle and standing up motion, and may be, for example, a sitting motion.

[0023] ≪Improvement area identification section 203≫ The improvement part identifying unit 203 identifies at least one of the body part and mental state of the user 110 that needs improvement by comparing the mental and physical function of the user 110 with a reference mental and physical function based on the muscle activity acceleration data for each of the separated movement phases. Here, the mental and physical function includes at least one of the range of motion of a joint, flexibility, balance, posture, left-right difference, distortion, and habit.

[0024] <Identifying body parts> For example, when muscle activity acceleration data is acquired while the user 110 is walking, the walking of the user 110 is analyzed from the acceleration data and compared with a reference walking. From the muscle activity acceleration data, data such as the pelvis angle, hip joint angle, knee joint angle, ankle joint angle, walking speed, and stride length can be obtained. Therefore, the improvement part identifying unit 203 compares data such as the pelvis angle obtained from the muscle activity acceleration data with the reference pelvis angle and the like to identify a body part of the user 110 that needs improvement. Note that the body parts identified by the improvement part identifying unit 203 are the pelvis, hip joint, knee joint, and ankle joint, but are not limited to these.

[0025] <Identifying mental states> The state of mind affects the walking speed, stride length, and the like. For example, when the user 110 is feeling depressed, the user 110 walks slowly, narrowing his stride length and slowing down his walking speed. From such a relationship between the state of mind and the actions of the user 110, the improvement part identifying unit 203 identifies the state of mind of the user 110 that needs improvement. Note that the state of mind identified by the improvement part identifying unit 203 includes, but is not limited to, joy, anger, sorrow, happiness, fatigue, stress, relaxation, and the like.

[0026] The analysis of the gait of the user 110 is performed, for example, as follows: The improvement part specifying unit 203 uses a multiple regression model calculated in advance to calculate the joint angle data of at least one of the right and left halves of the body in each phase of the movement (stance phase, swing phase) from the muscle activity acceleration data in each phase.

[0027] Here, the multiple regression model is calculated by performing principal component analysis and multiple regression analysis using muscle activity acceleration data measured in advance while walking for multiple subjects and joint angle data obtained by analyzing images of the subjects while walking as samples. Note that the muscle activity acceleration data and joint angle data used to calculate the multiple regression model include two phases of walking (stance phase and swing phase). In other words, the multiple regression model is not differentiated for each phase of walking, but is a single model common to both phases.

[0028] The joint angle data indicates the walking posture of the subject, represents the angles between the bones constituting the joints of the human body, and includes joint angle data of the right half of the body and joint angle data of the left half of the body. In this embodiment, the joint angle data is targeted at the lower half of the subject's body, i.e., the joints below the waist, specifically, the left and right pelvis, hip joints, knee joints, and ankle joints. Furthermore, the joint angle data includes the angle in the sagittal plane (angle seen from the side), the angle in the frontal plane (angle seen from the front), and the angle in the horizontal plane (angle seen from above), and the joint angle data has 4 locations x 3 directions = 12 measurement values ​​per measurement timing. Note that the analysis of the walking of the user 110 is not limited to the above example, and various methods can be used.

[0029] <Display control unit 204> The display control unit 204 displays at least one of the identified body parts requiring improvement and the state of mind. The identified body parts requiring improvement are displayed on a mobile terminal such as a smartphone or tablet terminal owned by the user 110. The display control unit 204 may display the body parts requiring improvement, for example, by displaying the walking status of the user 110. The display control unit 204 may also display the body parts requiring improvement, for example, by displaying the past walking status and the current walking status of the user 110. Alternatively, the display control unit 204 may display the walking status of the user 110 and an ideal walking status, thereby making it possible to recognize the difference between the ideal walking status.

[0030] 3A is a diagram showing an example of an acceleration data table 301 held by the muscle operation state management device 100. The acceleration data table 301 stores angle data 312 in association with acceleration data 311. The acceleration data 311 is acceleration data acquired from an acceleration sensor while the user 110 moves his / her body to perform a predetermined motion and is in a muscle operation state. The angle data 312 is data relating to the angle of each body part analyzed from the data acquired from the acceleration sensor. The improvement part identifying unit 203 then refers to the acceleration data table 301 to identify the angle data of the body part in the obtained acceleration data of the muscle operation state, and identifies the body part to be improved while the user 110 is in motion.

[0031] 3B is a diagram showing an example of a mental state determination table 302 included in the muscle performance management device 100. The mental state determination table 302 stores a mental state 322 in association with a body part 321. The body part 321 is the movement state of the body part of the user 110 analyzed from the muscle performance acceleration data. The mental state 322 indicates the psychological state of the user 110 according to the movement of the body part.

[0032] The hardware configuration of the muscle performance management device 100 will be described with reference to FIG. 4. The CPU (Central Processing Unit) 410 is a processor for arithmetic control, and executes programs to realize the various functional configurations of the muscle performance management device 100 in FIG. 2. The CPU 410 may have multiple processors and execute different programs, modules, tasks, threads, etc. in parallel. The ROM (Read Only Memory) 420 stores fixed data such as initial data and programs, and other programs. The network interface 430 communicates with other devices via a network. The CPU 410 is not limited to one, and may be multiple CPUs or may include a GPU (Graphics Processing Unit) for image processing. The network interface 430 preferably has a CPU independent of the CPU 410 and writes or reads transmitted / received data in an area of ​​the RAM (Random Access Memory) 440. It is also preferable to provide a DMAC (Direct Memory Access Controller) for transferring data between the RAM 440 and the storage 450 (not shown). Furthermore, the CPU 410 processes the data upon recognizing that the data has been received or transferred to the RAM 440. The CPU 410 also prepares the processing results in the RAM 440, and leaves the subsequent transmission or transfer up to the network interface 430 or DMAC.

[0033] The RAM 440 is a random access memory used by the CPU 410 as a temporary storage work area. The RAM 440 has a storage area reserved for storing data necessary for implementing this embodiment. The acceleration data 441 is acceleration data acquired from an acceleration sensor while the user 110 is moving his / her body and in a muscle working state. The separation phase 442 is data related to a phase of a predetermined movement separated based on the acquired muscle working state acceleration data. The reference mental and physical function data 443 is data that serves as a reference for identifying the physical function or mental state of the user 110 that needs to be improved. The improvement part data 444 is data related to the body part or mental state that needs to be improved. The display destination data 445 is data related to a terminal or the like that displays the identified body part or mental state that needs to be improved, for example, data for identifying a smartphone or the like owned by the user 110.

[0034] The transmitted / received data 446 is data that is transmitted and received via the network interface 430. The RAM 440 also has an application execution area 447 for executing various application modules.

[0035] Storage 450 stores a database, various parameters, or the following data or programs required to realize this embodiment. Storage 450 stores acceleration data table 301 and mental state determination table 302. Acceleration data table 301 is a table that manages the relationship between acceleration data 311 and angle data 312 shown in Fig. 3A. Mental state determination table 302 is a table that manages the relationship between body parts 321 and mental states 322 shown in Fig. 3B.

[0036] The storage 450 further stores a muscle activity acceleration data acquisition module 451, a phase separation module 452, an improvement part identification module 453, and a display control module 454. The muscle activity acceleration data acquisition module 451 is a module that acquires muscle activity acceleration data while the user 110 moves his / her body to perform a predetermined motion and is in a muscle activity state. The phase separation module 452 is a module that separates a predetermined motion into phases of the motion based on the acquired muscle activity acceleration data. The improvement part identification module 453 is a module that identifies at least one of the body part and mental state of the user 110 that needs improvement by comparing the mental and physical function of the user 110 with a reference mental and physical function for each of the separated phases of the motion. The display control module 454 is a module that displays at least one of the identified body part and mental state of the user that needs improvement. These modules 451 to 454 are read into the application execution area 447 of the RAM 440 by the CPU 410 and executed. The control program 455 is a program for controlling the muscle performance management device 100 as a whole.

[0037] The input / output interface 460 interfaces with input / output devices for input and output data. A display unit 461 and an operation unit 462 are connected to the input / output interface 460. A storage medium 464 may also be connected to the input / output interface 460. A speaker 463 serving as an audio output unit, a microphone (not shown) serving as an audio input unit, or a GPS position determination unit may also be connected. Note that the RAM 440 and storage 450 shown in FIG. 4 do not show programs and data relating to the general-purpose functions of the muscle operation state management device 100 or other feasible functions.

[0038] Next, a processing procedure of the muscle performance management device 100 will be described with reference to the flowchart shown in Fig. 5. This flowchart is executed by the CPU 410 in Fig. 4 using the RAM 440, and realizes each functional configuration of the muscle performance management device 100 in Fig. 2.

[0039] In step S501, the muscle activity state acceleration data acquisition unit 201 acquires acceleration data while the user 110 moves his / her body to perform a predetermined motion and is in a muscle activity state. In step S503, the phase separation unit 202 separates the predetermined motion into phases of motion based on the acquired muscle activity state acceleration data. In step S505, for each of the separated motion phases, at least one of a body part and a mental function of the user 110 that needs improvement is identified. In step S507, the improvement part identification unit 203 determines whether or not there is at least one of a body part and a mental function that needs improvement.

[0040] If there is a body part or the like that needs improvement (YES in step S507), the improvement part identifying unit 203 proceeds to step S509. In step S509, the display control unit 204 displays at least one of the identified body part or parts that need improvement and the mental state. The displayed content may be, for example, but is not limited to, the walking status of the user 110, the past and present walking status of the user 110, and the ideal walking status of the user 110. If there is no body part or the like that needs improvement (NO in step S507), the muscle operation state management device 100 ends the processing.

[0041] According to this embodiment, the body part and mental state to be improved are specified for each phase of the movement, so that the working state of the muscles can be more reliably managed and the improvement of the movement can be promoted. Furthermore, the user can easily recognize the body part and mental state to be improved, or the walking condition, the past and present walking conditions, and the ideal walking condition through the display screen, etc.

[0042] [Second embodiment] Next, a muscle performance management device according to a second embodiment of the present invention will be described with reference to Figs. 6 to 9. Fig. 6 is a block diagram for explaining the configuration of a muscle performance management device 600 according to this embodiment. The muscle performance management device 600 according to this embodiment differs from the first embodiment in that it includes an improvement method generation unit 601 and a proposal unit 602. As the other configurations and operations are similar to those of the first embodiment, the same configurations and operations are denoted by the same reference numerals and detailed description thereof will be omitted. The muscle performance management device 600 further includes an improvement method generation unit 601 and a proposal unit 602.

[0043] ≪Improvement method generation unit 601≫ The improvement method generating unit 601 generates an improvement method according to at least one of the identified body part and mental state of the user 110 that needs improvement. For example, if the body part that needs improvement is a forehead left-right difference of the pelvis, the improvement method generating unit 601 generates a walking style or exercise for correcting this as an improvement method. The improvement method may be, for example, a walking style or exercise (corrective exercise), sports, a method using a massage tool or training tool, a recommendation to apply a liniment, or the like.

[0044] Furthermore, the improvement method may be a recommendation of lower limb / below-navel wear (socks, support innerwear, shoes, insoles, etc.), a recommendation of existing health care products (blood circulation promoting products such as bath salts and heating devices), etc. Furthermore, the improvement method may be a recommendation of meals and drinks (calorie and PFC (Protein Fat Carbohydrate) balance, supplements, health-related commercially available drinks, etc.). Of the above-mentioned improvement methods, exercise and massage can be expected to improve the body part because the user 110 can feel an immediate sense of refreshment, and even with other improvement methods, a change (improvement) in the body part can be expected to change (improve) the mental state.

[0045] ≪Proposal Department 602≫ The suggestion unit 602 suggests the generated improvement method to the user 110. The suggestion unit 602 suggests the improvement method to the user 110, for example, by transmitting the generated improvement method to a mobile terminal such as a smartphone carried by the user 110. The improvement method is sent in a format such as a text message, a message with a link to a predetermined web page (URL: Uniform Resource Locator), or a text message with a video attached. However, the format of the proposed improvement method is not limited to the format shown here, as long as it is a method that can be suggested to the user 110.

[0046] Next, FIG. 7A is a diagram showing an example of a mental state improvement method table 701 possessed by the muscle performance state management device 600. The mental state improvement table 701 stores improvement and maintenance methods 711 in association with the mental state 322. The mental state 322 is the same as that described in FIG. 3B. The improvement and maintenance methods 711 are improvement methods or methods for maintaining the mental state 322, respectively. The improvement and maintenance methods 711 include walking style and others. For example, the improvement method generation unit 601 refers to the mental state improvement method table 701, and when the mental state 322 is enjoyable, generates as improvement and maintenance methods a walking style of taking large steps and sports and the like in order to maintain the mental state.

[0047] FIG. 7B is a diagram showing an example of a body part improvement table 702 included in the muscle operation state management device 600. The body part improvement method table 702 stores a phase 722 and an improvement and maintenance method 723 in association with a body part 721. The body part 721 is a body part that the user 110 needs to improve, and includes lower body parts such as the pelvis, hip joint, knee joint, and ankle joint. The phase 722 indicates an evaluation of the user 110's movement against a standard in a phase of movement. As shown in the figure, in the case of walking, the phase includes a stance phase and a swing phase. The improvement and maintenance method 723 is a method of improvement or the like for each body part when improvement or the like is required for the body part in each phase. The suggestion unit 602 then refers to the body part improvement table 702 and suggests an improvement method to the user 110.

[0048] The hardware configuration of the muscle operation state management device 600 will be described with reference to Fig. 8. The RAM 840 is a random access memory used by the CPU 410 as a work area for temporary storage. A storage area for storing data necessary for implementing this embodiment is secured in the RAM 840. The improvement method data 841 is data related to a method for improving a body part or the like that needs improvement, and is data related to movement patterns and exercises. The proposed destination data 842 is data related to a destination, such as a mobile terminal, to which the generated improvement method is proposed.

[0049] The storage 850 stores a database, various parameters, or the following data or programs required to realize this embodiment. The storage 850 stores a mental state improvement table 701 and a body part improvement table 702. The mental state improvement table 701 is a table that manages the relationship between the mental state 322 and the improvement and maintenance method 711 shown in Fig. 7A. The body part improvement table 702 is a table that manages the relationship between the body part 721 and the improvement and maintenance method 723, etc. shown in Fig. 7B.

[0050] The storage 850 further stores an improvement method generation module 851 and a proposal module 852. The improvement method generation module 851 is a module that generates an improvement method according to at least one of the identified body part and mental state of the user 110 that needs improvement. The proposal module 852 is a module that proposes the generated improvement method to the user 110. These modules 851 to 852 are read by the CPU 410 into the application execution area 447 of the RAM 840 and executed.

[0051] Next, a processing procedure of the muscle performance state management device 600 will be described with reference to the flowchart shown in Fig. 9. This flowchart is executed by the CPU 410 in Fig. 8 using the RAM 840, and realizes each functional configuration of the muscle performance state management device 600 in Fig. 6.

[0052] In step S901, the improvement method generating unit 601 generates an improvement method according to a body part that needs improvement, etc. In step S903, the proposing unit 602 proposes the generated improvement method to the user 110, and the process ends.

[0053] According to this embodiment, an improvement method is generated for the body part and mental state that the user wants to improve and is proposed to the user, so that the user can easily improve the body part and mental state by simply practicing the proposed improvement method.

[0054] [Third embodiment] Next, a muscle performance management device according to a third embodiment of the present invention will be described with reference to Fig. 10 and Fig. 11. Fig. 10 is a block diagram for explaining the configuration of a muscle performance management device 1000 according to this embodiment. The muscle performance management device 1000 according to this embodiment differs from the first and second embodiments in that it includes an image acquisition unit 1001. Other configurations and operations are similar to those of the first and second embodiments, so the same configurations and operations are denoted by the same reference numerals and detailed description thereof will be omitted.

[0055] The muscle operation state management device 1000 further includes an image acquisition unit 1001. The image acquisition unit 1001 acquires an image of the user 110 performing a predetermined movement. The acquired image may be any image as long as it shows the joint angles while the user 110 is performing the predetermined movement.

[0056] The phase separating unit 202 separates the predetermined motion into phases of the motion from the acquired muscle activity acceleration data and video. The improvement part identifying unit 203 identifies the body part and mental function of the user 110 that need improvement by comparing the mental and physical function of the user 110 with a reference mental and physical function based on the muscle activity acceleration data and video for each of the separated phases of the motion.

[0057] Here, examples of imaging devices that image the user 110 during a predetermined movement include a camera capable of capturing video images and a depth sensor (3D sensor) that can capture the shape of an object such as a person or an object in a three-dimensional form. In addition, as imaging devices, an AI (Artificial Intelligence) posture estimation engine that can detect a person's skeleton using a camera image without using a depth sensor or a device that can capture markerless motion capture video can be used. By using such devices, for example, the user 110 can easily estimate the angle of each joint while walking. Note that devices that can be used as imaging devices are not limited to the devices shown here.

[0058] In this way, it is possible to estimate the angles of each joint of user 110, etc., by using the acceleration data obtained from the acceleration sensor and further the data obtained from these imaging devices.

[0059] Therefore, the phase separating unit 202 separates the predetermined action into phases of the movement using the video thus obtained. Then, the improvement part specifying unit 203 specifies at least one of the body part and the mental state of the user 110 that needs improvement for each separated phase.

[0060] Next, a processing procedure of the muscle performance state management device 1000 will be described with reference to the flowchart shown in Fig. 11. This flowchart is executed by a CPU (not shown) using a RAM, and realizes each functional configuration of the muscle performance state management device 1000 in Fig. 10.

[0061] In step S1101, the image acquisition unit 1001 acquires an image of the user 110 performing a predetermined movement. In step S1103, the phase separation unit 202 separates the predetermined movement into phases of the movement based on the muscle activity acceleration data and the image. In step S1105, the improvement part identification unit 203 identifies a body part and a mental function of the user 110 that need improvement for each separated phase based on the acceleration data and the image.

[0062] According to this embodiment, in addition to acceleration data, video data is used to separate a user's specified movements into phases of the movement, so that the movements of the specified movements can be separated into phases with greater accuracy, and appropriate improvement methods can be proposed to the user.

[0063] Although the present invention has been described above with reference to the embodiments, the present invention is not limited to the above-described embodiments and can be modified as appropriate. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention. In addition, systems or devices that combine separate features included in each embodiment in any way are also included in the scope of the present invention.

[0064] The present invention may be applied to a system consisting of multiple devices, or to a single device. Furthermore, the present invention may be applied to a case where an information processing program for implementing the functions of the embodiment is supplied to a system or device and executed by a built-in processor. Therefore, the technical scope of the present invention includes a program installed on a computer to implement the functions of the present invention with a computer, a medium storing the program, a WWW (World Wide Web) server that downloads the program, and a processor that executes the program. In particular, at least a non-transitory computer readable medium storing a program that causes a computer to execute the processing steps included in the above-mentioned embodiment is included in the technical scope of the present invention.

Claims

1. a muscle activity acceleration data acquisition unit that acquires muscle activity acceleration data from an acceleration sensor disposed on a median line, which is the center line between the left and right sides of the user's body, while the user is moving their body to perform a predetermined movement and is in a muscle activity state; a phase separating unit that separates the predetermined motion into phases of the motion based on the acquired muscle activity acceleration data; an improvement part specifying unit that specifies at least one of the user's body part and mental state that need to be improved by comparing the user's mental and physical function with a reference mental and physical function based on the muscle activity acceleration data for each of the separated phases of the movement; a display control unit that displays at least one of the identified body part and mental state of the user that need improvement; A muscle activity status management device equipped with the device.

2. an improvement method generation unit that generates an improvement method according to at least one of the identified body part and mental state of the user that need improvement; a suggestion unit that suggests the generated improvement method to the user; The muscle performance monitoring device according to claim 1 , further comprising:

3. a video acquisition unit that acquires a video of the user performing the predetermined action, the phase separating unit separates the predetermined motion into phases of movement based on the acquired muscle activity acceleration data and the video; The muscle activity status management device of claim 1, wherein the improvement area identification unit identifies the user's body area and mental function that need improvement by comparing the user's mental and physical function with a reference mental and physical function based on the muscle activity status acceleration data and the video for each of the separated phases of the movement.

4. The muscle activity state management device according to any one of claims 1 to 3, wherein the phase of the movement includes at least one of a walking cycle, a standing up movement, and a sitting down movement.

5. The muscle activity state management device according to any one of claims 1 to 3, wherein the user's physical and mental functions include at least one of the range of motion of joints, flexibility, balance, posture, asymmetry, distortion, and habits.

6. The muscle performance management device according to claim 2 , wherein the improvement method generator generates corrective exercise as the improvement method.

7. a muscle activity acceleration data acquisition step of acquiring muscle activity acceleration data from an acceleration sensor disposed on a median line, which is a center line between the left and right sides of the user's body, while the user is moving their body to perform a predetermined movement and is in a muscle activity state; a phase dividing step of dividing the predetermined motion into phases of a movement based on the acquired muscle activity acceleration data; an improvement part identification step of identifying at least one of the user's body part and mental state that need to be improved by comparing the user's mental and physical function with a reference mental and physical function based on the muscle activity acceleration data for each of the separated phases of the movement; a display control step of displaying at least one of the identified body part and mental state of the user that need improvement; A muscle activity management method including:

8. a muscle activity acceleration data acquisition step of acquiring muscle activity acceleration data from an acceleration sensor disposed on a median line, which is a center line between the left and right sides of the user's body, while the user is moving their body to perform a predetermined movement and is in a muscle activity state; a phase dividing step of dividing the predetermined motion into phases of a movement based on the acquired muscle activity acceleration data; an improvement part identification step of identifying at least one of the user's body part and mental state that need to be improved by comparing the user's mental and physical function with a reference mental and physical function based on the muscle activity acceleration data for each of the separated phases of the movement; a display control step of displaying at least one of the identified body part and mental state of the user that need improvement; A muscle activity management program that causes a computer to execute the above.

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