Action improvement proposal device, action improvement proposal method, action improvement proposal management program, and action improvement proposal system

Abstract

This action improvement proposal device comprises: an action-related information acquisition unit for acquiring action-related information pertaining to a duration in which a user performs a prescribed action; a selection unit for selecting a physical health care proposal for improving the prescribed action; and a notification control unit for notifying a prescribed notification destination regarding the selected physical health care proposal. The selection unit selects the physical health care proposal using the acquired action-related information.

Description

Motion improvement proposal device, motion improvement proposal method, motion improvement proposal management program, and motion improvement proposal system

[0001] The present invention relates to an action improvement suggestion device, an action improvement suggestion method, an action improvement suggestion management program, and an action improvement suggestion system.

[0002] In the above technical fields, Patent Document 1 discloses a method for evaluating the walking posture of a subject over a certain period of time based on acceleration measured by an acceleration sensor attached to the midline of the subject's waist, and displaying the evaluation results in a chronological order (claim 1, etc.). Patent Document 2 discloses a method for calculating angle data of joints in the right half of the body and joints in the left half of the body using a multiple regression model from acceleration data of the subject while walking measured by an acceleration sensor (claim 1, etc.).

[0003] US2016038060A1 JP2024-173319A

[0004] The present invention relates to a motion improvement suggestion device. In one embodiment, the motion improvement suggestion device preferably includes: a motion-related information acquisition unit that acquires motion-related information while a user is performing a predetermined motion; a selection unit that selects a physical health care suggestion for improving the predetermined motion; and a notification control unit that notifies a predetermined notification destination of the selected physical health care suggestion. In one embodiment, the selection unit preferably selects the physical health care suggestion using the acquired motion-related information.

[0005] The present invention also relates to a motion improvement suggestion method. In one embodiment, the motion improvement suggestion method is preferably executed by an information processing device. In one embodiment, the motion improvement suggestion method preferably includes: a motion-related information acquisition step of acquiring motion-related information while a user is performing a predetermined motion; a selection step of selecting a physical health care suggestion for improving the predetermined motion; and a notification control step of notifying a predetermined notification destination of the selected physical health care suggestion. In one embodiment, in the selection step, the physical health care suggestion is selected using the acquired motion-related information.

[0006] The present invention also relates to a motion improvement suggestion system. In one embodiment, the motion improvement suggestion system preferably includes a user terminal and a motion improvement suggestion device connected to the user terminal via a wired or wireless connection. In one embodiment, the user terminal preferably includes a sensor that acquires data while the user is performing a predetermined motion. In one embodiment, the motion improvement suggestion device preferably includes: a selection unit that selects a physical health care suggestion for improving the predetermined motion; a notification control unit that notifies a predetermined notification destination of the selected physical health care suggestion; and a memory unit. In one embodiment, the motion-related information acquisition unit preferably acquires motion-related information for the predetermined motion using the motion data acquired by the sensor. In one embodiment, the memory unit preferably stores the motion data or the motion-related information. In one embodiment, the selection unit preferably selects the physical health care suggestion using at least one or more of the motion data or the motion-related information stored in the memory unit.

[0007] Furthermore, the present invention relates to a program for a user terminal. In one embodiment, the program for a user terminal is preferably used to have a user perform a predetermined action and acquire data related to the predetermined action of the user. In one embodiment, the program for a user terminal preferably causes an information processing device of the user terminal to execute an action preparation command step of commanding the user to prepare for the predetermined action, an action preparation completion determination step of determining whether the user is ready for the action, an action start command step of commanding the user to start the action, and a step of acquiring the data.

[0008] FIG. 1 is a diagram for explaining an overview of the operation of the proposal selection device according to the first embodiment of the present invention. FIG. 2 is a block diagram for explaining the configuration of the proposal selection device according to the first embodiment of the present invention. FIG. 3 is a diagram for explaining scoring criteria referred to by the proposal selection device according to the first embodiment of the present invention. FIG. 4 is a diagram for explaining scoring criteria referred to by the proposal selection device according to the first embodiment of the present invention. FIG. 5 is a diagram for explaining an example of a type determination table included in the proposal selection device according to the first embodiment of the present invention. FIG. 6 is a diagram for explaining the hardware configuration of the proposal selection device according to the first embodiment of the present invention. FIG. 7 is a flowchart for explaining the processing procedure of the proposal selection device according to the first embodiment of the present invention. FIG. 8 is a block diagram for explaining the configuration of the proposal selection device according to the second embodiment of the present invention. FIG. 9 is a diagram for explaining the hardware configuration of the proposal selection device according to the second embodiment of the present invention. FIG. 10 is a flowchart for explaining the processing procedure of the proposal selection device according to the second embodiment of the present invention. FIG. 11 is a diagram for explaining an overview of the operation of the action improvement suggesting device according to the third embodiment of the present invention. FIG. 12 is a block diagram for explaining the configuration of the action improvement suggesting device according to the third embodiment of the present invention. FIG. 13 is a diagram for explaining an example of a table included in the action improvement suggesting device according to the third embodiment of the present invention. FIG. 14 is a diagram for explaining the hardware configuration of the action improvement suggesting device according to the third embodiment of the present invention. FIG. 15 is a flowchart for explaining the processing procedure of the action improvement suggesting device according to the third embodiment of the present invention. FIG. 16 is a diagram showing the overall configuration of an action improvement suggesting device system according to a fifth embodiment of the present invention. FIG. 17 is a diagram showing the overall flow for a user according to the fifth embodiment of the present invention. FIG. 10 is a block diagram of a proposal selection system according to a fifth embodiment of the present invention. FIG. 11 is a diagram showing the configuration of a user DB according to a fifth embodiment of the present invention. FIG. 12 is a diagram for explaining an implementation status column in a user DB according to a fifth embodiment of the present invention. FIG. 13 is a flowchart for explaining the initial processing procedure of a user terminal according to a fifth embodiment of the present invention. FIG. 14 is a flowchart for explaining the second and subsequent processing procedures of a user terminal according to a fifth embodiment of the present invention. FIG. 15 is a flowchart for explaining the processing procedure of a server according to a fifth embodiment of the present invention. FIG. 16 is a flowchart for explaining the processing procedure of a server according to a fifth embodiment of the present invention.10 is a flowchart illustrating a processing procedure of a server according to a fifth embodiment of the present invention. FIG. 11 is a flowchart illustrating the operation of a motion-related information acquisition and transmission process according to a fifth embodiment of the present invention. FIG. 12 is a flowchart illustrating the operation of a motion-related information acquisition and transmission process according to a fifth embodiment of the present invention. FIG. 13 is a flowchart illustrating the operation of an averaging process according to a fifth embodiment of the present invention. FIG. 14 is a flowchart illustrating the operation of a care selection unit according to a fifth embodiment of the present invention. FIG. 15 is a flowchart illustrating the operation of the care selection unit according to a fifth embodiment of the present invention. FIG. 16 is a diagram illustrating the contents of a care suggestion candidate table used in a selection unit according to a fifth embodiment of the present invention. FIG. 17 is a diagram illustrating an overall flow for a user according to a sixth embodiment of the present invention. FIG. 18 is a block diagram of a suggestion selection system according to a sixth embodiment of the present invention. FIG. 19 is a diagram illustrating the configuration of a user DB according to a sixth embodiment of the present invention. FIG. 19 is a flowchart illustrating the processing procedure of a user terminal according to a sixth embodiment of the present invention. FIG. 19 is a flowchart illustrating the processing procedure of a user terminal according to a sixth embodiment of the present invention. FIG. 19 is a flowchart illustrating the processing procedure of a server according to a sixth embodiment of the present invention. FIG. 19 is a flowchart illustrating the processing procedure of a server according to a sixth embodiment of the present invention. FIG. 19 is a diagram illustrating an example of changes in data in a user DB according to a sixth embodiment of the present invention. FIG. 19 is a flowchart illustrating an example of a method for determining fifth motion-related information of a server according to a sixth embodiment of the present invention. FIG. 19 is a diagram illustrating a method for determining a type, which is motion-related information, according to a sixth embodiment of the present invention. FIG. 19 is a diagram illustrating the contents of a care suggestion candidate table used in a selection unit according to a sixth embodiment of the present invention. 13 is a flowchart illustrating a processing procedure of a server included in the proposal selection system according to the seventh embodiment of the present invention. Detailed Description of the Invention

[0009] The techniques described in Patent Documents 1 and 2 above are capable of determining whether the walking posture of the subject is good or bad, but are unable to make suggestions for improving the walking posture of the subject.

[0010] The following describes in detail exemplary embodiments of the present invention with reference to the drawings. The configurations, numerical values, processing flows, functional elements, and the like described in the following embodiments are merely examples, and are open to modification and alteration. The technical scope of the present invention is not limited to the following description.

[0011] In this specification, a "predetermined movement" refers to a predetermined, fixed movement, such as walking five to ten steps. There is no limit to the type of movement other than the walking movement shown here, as long as it is known or well-known to the user. The predetermined movement may be taught to the user in advance or at each measurement by using a video or by a trainer demonstrating a sample. In the present invention, the predetermined movement is performed multiple times, but there is a sufficient interval between each predetermined movement to allow for other movements, including pauses. The time interval is typically about one week to one month.

[0012] In this specification, "measuring a predetermined movement" refers to quantifying the position or movement of a specific part of the user's body, or quantifying changes in position or movement over time, by having the user hold a measuring device, or by attaching a measuring device to the body, or by filming the user's movements. Typically, this refers to obtaining a time series of acceleration data by fixing an acceleration sensor to one or more locations on the body and measuring the acceleration at the location where the acceleration sensor is fixed. In this specification, the raw data or its time series appearing as numerical values ​​obtained by measuring a predetermined movement is referred to as "movement data."

[0013] In this specification, "movement-related information" refers to information about a predetermined movement obtained by measuring a predetermined movement of a user. The movement-related information includes, for example, acceleration data and joint angle data of the user during the predetermined movement. That is, movement-related information includes movement data, but in this specification, "movement-related information" is used as a broader term that also includes feature quantities of the predetermined movement obtained from the movement data, or numerical values ​​and other parameters and classifications generated from the movement data or feature quantities of the predetermined movement. That is, "movement-related information" refers not only to movement information such as acceleration data and joint angle data that directly represent the predetermined movement of the user, but also to information that indirectly represents the predetermined movement that is obtained by measuring the predetermined movement of the user.

[0014] In this specification, "acquisition" does not only mean that an information processing device obtains "motion data" obtained by "measuring a predetermined motion," but also includes calculating, processing, and converting information in a predetermined manner. Therefore, "acquisition" also includes obtaining another piece of the same or different type of motion-related information from one or more pieces of motion-related information.

[0015] In this specification, "using action-related information" includes using one or more pieces of action-related information obtained from multiple predetermined actions. That is, it includes not only the case of using one piece of action-related information, but also the case of obtaining one piece of action-related information from multiple pieces of action data obtained from multiple predetermined actions and using that one piece of action-related information, and the case of obtaining two or more pieces of action-related information from multiple pieces of action data obtained from multiple predetermined actions and using that two or more pieces of action-related information. When using two or more pieces of action-related information, the types of action-related information may be the same or different. Furthermore, the acquired action-related information and the action-related information used do not have to be the same type. Please note that, for example, when acceleration data is acquired and type is used for selection, it may be expressed as "selecting using the acquired action-related information."

[0016] As used herein, "care information" refers to information that is expected or anticipated to contribute to the improvement of a predetermined movement and may be presented to the user. Examples of the content of "care information" include suggestions for exercises (care exercises) that are recommended for daily use to improve a predetermined movement, and suggestions for products (care products) that are recommended for daily use. Care exercises include stretching, walking, and other light exercises. Care products include orthotics such as insoles and supports, heating devices, bath additives, supplements, and health drinks. Care information does not necessarily need to include suggested wording; its content, i.e., the care exercises or care products, may simply be presented as items. As used herein, "physical health" refers to a desirable state for a predetermined movement. "Physical health care" refers to the use of care products or care exercises to improve a predetermined movement aimed at physical health, while "physical health care suggestions" refer to suggestions for physical health care presented to the user, which has a narrower meaning than the literal meaning of suggestions aimed at general health.

[0017] As used herein, an information processing device refers to a device that processes or converts data using electronic means, i.e., performs information processing, and is typically referred to as a computer. Various architectures, such as Harvard architecture and von Neumann architecture, are known, and computers equipped with dedicated arithmetic circuits such as GPUs are also known. However, the information processing device referred to herein includes known devices or devices that can be easily configured by those skilled in the art from known devices. Specifically, information processing devices include server devices, personal computers, and mobile devices such as smartphones. As can be seen from the example of a server device, an information processing device does not necessarily have to be a single computer device; it can also be composed of multiple computer devices. As used herein, an information processing system or system is a collection of information processing devices that logically connect one or more information processing devices, for example, via a network, to perform one or more integrated information processing operations. Whether each information processing device is owned by a different entity or a single entity, the system is defined as such as long as it collectively realizes the functions described herein. There are no restrictions on the number or combination of central processing units in each computer; single-core or multi-core systems are acceptable. There is no limit to the type or number of the main memory device and external memory device, but as described in the embodiment of the present invention, it is preferable to have so-called non-volatile memory, in which the memory contents are preserved regardless of whether or not an external power source is supplied.

[0018] In this specification, a program is a sequence of codes or numbers that can be read by an information processing device via electromagnetic means and is used to define the operation of the information processing device. Here, electromagnetic means includes electrical, magnetic, or optical means. A program is often stored on a storage medium that can be read by the information processing device, transmitted to the information processing device via a signal on a known transmission path, and defines the content of the information processing performed by the information processing device. In this specification, a module refers to a program or a collection of multiple programs configured to cause a CPU to execute a specific process. Typically, a module refers to a part of a larger program that realizes a certain set of functions. A module may also contain even smaller modules.

[0019] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. However, the configurations, numerical values, processing flows, functional elements, and the like described in the following embodiments are merely examples, and are free to be modified or changed. The technical scope of the present invention is not limited to the following description. In this specification, the term "system" includes one or more information processing devices. For example, a system can be configured by a single information processing device, or multiple information processing devices working together to perform functions such as a web server can also constitute a system. Furthermore, as described in the following embodiments, the "system" may include an information processing device that functions as a web server, one or more terminal devices, and one or more inspection devices.

[0020] [First Embodiment] A proposal selection device according to a first embodiment of the present invention will be described with reference to Figures 1 to 5. Figure 1 is a diagram for explaining an overview of the operation of the proposal selection device 100 according to this embodiment. The proposal selection device 100 is a device that selects a proposal for improving at least one of a first predetermined motion 102 and a second predetermined motion 103, based on first predetermined motion information 121, which is motion-related information while a user 101 is performing a first predetermined motion 102, and second predetermined motion information 131, which is motion-related information while the user 101 is performing a second predetermined motion 103.

[0021] The first predetermined motion 102 and the second predetermined motion 103 are motions performed by the same subject, the user 101. The first predetermined motion 102 and the second predetermined motion 103 are different motions. Here, "different motions" refers not only to different motions, such as walking and running, but also to the same motion but different ways of moving, or the same motion but different timings of performing the motion when viewed chronologically. Here, motion can be rephrased as the type of exercise, and "same motion but different ways of moving" can also be expressed as "same type of exercise but different ways of moving." Examples of the same motion but different ways of moving include different walking motions and different situations in which the motion is performed.

[0022] Examples of cases where the walking style is different even though the walking motion is the same include when the first predetermined motion 102 is the walking style at a certain point in time, and the second predetermined motion 103 is the walking style after using a product to change the walking style of the first predetermined motion 102, after receiving treatment from a masseuse or chiropractor, or after receiving advice to change the walking style of the first predetermined motion 102.

[0023] Examples of situations in which the movements are performed in different places or environments include when the first predetermined movement 102 and the second predetermined movement 103 are performed in different places or environments. Specifically, examples include cases in which the first predetermined movement 102 is a walking movement during commuting and the second predetermined movement 103 is a walking movement during sports, the first predetermined movement 102 is a walking movement when walking in town and the second predetermined movement 103 is a walking movement when walking in the mountains, the first predetermined movement 102 is a walking movement on sunny days and the second predetermined movement 103 is a walking movement on rainy days, etc.

[0024] An example of a case where the movements are the same but performed at different times along a timeline is when the first predetermined movement 102 is a walking movement and the second predetermined movement 103 is a walking movement that is started again after the first predetermined movement 102 is completed. When the first predetermined movement 102 and the second predetermined movement 103 are performed at different times, it is preferable that the second predetermined movement 103 be performed with an interval of several hours to several weeks after the first predetermined movement 102 is completed.

[0025] In the following, an example will be described in which the first predetermined motion 102 is the way the user 101 walks at a certain point in time, and the second predetermined motion 103 is the way the user 101 walks after using a product to change the first predetermined motion 102. The second predetermined motion 103 may be a motion in which the effect of using a product to change the first predetermined motion 102 is recognized, or may not be a motion in which the effect is recognized.

[0026] First, the proposal selection device 100 acquires first predetermined motion information 121 while the user 101 is performing a first predetermined motion 102. Typically, the user 101 is asked to walk while holding a user terminal such as a smartphone 104 equipped with an acceleration sensor, and acceleration data (raw data) acquired by the acceleration sensor is acquired as the first predetermined motion information 121. The smartphone 104 is placed on the midline of the user 101's body. The smartphone 104 may be held by the user 101 or may be attached to the user 101's body. Here, from the viewpoint of ease of measurement, it is preferable to place the user terminal such as the smartphone 104 at the navel or lower abdomen of the user's body, walk, and acquire acceleration data. Note that, when acquiring the predetermined motion, the number of steps and time the user walks can be set to a predetermined number of steps and time, but from the viewpoint of achieving both ease of measurement and accuracy, it is preferable that the number of steps be a few to several tens of steps.

[0027] When the proposal selection device 100 acquires first predetermined motion information 121, which is motion-related information, from a user terminal such as a smartphone 104, the proposal selection device 100 selects a first physical health care proposal 105 for improving the first predetermined motion 102. The proposal selection device 100 then notifies the selected first physical health care proposal 105 to a mobile terminal 107, such as a smartphone, carried by the user 101, which is the notification destination. The first physical health care proposal 105 is presented to the user 101 by being displayed on the screen of the mobile terminal 107.

[0028] Thereafter, the user 101 uses a product or service to change the first predetermined motion 102. After the user 101 uses the product or service to change the first predetermined motion 102, the proposal selection device 100 acquires second predetermined motion information 131, which is motion-related information. The second predetermined motion information 131 is acquired in the same manner as the first predetermined motion information 121. Specifically, the user 101 is made to walk while carrying an acceleration sensor, and acceleration data obtained by the acceleration sensor at this time is acquired as the second predetermined motion information 131. The first predetermined motion information 121 and the second predetermined motion information 131 may be acquired, for example, by the user 101 launching an application installed on the smartphone 104 and following the instructions of the application.

[0029] The proposal selection device 100 then selects a proposal for improving the second predetermined motion 103 using the first predetermined motion information 121 and the second predetermined motion information 131. Specifically, by comparing the first predetermined motion information 121 and the second predetermined motion information 131, it identifies an area of ​​the second predetermined motion 103 that needs further improvement. The "area that needs improvement" includes not only body parts of the user 101 but also motion characteristics, motion habits, and the like. The proposal selection device 100 then selects physical health care proposals 105 and 106 for improving the identified area. Specifically, the proposal selection device 100 selects at least one of a first physical health care proposal 105 for improving the first predetermined motion 102 and a second physical health care proposal 106 for improving the second predetermined motion 103. Furthermore, the proposal selection device 100 displays the selected physical health care proposals 105 and 106 on a display screen of a mobile terminal 107, such as a smartphone, carried by the user 101. By viewing the physical health care suggestions 105, 106 displayed on the display screen, the user 101 can recognize what he or she should do to further improve his or her walking style.

[0030] Next, the configuration of the proposal selection device 100 according to this embodiment will be described with reference to Fig. 2A. The proposal selection device 100 includes an action information acquisition unit 201, a first determination unit 202, a second determination unit 203, a first evaluation unit 204, a second evaluation unit 205, a selection unit 206, and a notification control unit 207.

[0031] The motion information acquisition unit 201 acquires first predetermined motion information 121 while the user 101 is moving his / her body to perform a first predetermined motion 102, and second predetermined motion information 131 different from the first predetermined motion information 121 while the user 101 is performing a second predetermined motion 103 different from the first predetermined motion 102.

[0032] As described above, the motion information acquisition unit 201 acquires first predetermined motion information 121 and second predetermined motion information 131 from the acceleration sensors. Specifically, as the first predetermined motion information 121, first muscle activity acceleration data is acquired 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 101, while the user 101 is moving his / her body to perform a first predetermined motion 102 and is in a muscle activity state. Furthermore, as the second predetermined motion information 131, second muscle activity acceleration data is acquired 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 101, while the user 101 is moving his / her body to perform a second predetermined motion 103 and is in a muscle activity state.

[0033] Here, the acceleration sensor used is, for example, one built into a mobile terminal such as a smartphone 104 carried by the user 101. However, the acceleration sensor may also be, for example, a wearable device worn on the body of the user 101, or a device such as a data logger that can record acceleration data.

[0034] For example, when the user 101 uses the smartphone 104 to record acceleration data during a predetermined movement, the user 101 first holds the smartphone 104 on the midline of his or her body. Note that the proposal selection device 100 may provide instructions to the user 101 via the smartphone 104, such as by voice or image, to ensure that the user 101 holds the smartphone 104 on the midline. Then, when data from the acceleration sensor maintains a constant value for a predetermined period of time, the proposal selection device 100 determines that the user 101 is holding the smartphone on the midline. The proposal selection device 100 can determine the direction of gravity by acquiring acceleration data in this state.

[0035] The user 101 holds the smartphone 104 on the midline and moves his / her body to perform a first predetermined motion 102 and a second predetermined motion 103. The proposal selection device 100 may notify the user 101 of the timing to move his / her body via the smartphone 104. In this manner, the motion information acquisition unit 201 acquires acceleration data while the user 101 is performing the first predetermined motion 102 and the second predetermined motion 103. The first predetermined motion 102 and the second predetermined motion 103 include, for example, walking, running, standing up and sitting down, and sports motions, but are not limited to these.

[0036] The motion information acquisition unit 201 may acquire the first muscle activity acceleration data from the acceleration sensor in real time, or may acquire data recorded in the acceleration sensor after the user 101 has completed the first predetermined motion 102. The motion information acquisition unit 201 may also acquire the first muscle activity acceleration data from the acceleration sensor via wireless or wired communication. Alternatively, the motion information acquisition unit 201 may acquire the first muscle activity acceleration data recorded in the acceleration sensor via a computer-readable recording medium. The second muscle activity acceleration data can also be acquired in the same manner as the first muscle activity acceleration data.

[0037] The first predetermined motion information 121 and the second predetermined motion information 131 may include upper body trunk angle data, jaw joint angle data, lower body joint angle data, movement speed, and walking data, respectively. When using upper body trunk angle data, the contents of, for example, Japanese Patent Application Publication No. 2013-143996 and Japanese Patent Application Publication No. 2023-11101 may be used, and when using jaw joint angle data, the contents of, for example, Japanese Patent Application Publication No. 2010-200856 may be used, as appropriate. From the perspective of understanding the health issues of the user 101, it is preferable that the first predetermined motion information 121 and the second predetermined motion information 131 each include at least one of these. Furthermore, from the perspective of specifically identifying areas requiring improvement, it is preferable that the first predetermined motion information 121 and the second predetermined motion information 131 each include at least lower body joint angle data, movement speed, and stride length. In addition, the upper body trunk angle data, jaw joint angle data, lower body joint angle data, movement speed and walking data can be obtained, for example, from the first muscle activity state acceleration data and the second muscle activity state acceleration data.

[0038] Here, the trunk angle data of the upper body and the jaw joint angle data typically include angle data in the sagittal plane, frontal plane, and horizontal plane, respectively.

[0039] The joint angle data of the lower body includes angle data of the pelvis, hip joints, knee joints, and ankle joints. It is preferable that the joint angle data of the lower body include all of these in order to identify in detail the parts that need improvement.

[0040] The walking data typically includes the number of steps, walking speed as a movement speed, and stride length. In addition to the above, the walking data also includes data on walking conditions such as stance phase and swing phase, walking angle, toe angle, walking cycle time, double support phase time, walking ratio, etc.

[0041] The first determination unit 202 determines which of a plurality of movement types the first predetermined movement 102 corresponds to, based on the joint angle data of the lower body, the movement speed, and the stride length, based on the first predetermined movement information 121. Examples of the plurality of movement types include the following types A to E. Note that the plurality of movement types are not limited to the following five types A to E, and may be four or less, or six or more.

[0042] <Type A: No problem> Type A has no particular problem with the way they walk, and walks normally.

[0043] <Type B: Shuffling type> Type B is a walking style with a narrow stride and a shuffling gait. Possible causes of Type B walking are a narrow range of motion in the ankles, flat feet with no arch in the feet, and an inability to lift the toes when walking. Also, Type B walking is thought to make it difficult for the calf muscles to move, which can lead to swelling due to restricted blood flow. Furthermore, overuse of the front of the thighs can make people more susceptible to fatigue and lower body weight.

[0044] <Type C: Posterior Pelvic Tilt Type> Type C is a walking style in which the pelvis is tilted backward, with a weak backward push-off and insufficient hip extension. The cause of Type C walking is thought to be the position of the pelvis, in other words, poor pelvic alignment, which inhibits movement. Also, Type C walking is thought to be prone to stiffness in the neck, shoulders, and back due to hunched posture. Furthermore, because the spine is no longer resting on the pelvis when the upper body is leaned forward, nerves are compressed and muscles become tense, which may result in a feeling of heaviness, fatigue, and pain in the lower back.

[0045] <Type D: Anterior Pelvic Tilt Type> Type D is a type in which the pelvis is tilted forward, resulting in chronic lower back pain. Possible causes of Type D walking are the position of the pelvis, in other words, poor pelvic alignment, excessive forward pelvic tilt resulting in arched lower back, and insufficient range of motion in the ankle or hip joints. Furthermore, Type D walking is thought to be prone to chronic lower back stiffness and pain due to a collapse of the S-curve of the spine, which places a heavy burden on the lower back. Poor circulation may also lead to swelling, and the stomach and buttocks may be prone to protruding.

[0046] <Type E: Common Pain Type (Knee)> Type E is a type in which knee pain is caused by walking style. A lack of range of motion in the ankle and hip joints is thought to be the cause of Type E walking style. Specifically, while balance should be maintained at three points: the ankle, knee, and hip joint, a lack of range of motion in the ankle and hip joints causes the person to walk in a way that protects the movement with the knee, placing a heavy burden on the knee. Furthermore, when walking with Type E walking style, stiff hip joints and limited calf movement are thought to make the person more susceptible to swelling due to poor circulation. Furthermore, stiff hip joints and limited movement of inner muscles are thought to cause trunk instability and fatigue.

[0047] Whether the first predetermined movement 102 falls into one of Types A to E can be determined based on the angle data of the pelvis, hip joints, knee joints, and ankle joints, the movement speed, and the stride length. Specifically, the angle data of the pelvis, hip joints, knee joints, and ankle joints, the movement speed, and the stride length are each scored, and the type of Type A to E to which the first predetermined movement 102 falls can be determined based on a combination of these scores. First, the scoring method will be described. The first discrimination unit 202 scores the angle data of the pelvis, hip joints, knee joints, and ankle joints, the movement speed, and the stride length based on the scoring criteria shown in FIGS. 2B and 2C .

[0048] A method for scoring the angle data of the pelvis, hip joint, knee joint, and ankle joint will be described below with reference to Figure 2B. When scoring the angle data of the pelvis, hip joint, knee joint, and ankle joint, amplitude data of the range of motion of the pelvis, hip joint, knee joint, and ankle joint is used. The amplitude data of the range of motion of the pelvis, hip joint, knee joint, and ankle joint is obtained from the angle data of the pelvis, hip joint, knee joint, and ankle joint.

[0049] <Pelvis Scoring Criteria 221> The first discrimination unit 202 determines a pelvis score 221b corresponding to the amplitude 221a of the range of motion of the pelvis by referring to the pelvis scoring criteria 221. Typically, the first discrimination unit 202 compares the amplitude data of the range of motion of the pelvis in the first predetermined movement 102 with the amplitude data of the range of motion of the pelvis that serves as a reference, and assigns a score of 1 if the amplitude 221a of the range of motion of the pelvis in the first predetermined movement 102 is between −15 degrees and 5 degrees (if the range of motion of the pelvis is within the reference range), assigns a score of 2 if the amplitude 221a is less than −15 degrees (if the pelvis is tilted too far forward), and assigns a score of 3 if the amplitude 221a is more than 5 degrees (if the pelvis is tilted too far backward).

[0050] <Hip Scoring Criteria 222> The first discrimination unit 202 determines a hip joint score 222b corresponding to the amplitude 222a of the range of motion of the hip joint by referring to the hip joint scoring criteria 222. Typically, the first discrimination unit 202 compares the amplitude data of the range of motion of the hip joint during the first predetermined movement 102 with the amplitude data of the range of motion of the hip joint that serves as a reference, and assigns a score of 1 if the amplitude 222a of the range of motion of the hip joint during the first predetermined movement 102 is 45 degrees or more (if the hip joint is being used well), a score of 2 if the amplitude 222a is 42 degrees or more but less than 45 degrees (if the hip joint is not being used well), a score of 3 if the amplitude 222a is 39 degrees or more but less than 42 degrees (if the hip joint is not being used as well), and a score of 4 if the amplitude 222a is 36 degrees or more but less than 39 degrees (if the hip joint is not being used as well).

[0051] <Ankle joint scoring criteria 223> The first discrimination unit 202 determines an ankle joint score 223b corresponding to the amplitude 223a of the range of motion of the ankle joint by referring to the ankle joint scoring criteria 223. Typically, the first discrimination unit 202 compares the amplitude data of the range of motion of the ankle joint during the first predetermined movement 102 with the amplitude data of the range of motion of the ankle joint as a reference, and assigns a score of 1 if the amplitude 223a of the range of motion of the ankle joint during the first predetermined movement 102 is 29 degrees or more (when the ankle joint is being used well), a score of 2 if the amplitude 223a is 27 degrees or more but less than 29 degrees (when the ankle joint is being used poorly), a score of 3 if the amplitude 223a is 25 degrees or more but less than 27 degrees (when the ankle joint is being used less), and a score of 4 if the amplitude 223a is 23 degrees or more but less than 25 degrees (when the ankle joint is being used less).

[0052] <Knee Joint Scoring Criteria 224> The first discrimination unit 202 determines a score 224b of the knee joint corresponding to the amplitude 224a of the range of motion of the knee joint by referring to the knee joint scoring criteria 224. Typically, the first discrimination unit 202 compares the amplitude data of the range of motion of the knee joint during the first predetermined movement 102 with the amplitude data of the range of motion of the knee joint that serves as a reference, and assigns a score of 1 if the amplitude 224a of the knee joint during the first predetermined movement 102 is less than −15 degrees (when the knee joint is being used well), a score of 2 if the amplitude 224a is −15 degrees or more but less than −13 degrees (when the knee joint is not being used well), a score of 3 if the amplitude 224a is −13 degrees or more but less than −11 degrees (when the knee joint is not being used as well), and a score of 4 if the amplitude 224a is −11 degrees or more (when the knee joint is not being used as well).

[0053] Hereinafter, a method for scoring the movement speed and stride length will be described in order with reference to FIG. 2C.

[0054] <Movement Speed ​​Scoring Criteria 225> The first discrimination unit 202 determines a movement speed score 225b corresponding to the movement speed 225a by referring to the movement speed scoring criteria 225. Typically, the movement speed of the first predetermined movement 102 is compared with a reference movement speed, and if the movement speed 225a during the first predetermined movement 102 is 125 cm / sec or more (if the movement speed 225a is equal to or greater than the reference speed), the score is set to 1; if the movement speed 225a during the first predetermined movement 102 is 115 cm / sec or more but less than 125 cm / sec (if the movement speed 225a is within the reference speed), the score is set to 2; and if the movement speed is less than 115 cm / sec (if the movement speed 225a is less than the reference speed), the score is set to 3.

[0055] <Stride Scoring Criteria 226> The first discrimination unit 202 determines a stride score 226b corresponding to the stride 226a by referring to the stride scoring criteria 226. Typically, the stride during the first predetermined movement 102 is compared with a reference stride, and if the stride 226a during the first predetermined movement 102 is 65 cm / sec or more (if the stride 226a is equal to or greater than the reference), the score is set to 1; if the stride 226a is 60 cm / sec or more but less than 65 cm / sec (if the stride 226a is within the reference), the score is set to 2; and if it is less than 60 cm / sec (if the stride 226a is less than the reference), the score is set to 3.

[0056] Next, a method for determining which of types A to E the first predetermined motion 102 falls into based on the score combination will be described. An example of the relationship between the score combination and types A to E is shown below. Type A: Pelvis score: 1, hip score: 1 or 2, knee score: 1 or 2, ankle score: 1 or 2, movement speed score: 1, stride length score: 1. Type B: Pelvis score: 1, 2 or 3, hip score: 1, 2, 3 or 4, knee score: 1, 2, 3 or 4, ankle score: 3 or 4, movement speed score: 3, stride length score: 3. Type C: Pelvis score: 3, hip score: 3 or 4, knee score: 2, 3 or 4, ankle score: 2, 3 or 4, movement speed score: 1 or 2, stride length score: 1 or 2. Type D: Pelvis score: 3, hip score: 2, 3 or 4, knee score: 1, 2, 3 or 4, ankle score: 1, 2, 3 or 4, movement speed score: 1 or 2, stride length score: 1 or 2. Type E: Pelvis score: 1; Hip score: 3 or 4; Knee score: 2, 3 or 4; Ankle score: 3 or 4; Movement speed score: 1, 2, 3 or 4; Step length score: 1, 2, 3 or 4

[0057] In this way, the first determination unit 202 determines which of types A to E the first predetermined motion 102 falls into. Note that the above-described classification of types is an example. Furthermore, if the first predetermined motion 102 falls into multiple types, the first determination unit 202 determines that the first predetermined motion 102 falls into the type assigned to the first alphabetical letter in alphabetical order from A to E.

[0058] The second determination unit 203 determines to which of a plurality of types of movements the second predetermined movement 103 belongs, based on the second predetermined movement information 131. The determination by the second determination unit 203 can be performed in the same manner as the determination by the first determination unit 202.

[0059] The first evaluation unit 204 calculates a first evaluation value for the first predetermined motion 102 based on the type of motion to which the first predetermined motion 102 applies. The first evaluation value is an index that indicates the degree to which improvement is required for each type of motion. For example, if the first predetermined motion 102 is Type B (Shuffling type), the larger the first evaluation value, the more severe the shuffling. The first evaluation value can be, for example, the total value of the scores 221b to 226b of the scoring criteria 221 to 226 described above.

[0060] The second evaluation unit 205 calculates a second evaluation value for the second predetermined motion 103 based on the type of motion to which the second predetermined motion 103 applies. Similar to the first evaluation value, the second evaluation value is an index that indicates the degree to which improvement is required for the type of motion. The second evaluation value can be calculated in the same manner as the first evaluation value.

[0061] The selection unit 206 selects physical health care suggestions 105, 106 for improving at least one of the first predetermined motion 102 and the second predetermined motion 103. Specifically, the selection unit 206 selects at least one of the first physical health care suggestion 105 for improving the first predetermined motion 102 and the second physical health care suggestion 106 for improving the second predetermined motion 103. When selecting the physical health care suggestions 105, 106, the selection unit 206 may (1) use only the first predetermined motion information 121 and the second predetermined motion information 131, (2) take into account the determination results of the first discrimination unit 202 and the second discrimination unit 203, or (3) take into account the first evaluation value and the second evaluation value. Each case will be described below.

[0062] (1) When Only the First Predetermined Motion Information 121 and the Second Predetermined Motion Information 131 Are Used: The selector 206 uses the first predetermined motion information 121 and the second predetermined motion information 131 to select physical health care suggestions 105, 106 for improving at least one of the first predetermined motion 102 and the second predetermined motion 103. Specifically, by comparing the first predetermined motion information 121 and the second predetermined motion information 131, changed and unchanged portions of the user's 101 walking style are identified after using a product for changing the first predetermined motion 102. When comparing the first predetermined motion information 121 and the second predetermined motion information 131, raw data, for example, pelvic angle data, may be compared. Then, the selector 206 selects the second physical health care suggestion 106 for improving the second predetermined motion 103 based on the changed and unchanged portions. Here, improving the second predetermined movement 103 includes not only improving the bad points of the second predetermined movement 103, but also further improving the good points and maintaining the current movement.

[0063] Physical health care suggestions 105, 106 include, for example, care products to be applied to the muscles and joints of the lower body, gait correction devices that have the effect of correcting walking style and posture (defined in this specification as gait correction effects), foods containing active ingredients, exercise, and rest.

[0064] Specific examples of care products applied to muscles and joints of the lower body include taping and sports leggings. Taping may be a taping method or taping tape.

[0065] Specific examples of gait correction devices include corsets for pelvic correction, supports, and insoles that are effective in correcting walking style and posture.

[0066] Typical examples of foods containing active ingredients include supplements and commercially available health drinks, and specific examples include foods containing milk-derived sphingomyelin, which has been reported to have the effect of improving motor function, foods containing GABA or citric acid, which have been reported to have the effect of improving fatigue, and foods containing chlorogenic acid, which has been reported to have the effect of improving sleep quality. As for the form of food, supplements are preferred from the viewpoint that nutrients can be easily replenished regardless of time or place.

[0067] Examples of exercise include stretching and yoga.

[0068] Resting can include, for example, long periods of sleep or short naps, such as power naps or afternoon naps, and can also include remaining still in a relaxed position, such as sitting or lying down.

[0069] The physical health care suggestions 105, 106 may include multiple suggestions. Among the specific examples described above, the physical health care suggestions 105 preferably include suggestions for insoles and / or exercises that contribute significantly to correcting walking style and posture, or suggestions for foods containing chlorogenic acid, which have been reported to improve sleep quality, and more preferably suggestions for insoles and / or exercises. Furthermore, if the physical health care suggestions 105 include insoles and exercises, the physical health care suggestions 105, 106 may also include the order in which to use the insoles and perform the exercises. From the perspective of providing the user with a greater sense of effectiveness, the order in which to use the insoles and perform the exercises is preferably exercise first, followed by insole use.

[0070] When the selector 206 selects both the first physical health care suggestion 105 and the second physical health care suggestion 106, the first physical health care suggestion 105 and the second physical health care suggestion 106 are preferably different. For example, the first physical health care suggestion 105 is exercise and the second physical health care suggestion 106 is insoles.

[0071] Note that the first physical health care suggestion 105 and the second physical health care suggestion 106 may be the same. For example, if the suggestion selection device 100 acquires the second predetermined motion information 131 after the user 101 makes the first physical health care suggestion 105 and selects the second physical health care suggestion 106 based on the second predetermined motion information 131, the first physical health care suggestion 105 may not have improved the user's health, and the second physical health care suggestion 106, which is the same as the first physical health care suggestion 105, may be selected again. In such a case, the first and second predetermined motions 102 and 103 may be the same. Even if the first and second predetermined motions 102 and 103 are different types of motions, the physical health care suggestions 105 and 106 for improving the first and second predetermined motions 102 and 103 may be the same, and the second physical health care suggestion 106 may be the same as the first physical health care suggestion 105.

[0072] (2) When the determination result of the first determination unit 202 and the determination result of the second determination unit 203 are taken into consideration The selection unit 206 may select the physical health care suggestions 105, 106 by taking into consideration at least one of the determination result of the first determination unit 202 and the determination result of the second determination unit 203. Examples of preferable physical health care suggestions 105, 106 for each type of movement are shown below. Type A: It is not necessary to select the physical health care suggestions 105, 106 Type B: An insole that can lift the arch of the foot and is not too high Type C: Adjusting the position and inclination of the foot with a heel cup Type D: An insole that supports the arch of the foot and can optimize the rocker function, an insole that can correct the movement of the foot, and a heel cup that can adjust the position and inclination of the foot Type E: An insole that supports the arch of the foot and can optimize the rocker function, and an insole that can correct the movement of the foot

[0073] If the first discrimination unit 202 and the second discrimination unit 203 discriminate differently, it is considered that the effect of the user 101 using the product for changing the first predetermined motion 102 is recognized, and the walking style for the second predetermined motion 103 is different from the walking style for the first predetermined motion 102. Therefore, it is considered that the part that needs improvement in the second predetermined motion 103 is different from the part that needs improvement in the first predetermined motion 102. For example, this is the case when the first predetermined motion 102 is Type B (Shuffling type) and the second predetermined motion 103 is Type C (Posterior pelvic tilt). In this way, when the parts that need improvement differ between the second predetermined motion 103 and the first predetermined motion 102, the second physical health care suggestion 106 selected by the selection unit 206 may be a product other than the product for changing the first predetermined motion 102.

[0074] Furthermore, if there is a difference in the walking style between the second predetermined motion 103 and the first predetermined motion 102, it is possible that the first predetermined motion 102 required improvement, whereas the second predetermined motion 103 is not particularly problematic and there is no particular area requiring improvement. For example, this may be the case when the first predetermined motion 102 is Type B (shuffling type) and the second predetermined motion 103 is Type A (no problem). In this way, when there is no particular area requiring improvement in the second predetermined motion 103, the second physical health care suggestion 106 selected by the selection unit 206 may include products for maintaining the second predetermined motion 103.

[0075] (3) When the first evaluation value and the second evaluation value are taken into consideration The selection unit 206 may select the physical health care suggestions 105, 106 by taking into consideration at least one of the first evaluation value and the second evaluation value. By taking into consideration the first evaluation value or the second evaluation value, it is possible to select the physical health care suggestions 105, 106 according to the degree of improvement needed for each movement type, thereby enabling the selection of more appropriate physical health care suggestions 105, 106. Below, a method for selecting the second physical health care suggestions 106 by taking into consideration the first evaluation value and the second evaluation value for each movement type will be described. Note that the first evaluation value and the second evaluation value here include not only the total value of each score, but also the value of each score, as described below.

[0076] <When the first predetermined movement 102 and the second predetermined movement 103 are both Type B (Shuffling)> From the first evaluation value and the second evaluation value, it is assumed that the following improvements and non-improvements in the second predetermined movement 103 compared to the first predetermined movement 102 are identified: (Improved) - Change from shuffling to walking with the heel landing (Not improved) - Narrow stride - Flat feet

[0077] The reason for the change from shuffling to landing on the heel in the second predetermined motion 103 as described above is believed to be that the user 101 used an insole that can lift the arch of the foot and is not too high, as the first physical health care suggestion 105 for improving the first predetermined motion 102. It is believed that the use of such an insole has enabled the user to lift the toes. Furthermore, it is believed that the range of motion of the ankle has increased, improving the rocker function.

[0078] Furthermore, as described above, the second predetermined movement 103 involves a change from shuffling to landing on the heel, which in turn activates the calves, and this is thought to have improved swelling. Furthermore, the improvement in gait is also thought to have reduced the strain on the front of the thighs.

[0079] Thus, while the second predetermined motion 103 has improved in that it has changed from shuffling to landing on the heel, the narrow stride and flat feet have not been improved, and the improvement is insufficient. Therefore, the selection unit 206 selects, as the second physical health care suggestion 106 for improving the second predetermined motion 103, for example, a higher insole that can lift the arch of the foot.

[0080] That is, when the discrimination result obtained from the first predetermined motion information 121 and the discrimination result obtained from the second predetermined motion information 131 are both the same Type B, the selector 206 of the proposal selection device 100 takes into consideration the first evaluation value and the second evaluation value to select the second physical health care proposal 106. More specifically, the selector 206 compares the first evaluation value with the second evaluation value, and when the second evaluation value has improved, selects, as the second physical health care proposal 106, an insole that is taller than the insole proposed in the first physical health care proposal 105.

[0081] As described above, the improvement in the second predetermined movement 103 was insufficient. Therefore, it is preferable to use the proposal selection device 100 to analyze the user's 101 walking style (third predetermined movement) after the user 101 performs the second physical health care proposal 106 for improving the second predetermined movement 103, and to confirm whether the third predetermined movement has improved. Specifically, the proposal selection device 100 acquires third predetermined movement information while the user 101 is performing the third predetermined movement. Furthermore, the proposal selection device 100 analyzes the third predetermined movement by determining which of movement types A to E the third predetermined movement corresponds to and calculating a third evaluation value for the third predetermined movement based on the acquired third predetermined movement information. The acquisition of the third predetermined movement information, the determination of which of the multiple movement types A to E the third predetermined movement corresponds to, and the calculation of the third evaluation value can be performed in the same manner as for the first predetermined movement 102 and the second predetermined movement 103. The analysis of the third predetermined movement is performed in the same manner as the first predetermined movement 102 and the second predetermined movement 103, for example, by regarding the third predetermined movement as the second predetermined movement 103 and the second predetermined movement 103 as the first predetermined movement 102.

[0082] The proposal selection device 100 considers the proposal to have been implemented after a predetermined period of time, for example, two weeks, has passed after notifying the second physical health care proposal 106, and sends a message to the smartphone 104 urging the user 101 to perform the third predetermined action, and acquires third predetermined action information from the third predetermined action performed by the user 101 in response to the sent message.

[0083] For example, suppose that as a result of determining which of a plurality of types A to E the third predetermined movement falls into, the third predetermined movement is also determined to be type B (shuffling type). Furthermore, suppose that a third evaluation value is calculated, and from the calculated third evaluation value, the following improvements and non-improvements in the third predetermined movement are identified with respect to the second predetermined movement 103: (Improved points) Improved stride length (increased walking speed) Improved flat feet (Non-improved points) None

[0084] As described above, the third predetermined movement is thought to be a way of using the body that is less tiring due to an appropriate gait and a moderate load, as a result of improving stride length and flat feet.

[0085] In this way, the stride length and flat feet have been improved for the third predetermined movement, and all areas that needed improvement have been improved. In other words, the third predetermined movement is an ideal movement and does not need to be improved further. Therefore, the proposal selection device 100 does not need to select a third physical health care proposal for the third predetermined movement. However, the proposal selection device 100 may select, for example, an insole that can strengthen the toes as the third physical health care proposal for maintaining the third predetermined movement.

[0086] Because the third predetermined movement is an ideal movement, there is no need to acquire predetermined movement information and analyze the walking style of the user 101 after the third predetermined movement information is acquired. However, it is also preferable to periodically acquire the predetermined movement of the user 101 and analyze the walking style. By doing so, it is possible to periodically check whether the user 101 is maintaining ideal movements. Furthermore, if the user 101 feels unwell with their own movements, the proposal selection device 100 may acquire predetermined movement information and analyze the walking style.

[0087] The above-described example of the third predetermined movement is an example in which the third predetermined movement is an ideal movement. However, if the third predetermined movement still has areas that need improvement, the proposal selection device 100 selects a third physical health care proposal for improving the third predetermined movement. Furthermore, predetermined movement information is acquired about the user's 101 walking style after the third predetermined movement information is acquired, and the walking style is analyzed. It is then preferable to repeat the selection of physical health care proposals, the acquisition of predetermined movement information, and the analysis of the walking style until all areas that need improvement are improved.

[0088] <When the first predetermined movement 102 and the second predetermined movement 103 are both Type C (posterior pelvic tilt)> From the first evaluation value and the second evaluation value, it is assumed that the following improvements and unimproved points are identified for the second predetermined movement 103 compared to the first predetermined movement 102. (Improved points) - Pelvic position is optimized (Unimproved points) - Backward kick is weak and hip extension is insufficient

[0089] As described above, the reason why the position of the pelvis is optimized in the second predetermined motion 103 is believed to be because the user 101 adjusts the position and inclination of the foot using the heel cup as the first physical health care suggestion 105 for improving the first predetermined motion 102. As a result, the foot position is believed to be optimized by the heel cup. Furthermore, it is believed that the increased heel height improved the backward tilt of the pelvis, and the alignment of the pelvis improved pronation.

[0090] Furthermore, in the second predetermined movement 103, as described above, the position of the pelvis is optimized, which is thought to improve posture and relieve stiffness.

[0091] In this way, while the position of the pelvis has been optimized for the second predetermined movement 103, the weak backward push-off and insufficient hip extension have not been improved, and there are still areas to be improved. Therefore, the selection unit 206 selects, as the second physical health care suggestion 106 for improving the second predetermined movement 103, for example, an insole that can strengthen the arch of the foot and support movement.

[0092] Furthermore, while forward and backward movement was hindered in the first predetermined movement 102 due to poor pelvic position, it is believed that, as described above, the pelvis is properly positioned in the second predetermined movement 103, allowing forward and backward movement. Therefore, supporting exercises are also considered effective as the second physical health care suggestion 106 for improving the second predetermined movement 103.

[0093] As described above, there are still areas for improvement in the second predetermined movement 103, so it is preferable to analyze the third predetermined movement using the proposal selection device 100 to check whether there are any areas for improvement in the third predetermined movement. For example, as a result of analyzing the third predetermined movement, it is assumed that the third predetermined movement is also type C, and the third evaluation value identifies the following improved and unimproved areas in the third predetermined movement compared to the second predetermined movement 103: (Improved areas) - Improved hip extension, stride length, and walking speed (Unimproved areas) - None

[0094] The reason why hip extension, stride length, and walking speed improved in the third predetermined movement as described above is thought to be because user 101 used an insole capable of strengthening the arch of the foot and supporting movement as second physical health care suggestion 106 for improving second predetermined movement 103. It is thought that the use of such an insole improved posture and expanded range of motion, thereby enabling dynamic movement.

[0095] Furthermore, as described above, the third predetermined movement is thought to result in improved hip extension, stride length, and walking speed, resulting in a more appropriate gait and moderate load, which allows the body to be used in a way that is less tiring.

[0096] As described above, the third predetermined movement has improved in terms of hip extension, stride length, and walking speed, and all areas requiring improvement have been improved. In other words, the third predetermined movement is an ideal movement and does not require further improvement. Therefore, the proposal selection device 100 does not need to select a third physical health care proposal for the third predetermined movement. However, the proposal selection device 100 may select, for example, insoles that can strengthen the toes as the third physical health care proposal for maintaining the third predetermined movement.

[0097] Furthermore, since the third predetermined movement is an ideal movement, there is no need to acquire predetermined movement information and analyze the walking style of the user 101 after the third predetermined movement information is acquired. However, it is also preferable to periodically acquire the predetermined movement of the user 101 and analyze the walking style in order to periodically check whether the user 101 is maintaining ideal movements. Furthermore, if the user 101 feels unwell with their own movements, etc., the proposal selection device 100 may acquire predetermined movement information and analyze the walking style.

[0098] The above-mentioned example of the third predetermined movement is an example in which the third predetermined movement is an ideal movement, but if the third predetermined movement still has areas that need improvement, it is preferable that the proposal selection device 100 repeats the selection of physical health care proposals, the acquisition of predetermined movement information, and the analysis of walking style until all areas that need improvement are improved.

[0099] <When the first predetermined movement 102 and the second predetermined movement 103 are both Type D (pelvic anterior tilt)> From the first evaluation value and the second evaluation value, it is assumed that the following improvements and unimproved aspects of the second predetermined movement 103 compared to the first predetermined movement 102 are identified. (Improved aspects) - The range of motion of the ankle joints and hip joints has increased. - The posture and pelvic alignment have been optimized. (Unimproved aspects) - Lower back pain has occurred.

[0100] As described above, the second predetermined movement 103 is thought to improve swelling as a result of the increased range of motion of the ankle and hip joints and the improved posture and pelvic alignment. It is also thought that the position of the stomach and buttocks has improved.

[0101] Thus, while the second predetermined movement 103 has improved in that the range of motion of the ankle and hip joints has increased and posture and pelvic alignment have been optimized, lower back pain still occurs and there are still areas that need improvement. Therefore, the selection unit 206 selects, for example, adjusting the position and inclination of the foot with a heel cup as the second physical health care suggestion 106 for improving the second predetermined movement 103.

[0102] As described above, there are still areas to be improved in the second predetermined motion 103, so it is preferable to analyze the third predetermined motion using the proposal selection device 100 to confirm whether there are any areas to be improved in the third predetermined motion. For example, as a result of analyzing the third predetermined motion, it is assumed that the third predetermined motion is also type D, and the third evaluation value identifies the following improved and unimproved aspects of the third predetermined motion compared to the second predetermined motion 103: (Improved aspects) - Lower back pain improved (Unimproved aspects) - None

[0103] As mentioned above, the third predetermined movement is thought to improve the lower back pain, which in turn reduces the chronic stiffness and pain in the lower back. Furthermore, it is thought that the appropriate gait and moderate load allow the body to be used in a way that is less tiring.

[0104] In this way, the third predetermined movement has improved the lower back pain and all areas that needed improvement have been improved. In other words, the third predetermined movement is an ideal movement and does not need to be improved further. Therefore, the proposal selection device 100 does not need to select a third physical health care proposal for the third predetermined movement. However, the proposal selection device 100 may select, for example, insoles that can strengthen the toes as the third physical health care proposal for maintaining the third predetermined movement.

[0105] Furthermore, since the third predetermined movement is an ideal movement, there is no need to acquire predetermined movement information and analyze the walking style of the user 101 after the third predetermined movement information is acquired. However, it is also preferable to periodically acquire the predetermined movement of the user 101 and analyze the walking style in order to periodically check whether the user 101 is maintaining ideal movements. Furthermore, if the user 101 feels unwell with their own movements, etc., the proposal selection device 100 may acquire predetermined movement information and analyze the walking style.

[0106] The above-mentioned example of the third predetermined movement is an example in which the third predetermined movement is an ideal movement, but if the third predetermined movement still has areas that need improvement, it is preferable that the proposal selection device 100 repeats the selection of physical health care proposals, the acquisition of predetermined movement information, and the analysis of walking style until all areas that need improvement are improved.

[0107] <When the first predetermined movement 102 and the second predetermined movement 103 are both Type E (Knee)> From the first evaluation result and the second evaluation result, it is assumed that the following improvements and unimproved points are identified for the second predetermined movement 103 compared to the first predetermined movement 102. (Improved points) - The range of motion of the ankle joint and hip joint has increased. (Unimproved points) - Knee pain has occurred.

[0108] As described above, the reason why the knee pain was not improved in the second predetermined movement 103 is thought to be that poor alignment such as bow legs or knock knees generates unnecessary moments, which tend to put stress on the area around the knees.

[0109] Furthermore, as described above, the second predetermined movement 103 is thought to improve swelling as a result of increasing the range of motion of the ankle joints and hip joints.

[0110] Thus, while the range of motion of the ankle and hip joints has increased in the second predetermined motion 103, pain in the knees still remains and there is still room for improvement. Therefore, the selection unit 206 selects, as the second physical health care suggestion 106 for improving the second predetermined motion 103, an insole that can support the outer arch of the foot and alleviate the pain, for example.

[0111] As described above, there are still areas to be improved in the second predetermined motion 103, so it is preferable to analyze the third predetermined motion using the proposal selection device 100 to confirm whether there are any areas to be improved in the third predetermined motion. For example, as a result of analyzing the third predetermined motion, it is assumed that the third predetermined motion is also type E, and the improved and unimproved aspects of the third predetermined motion compared to the second predetermined motion 103 are identified from the third evaluation value as follows: (Improved aspects) - Knee pain improved (Unimproved aspects) - None

[0112] In the third predetermined movement, as mentioned above, it is thought that the improvement in knee pain resulted in the stabilization of the trunk, which reduced fatigue. Furthermore, it is thought that the appropriate gait and moderate load allowed the body to be used in a way that was less tiring.

[0113] In this way, the third predetermined movement has improved the knee pain and all areas that needed improvement have been improved. In other words, the third predetermined movement is an ideal movement and does not need to be improved further. Therefore, the proposal selection device 100 does not need to select a third physical health care proposal for the third predetermined movement. However, the proposal selection device 100 may select, for example, insoles that can strengthen the toes as the third physical health care proposal for maintaining the third predetermined movement.

[0114] Furthermore, since the third predetermined movement is an ideal movement, there is no need to acquire predetermined movement information and analyze the walking style of the user 101 after the third predetermined movement information is acquired. However, it is also preferable to periodically acquire the predetermined movement of the user 101 and analyze the walking style in order to periodically check whether the user 101 is maintaining ideal movements. Furthermore, if the user 101 feels unwell with their own movements, etc., the proposal selection device 100 may acquire predetermined movement information and analyze the walking style.

[0115] The above-mentioned example of the third predetermined movement is an example in which the third predetermined movement is an ideal movement, but if the third predetermined movement still has areas that need improvement, it is preferable that the proposal selection device 100 repeats the selection of physical health care proposals, the acquisition of predetermined movement information, and the analysis of walking style until all areas that need improvement are improved.

[0116] The notification control unit 207 notifies a predetermined notification destination of the selected physical health care suggestions 105, 106. Examples of the predetermined notification destination include a user terminal such as a smartphone or tablet terminal owned by the user 101. By viewing the physical health care suggestions 105, 106 displayed on the display screen of the user terminal, the user 101 can recognize what he or she should do to further improve his or her walking style.

[0117] 3 is a diagram illustrating an example of a type determination table 301 included in the proposal selection device 100. The type determination table 301 is a table that stores movement types 312 in association with scores 311 of the angle data of the pelvis, hip joints, knee joints, and ankle joints, the movement speed, and the stride length. The scores 311 are the scores of the angle data of the pelvis, hip joints, knee joints, and ankle joints, the movement speed, and the stride length. The movement types 312 are types A to E of movements corresponding to the angle data of the pelvis, hip joints, knee joints, and ankle joints, the movement speed, and the stride length. The first determination unit 202 and the second determination unit 203 refer to the type determination table 301 to determine to which of the multiple movement types A to E the first predetermined movement 102 and the second predetermined movement 103 belong.

[0118] The hardware configuration of the proposal selection device 100 will be described with reference to FIG. 4 . The CPU (Central Processing Unit) 410 is a processor for arithmetic control, and by executing programs, it realizes the various functional components of the proposal selection device 100 shown in FIG. 2A . 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, as well as other programs. The network interface 430 communicates with other devices via a network. The CPU 410 is not limited to one CPU, and may include multiple CPUs or a GPU (Graphics Processing Unit) for image processing. The network interface 430 preferably has a CPU independent of the CPU 410 and writes and reads transmitted and received data to and from an area of ​​the RAM (Random Access Memory) 440. It is also desirable to provide a DMAC (Direct Memory Access Controller) (not shown) that transfers data between the RAM 440 and the storage 450. Furthermore, the CPU 410 processes the data upon recognizing that data has been received or transferred to the RAM 440. The CPU 410 also prepares the processing results in the RAM 440, and leaves subsequent transmission or transfer to the network interface 430 or the DMAC.

[0119] The RAM 440 is a random access memory used by the CPU 410 as a work area for temporary storage. The RAM 440 has a storage area reserved for storing data necessary for implementing this embodiment. The first predetermined motion information data 441 is data of the first predetermined motion information 121 acquired by the motion information acquisition unit 201. The second predetermined motion information data 442 is data of the second predetermined motion information 131 acquired by the motion information acquisition unit 201. The proposal data 443 is data of the physical health care proposals 105, 106 selected by the selection unit 206.

[0120] The transmitted / received data 444 is data transmitted and received via the network interface 430. The RAM 440 also has an application execution area 445 for executing various application modules.

[0121] The storage 450 stores a database, various parameters, or the following data or programs required to implement this embodiment. The storage 450 stores a type determination table 301. The type determination table 301 is a table that manages the relationship between the score 311 and the action type 312 shown in FIG. 3 .

[0122] The storage 450 further stores a motion information acquisition module 451, a first determination module 452, a second determination module 453, a first evaluation module 454, a second evaluation module 455, a selection module 456, and a notification control module 457. The motion information acquisition module 451 is a module that acquires first predetermined motion information 121 and second predetermined motion information 131. The first determination module 452 is a module that determines to which of a plurality of motion types A to E the first predetermined motion 102 applies based on the first predetermined motion information 121. The second determination module 453 is a module that determines to which of a plurality of motion types A to E the second predetermined motion 103 applies based on the second predetermined motion information 131. The first evaluation module 454 is a module that calculates a first evaluation value based on the motion type to which the first predetermined motion 102 applies. The second evaluation module 455 is a module that calculates a second evaluation value based on the type of movement to which the second predetermined movement 103 applies. The selection module 456 is a module that selects physical health care suggestions 105, 106 for improving at least one of the first predetermined movement 102 and the second predetermined movement 103. The notification control module 457 is a module that notifies predetermined notification destinations of the selected physical health care suggestions 105, 106. These modules 451 to 457 are read into the application execution area 445 of the RAM 440 by the CPU 410 and executed. The control program 458 is a program for controlling the entire proposal selection device 100.

[0123] The input / output interface 460 interfaces input / output data with input / output devices. 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 include programs or data related to the general-purpose functions of the proposal selection device 100 or other feasible functions.

[0124] Next, a processing procedure of the proposal selection 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 proposal selection device 100 in Fig. 2A.

[0125] In step S501, the motion information acquisition unit 201 acquires first predetermined motion information 121 while the user 101 is performing the first predetermined motion 102. In step S503, the first determination unit 202 determines to which of a plurality of motion types A to E the first predetermined motion 102 corresponds, based on the first predetermined motion information 121. In step S505, the first evaluation unit 204 calculates a first evaluation value based on the motion type to which the first predetermined motion 102 corresponds. In step S507, the motion information acquisition unit 201 acquires second predetermined motion information 131 while the user 101 is performing the second predetermined motion 103. In step S509, the second determination unit 203 determines to which of a plurality of motion types A to E the second predetermined motion 103 corresponds, based on the second predetermined motion information 131. In step S511, the second evaluation unit 205 calculates a second evaluation value based on the type of movement to which the second predetermined movement 103 applies. In step S513, the selection unit 206 selects physical health care suggestions 105, 106 for improving at least one of the first predetermined movement 102 and the second predetermined movement 103. In step S515, the notification control unit 207 notifies a predetermined notification destination of the selected physical health care suggestions 105, 106. In step S517, the proposal selection device 100 determines whether to reselect a physical health care suggestion for the movement of the user 101 after the user 101 performs the physical health care suggestions 105, 106 selected in step S513, for example, the third predetermined movement. For example, if there are no remaining improvements to be made in the second predetermined movement and all improvements have been made, the proposal selection device 100 determines not to select a physical health care suggestion. However, if there are remaining improvements to be made in the second predetermined movement, the proposal selection device 100 determines to select a physical health care suggestion.

[0126] If the selection is to be performed again (step S517: YES), the proposal selection device 100 returns to step S507 and repeats steps S507 to S517. Specifically, the second predetermined action 103 is replaced with the third predetermined action, and the first predetermined action 102 is replaced with the second predetermined action 103, and steps S507 to S517 are performed.

[0127] If the selection is not to be performed again (step S517: NO), the proposal selection device 100 ends the process.

[0128] According to this embodiment, physical health care suggestions 105, 106 are selected to improve at least one of the first predetermined motion 102 and the second predetermined motion 103, so that suggestions can be made to improve the motion of the user 101.

[0129] Furthermore, the proposal selection device 100 can select the physical health care proposals 105, 106 by taking into consideration the type of at least one of the first predetermined motion 102 and the second predetermined motion 103, by taking into account the determination results of at least one of the first determination unit 202 and the second determination unit 203. This allows the physical health care proposals 105, 106 to be selected with even greater accuracy.

[0130] Furthermore, by taking into consideration the evaluation value calculated by at least one of the first evaluation unit 204 and the second evaluation unit 205, the proposal selection device 100 can select physical health care proposals 105, 106 after taking into account the degree to which improvement is needed in the type of at least one of the first predetermined motion 102 and the second predetermined motion 103. This allows the physical health care proposals 105, 106 to be selected with even greater accuracy.

[0131] In this embodiment, a physical health care suggestion is selected based on the result of comparing the first predetermined motion information 121 and the second predetermined motion information 131. Alternatively, a physical health care suggestion may be selected by referring to a table using motion feature values ​​or scores of motion feature values ​​obtained from each of the first predetermined motion information 121 and the second predetermined motion information 131, or a physical health care suggestion may be selected based on the total or average value of the motion feature values, or a physical health care suggestion may be selected using a learning model that has learned combinations of both values ​​and proven physical health care suggestions.

[0132] In this embodiment, of the first physical health care suggestion 105 and the second physical health care suggestion 106, only the second physical health care suggestion is selected using both the first predetermined motion information 121 and the second predetermined motion information 131, but this is not limiting. For example, the first predetermined motion 102 and the second predetermined motion 103 may be different motions, and both the first predetermined motion information 121 and the second predetermined motion information 131 may be acquired, and using both the motion information 121 and 131, only the first physical health care suggestion 105 or both the first physical health care suggestion 105 and the second physical health care suggestion 106 may be selected. Alternatively, the first physical health care suggestion 105 may be selected using only the first predetermined motion information 121, without using the second predetermined motion information 131.

[0133] Second Embodiment Next, a proposal selection device 600 according to a second embodiment of the present invention will be described with reference to Fig. 6. Fig. 6 is a block diagram illustrating the configuration of the proposal selection device 600 according to this embodiment. The proposal selection device 600 according to this embodiment differs from the first embodiment in that it further includes a reception unit 601 and a determination unit 602. Since 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.

[0134] The receiving unit 601 receives input of a first implementation status of the first physical health care suggestion 105 for improving the first predetermined movement selected by the selecting unit 206. For example, the first implementation status is input as "◯" when the first physical health care suggestion 105 is implemented, and as "X" when the first physical health care suggestion 105 is not implemented. The first implementation status may include, for example, the date on which the first physical health care suggestion 105 was implemented. Furthermore, if the degree of implementation of the first physical health care suggestion 105 can be quantitatively evaluated, the first implementation status may also include the degree of implementation. The degree of implementation may be the degree of implementation per day, or the degree of implementation over a period of multiple days. For example, if the first physical health care suggestion 105 is stretching, examples of the degree of implementation include the number of times or duration of stretching.

[0135] The method by which the user 101 inputs the first implementation status is not particularly limited, and various known methods can be used. For example, a user interface such as a drop-down list, radio buttons, toggle switches, or check boxes may be displayed on the display screen of the user terminal, and the implementation status may be input via the user interface. Alternatively, the user 101 may tap on a date on which the first physical health care suggestion 105 was implemented on a calendar showing a schedule displayed on the display screen of the user terminal, thereby inputting that the first physical health care suggestion 105 was implemented on the date on which the user tapped the calendar.

[0136] The determination unit 602 determines whether the user 101 has implemented the first physical health care suggestion 105 based on the first implementation status. For example, when the first implementation status is "◯", the determination unit 602 determines that the user 101 has implemented the first physical health care suggestion 105, and when the first implementation status is "X", the determination unit 602 determines that the user 101 has not implemented the first physical health care suggestion 105. Note that if the first physical health care suggestion 105 is expected to have an improvement effect on a first predetermined movement by, for example, performing the first physical health care suggestion 105 a predetermined number of times or for a predetermined period, the determination unit 602 determines that the first physical health care suggestion 105 has been implemented when the first physical health care suggestion 105 has been performed a predetermined number of times or for a predetermined period.

[0137] When the determination unit 602 determines that the user 101 has performed the first physical health care suggestion 105, the selection unit 206 selects a second physical health care suggestion 106 for improving the second predetermined motion 103. The first physical health care suggestion 105 and the second physical health care suggestion 106 are preferably different. Specifically, it is preferable that the first physical health care suggestion 105 is exercise and the second physical health care suggestion 106 is insoles. Note that the first physical health care suggestion 105 and the second physical health care suggestion 106 may be the same. Furthermore, when the determination unit 602 determines that the user 101 has not performed the first physical health care suggestion 105, the selection unit 206 does not select the second physical health care suggestion 106.

[0138] When the determination unit 602 determines that the user 101 has performed the first physical health care suggestion 105, the suggestion selection device 600 may notify the user 101 that the user 101 is requested to perform the second predetermined motion 103. In this case, when the user 101 performs the second predetermined motion 103 in accordance with the received notification, the motion information acquisition unit 201 acquires second predetermined motion information 131.

[0139] The hardware configuration of the proposal selection device 600 will be described with reference to Figure 7. The RAM 740 is a random access memory used by the CPU 410 as a temporary storage work area. The RAM 740 has a storage area reserved for storing data necessary for implementing this embodiment. The implementation status data 741 is data on the first implementation status of the first physical health care proposal 105 accepted by the accepting unit 601.

[0140] The storage 750 stores a database, various parameters, and the following data or programs required to implement this embodiment. The storage 750 also stores a reception module 751 and a determination module 752. The reception module 751 is a module that receives input of the first implementation status of the first physical health care suggestion 105. The determination module 752 is a module that determines whether the user 101 has implemented the first physical health care suggestion 105 based on the input implementation status. These modules 751 to 752 are read into the application execution area 445 of the RAM 740 by the CPU 410 and executed.

[0141] Next, the processing procedure of the proposal selection device 600 will be described with reference to the flowchart shown in Fig. 8. This flowchart is executed by the CPU 410 in Fig. 7 using the RAM 740, and realizes each functional configuration of the proposal selection device 600 in Fig. 6.

[0142] In step S801, the selection unit 206 selects a first physical health care suggestion 105. The selection of the first physical health care suggestion 105 is typically performed based on the determination result of the first determination unit 202 and the evaluation result of the first evaluation unit 204. The first physical health care suggestion 105 is preferably, for example, stretching. In step S803, the notification control unit 207 notifies a predetermined notification destination of the selected first physical health care suggestion 105. In step S805, the determination unit 602 determines whether the user 101 has implemented the first physical health care suggestion 105 based on the input first implementation status of the first physical health care suggestion 105. If the user 101 has implemented the first physical health care suggestion 105 (step S805: YES), in step S807, the notification control unit 207 notifies the user 101 of a request to perform the second predetermined action 103. The notification in step S807 is made after a predetermined period of time, for example, three weeks, has elapsed since the previous notification (the notification in step S803). If the user 101 has not implemented the first physical health care suggestion 105 (step S805: NO), the suggestion selection device 600 repeats step S805. Note that in step S805, it is preferable to periodically prompt the user 101 to input the implementation status, for example, by making a weekly inquiry via the smartphone 104.

[0143] In this embodiment, in step S513, the selection unit 206 selects a second physical health care suggestion 106. The second physical health care suggestion 106 is preferably, for example, an insole. In step S515, the notification control unit 207 notifies a predetermined notification destination of the selected second physical health care suggestion 106. In this embodiment, the second physical health care suggestion 106 is notified regardless of whether or not there is an area for improvement remaining in the second predetermined motion 103. Note that, when there is no area for improvement remaining in the second predetermined motion 103, the second physical health care suggestion 106 is typically intended to maintain a state in which there is no area for improvement remaining in the second predetermined motion 103.

[0144] In step S517, the suggestion selection device 600 determines whether to reselect a physical health care suggestion for the third predetermined motion of the user 101 after the user 101 performs the second physical health care suggestion 106 selected in step S513. Specifically, if there are areas for improvement remaining in the second predetermined motion 103 and the second physical health care suggestion 106 is one for which the implementation status should be checked, the suggestion selection device 600 determines to reselect a physical health care suggestion. On the other hand, if there are no areas for improvement remaining in the second predetermined motion 103 and the second physical health care suggestion 106 is one for which the implementation status does not need to be checked, the suggestion selection device 600 determines not to select a physical health care suggestion. An example of a case in which the second physical health care suggestion 106 does not need to be checked is when the second physical health care suggestion 106 is one for maintaining a state in which there are no areas for improvement remaining in the second predetermined motion 103.

[0145] If the selection is to be performed again (step S517: YES), the proposal selection device 600 returns to step S801 and repeats the steps from step S801 onward. Specifically, the second predetermined action 103 is replaced with the third predetermined action, and the first predetermined action 102 is replaced with the second predetermined action 103, and the steps from step S805 onward are performed.

[0146] If no reselection is to be performed (step S517: NO), the proposal selection device 600 ends the process.

[0147] According to this embodiment, as with the proposal selection device 100 of the first embodiment, it is possible to make proposals for improving the movements of the user 101. Furthermore, the proposal selection device 600 selects the second physical health care proposal 106 after the user 101 makes the first physical health care proposal 105, and therefore it is possible to select the second physical health care proposal 106 after taking into consideration the effectiveness of the first physical health care proposal 105. Therefore, it is possible to select a more effective proposal as the second physical health care proposal 106. A notification of the second physical health care proposal 106 may be sent by email to the user's smartphone, etc.

[0148] Third Embodiment A motion improvement suggestion device according to a third embodiment of the present invention will be described with reference to FIGS. 9 to 13. FIG. 9 is a diagram illustrating an overview of the motion improvement suggestion device 100. The motion improvement suggestion device 100 is a device that selects a suggestion for improving the gait of a user 101. In other words, the motion improvement suggestion device 100 also functions as a suggestion selection device that selects a motion improvement suggestion. Specifically, when the user 101 walks while carrying a smartphone 104, an acceleration sensor included in the smartphone 104 measures acceleration data 111 of the user 101 while walking. The motion improvement suggestion device 100 acquires the measured acceleration data 111 and stores the acquired acceleration data 111. The motion improvement suggestion device 100 then selects a suggestion 105 for improving the gait of the user 101 using the acquired acceleration data 111 and at least one of past acceleration data 112. The motion improvement suggestion device 100 notifies the smartphone 104 of the selected suggestion 105. The user 101 implements the notified suggestion 105 displayed on the display screen of the smartphone 104, thereby improving the gait of the user 101. In this embodiment, the suggestion 105 is an insole, and implementing the suggestion 105 means using the insole.

[0149] Next, the configuration of the action improvement proposing device 100 will be described with reference to Fig. 10. The action improvement proposing device 100 includes an action-related information acquiring unit 201, a storage unit 208, a selecting unit 206, and a notification control unit 20.

[0150] The motion-related information acquisition unit 201 acquires motion-related information while the user 101 is performing a predetermined motion. In this embodiment, the predetermined motion is walking, and the motion-related information is raw data, i.e., acceleration data 111. Here, the raw data is a time-series of numerical values ​​measured by a sensor.

[0151] As described above, the motion-related information acquisition unit 201 acquires, as motion-related information, acceleration data 111 measured by an acceleration sensor built into the smartphone 104. The smartphone 104 is placed on the midline of the body of the user 101. The smartphone 104 may be held by the user 101's hand or attached to the user's body by a belt or other device. Here, from the viewpoint of ease of measurement, it is preferable that the user walks with the smartphone 104 placed at the navel or lower abdomen of the user 101, and acquire the acceleration data 111. Note that when acquiring the acceleration data 111, the number of steps and the time the user 101 walks can be any number and time, but from the viewpoint of achieving both ease of measurement and accuracy, it is preferable that the number of steps be a few to several tens of steps.

[0152] The motion-related information acquisition unit 201 may acquire the acceleration data 111 from the acceleration sensor in real time, or may acquire the acceleration data 111 recorded in the acceleration sensor after the user 101 has finished walking. The motion-related information acquisition unit 201 may also acquire the acceleration data 111 from the acceleration sensor via wireless communication or wired communication. Alternatively, the motion-related information acquisition unit 201 may acquire the acceleration data 111 recorded in the acceleration sensor via a predetermined computer-readable recording medium.

[0153] The storage unit 208 stores movement-related information of a predetermined movement performed by the user 101. For example, if the user 101 has walked three times in the past and the movement-related information acquisition unit 201 has acquired acceleration data 111 for each of the three walks, the storage unit 208 stores the acceleration data 112 for the three walks. In other words, the storage unit 208 stores the acceleration data 112, which is past movement-related information. Note that the movement improvement suggestion device 100 does not necessarily need to have the storage unit 208 built in. The storage unit 208 may be storage external to the movement improvement suggestion device 100. The storage unit 208 may be storage on the cloud or storage included in the smartphone 104 of the user 101.

[0154] The selection unit 206 selects a physical health care suggestion for improving a predetermined movement. The selection unit 206 selects the physical health care suggestion using the currently acquired movement-related information and at least one of the past movement-related information stored in the storage unit 208. In this embodiment, as described above, the newly acquired movement-related information is the acceleration data 111, and the movement-related information stored in the storage unit 208 is the past movement information, that is, the acceleration data 112.

[0155] The selection unit 206 selects a physical health care suggestion using the walking feature amount extracted from the acceleration data 111 and 112. In this embodiment, the selection unit 206 extracts the feature amount.

[0156] The number of pieces of past acceleration data 112 read from the storage unit 208 and used by the selection unit 206 to extract features may be one or more. The past acceleration data 112 used by the selection unit 206 to extract features is preferably the most recent one of the past acceleration data 112 stored in the storage unit 208. In other words, the past acceleration data 112 used by the selection unit 206 to extract features is preferably the most recent one selected from the acceleration data 112 stored in the storage unit 208. When the past acceleration data 112 used by the selection unit 206 to extract features is more recent, the extracted features reflect more recent data, thereby improving the selection of physical health care suggestions.

[0157] Here, the acceleration data 112 stored in the storage unit 208 may include data that is inappropriate for use in selecting physical health care suggestions, such as outlier data that has extreme values ​​compared to other data. For example, if the user 101 walks multiple times and the conditions for the walks are different from those of the others, the acceleration data 112 for the walks may be outlier data. Examples of different conditions include different locations or different times of day when the walks are performed.

[0158] When the selection unit 206 reads and selects past acceleration data 112 to be used for extracting features from the acceleration data 112 stored in the memory unit 208, it is preferable to remove outlier data from the viewpoint of improving the selection of physical health care suggestions.

[0159] The selection unit 206 processes the acceleration data 111, 112 as preprocessing before extracting feature amounts from the acceleration data 111, 112. The method for this will be described below.

[0160] The selection unit 206 normalizes the newly acquired acceleration data 111. Normalization is performed, for example, in units of walking cycles. Normalizing in units of walking cycles means aligning the walking cycle of the acceleration data 111 to a predetermined walking cycle. For example, if the walking cycle of the acceleration data 111 is longer than the predetermined walking cycle, the acceleration data 111 is compressed to correspond to the predetermined walking cycle. On the other hand, if the walking cycle of the acceleration data 111 is shorter than the predetermined walking cycle, the acceleration data 111 is expanded. It is preferable that the storage unit 208 stores acceleration data 111 that has been normalized to align the walking cycle. If the past acceleration data 112 stored in the storage unit 208 has not been normalized, the past acceleration data 112 is also read from the storage unit and normalized in the same way as the acceleration data 111. Performing the normalization process makes the subsequent statistical processing of the acceleration data 111 and the acceleration data 112 more appropriate. This allows for more accurate selection of physical care suggestions using the acceleration data 111 and 112.

[0161] The currently acquired and normalized acceleration data 111 and at least one of the past acceleration data 112 stored in the storage unit 208 are subjected to statistical processing. In this embodiment, the statistical processing is performed by averaging. That is, the normalized acceleration data 111 and one or more past acceleration data 112 are averaged to obtain averaged acceleration data. As described above, the acceleration data 111 and 112 are normalized, so the accuracy of the result obtained by the averaging processing (averaged acceleration data) can be improved. Note that the statistical processing is not limited to averaging and can be changed depending on the type of motion-related information.

[0162] A feature of the user 101's walking is extracted from the averaged acceleration data. For example, the symmetry of joint movements (posture) and the magnitude of joint movements (movement) are determined from the averaged acceleration data, and the determined posture and movement are each divided into three stages, for example, A to C. As a method for determining posture and movement from acceleration data, for example, the technology disclosed in Japanese Patent Application Laid-Open No. 2024-173319 can be used. An example of the criteria for division is as follows:

[0163] <Posture> The ratio of the difference between the maximum values ​​of left and right acceleration to the maximum value of the larger side Posture A: Less than 5% (good symmetry) Posture B: Between 5% and 15% (normal symmetry) Posture C: More than 5% (poor symmetry)

[0164] <Movement> Ratio of joint movement angle of lower limb (knee) to the reference value Movement A: +5% or more Movement B: +5% to -5% Movement C: -5% or less

[0165] The selection unit 206 classifies the walking of the user 101 into one of a plurality of types according to the walking feature amount, and selects a physical health care suggestion using the classification result. A method for selecting a physical health care suggestion using the classification result will be described below.

[0166] The selection unit 206 classifies the gait of the user 101 into seven types, types 1 to 7, as follows, for example. Note that the type classification method is not limited to the seven types 1 to 7 below, and may be six or less, or eight or more, depending on how the feature amounts are classified. Posture A, movement A; type "1" Posture A, movement B; type "2" Posture A, movement C; type "2" Posture B, movement A; type "3" Posture B, movement B; type "4" Posture B, movement C; type "6" Posture C, movement A; type "3" Posture C, movement B; type "5" Posture C, movement C; type "7"

[0167] An overview of each type is as follows. <Type "1": Ideal walking type> Type "1" is an ideal state in which the person has correct posture and good mobility in the lower limbs when walking. <Type "2": Posture stable type> Type "2" is a state in which the person has good posture but noticeable instability in walking movements. <Type "3": Movement stable type> Type "3" is a state in which the person's walking movements are smooth but their posture tends to deteriorate. <Type "4": Standard type> Type "4" is a state in which the quality of posture and walking is average and no particular problems are observed. <Type "5": Posture unstable type> Type "5" is a state in which the person's walking movements are normal but their posture tends to deteriorate. <Type "6": Walking unstable type> Type "6" is a state in which the person has normal posture but their walking movements are unstable or awkward. <Type "7": Posture and walking problem type> Type "7" is a state in which there are problems with both posture and walking movements.

[0168] The selection unit 206 uses the classified type to select a suggestion 105 (physical health care suggestion). In addition to insoles, the physical health care suggestion may include, for example, care products applied to the muscles and joints of the lower body, gait correction devices that have the effect of correcting walking style and posture (defined as gait correction effects in this specification), foods containing active ingredients, exercise, and rest.

[0169] Specific examples of care products applied to muscles and joints of the lower body include taping tape and sports leggings. When proposing taping tape, a taping method may also be proposed.

[0170] Specific examples of gait correction devices include corsets for pelvic correction, supports, and insoles that are effective in correcting walking style and posture.

[0171] Typical examples of foods containing active ingredients include supplements and commercially available health drinks, and specific examples include foods containing milk-derived sphingomyelin, which has been reported to have the effect of improving motor function, foods containing GABA or citric acid, which have been reported to have the effect of improving fatigue, and foods containing chlorogenic acid, which has been reported to have the effect of improving sleep quality. As for the form of food, supplements are preferred from the viewpoint that nutrients can be easily replenished regardless of time or place.

[0172] Examples of exercise include stretching and yoga.

[0173] Resting can include, for example, long periods of sleep or short naps, such as power naps or afternoon naps, and can also include remaining still in a relaxed position, such as sitting or lying down.

[0174] The physical health care recommendations may include only one recommendation or may include multiple recommendations.

[0175] The notification control unit 207 notifies a predetermined notification destination of the selected physical health care suggestion. Examples of the predetermined notification destination include a user terminal such as a smartphone 104 or a tablet terminal carried by the user 101. By viewing the physical health care suggestion displayed on the display screen of the smartphone 104, for example, the user 101 recognizes what he or she should do to improve his or her walking.

[0176] 11 shows an example of a suggestion table 300 included in the motion improvement suggestion device 100. The suggestion table 300 stores suggestions 313 in association with types 312. The types 312 are predetermined types into which the walking of the user 101 is classified. The suggestions 313 are preferred physical health care suggestions corresponding to the types 312, and examples of suggestions include products and exercises stored for each type. The selection unit 206 refers to the suggestion table 300 to select physical health care suggestions to be presented.

[0177] The hardware configuration of the operation improvement proposal device 100 will be described with reference to FIG. 12 . The CPU (Central Processing Unit) 410 is a processor for arithmetic control, and by executing programs, realizes the various functional components of the operation improvement proposal device 100 shown in FIG. 10 . Multiple CPUs 410 may be provided, each executing different programs, modules, tasks, threads, etc. in parallel. The ROM (Read Only Memory) 420 stores fixed data such as system parameters, a boot loader, and other programs. The network interface 430 communicates with other devices via a network. It is preferable that the network interface 430 has a CPU independent of the CPU 410 and writes and reads transmitted and received data to and from an area of ​​the RAM (Random Access Memory) 440. It is desirable to provide a direct memory access controller (DMAC) (not shown) that transfers data between the RAM 440 and the storage 450. The CPU 410 processes the data after recognizing that data has been received or transferred to the RAM 440. The CPU 410 also prepares the processing results in the RAM 440, and leaves subsequent transmission or transfer to the network interface 430 or the DMAC.

[0178] The RAM 440 is used by the CPU 410 as a temporary storage work area. A storage area for storing data and programs necessary for implementing this embodiment is allocated in the RAM 440 as needed. The motion-related information data 441 is the acceleration data 111 and past acceleration data 112 acquired by the motion-related information acquisition unit 201. The proposal data 442 is data on physical health care proposals selected by the selection unit 206.

[0179] The transmitted / received data 443 is data transmitted and received via the network interface 430. The RAM 440 also has an application execution area 444 for reading various application modules from the storage 450 and executing them.

[0180] The storage 450 stores the following data and programs required to implement this embodiment. The storage 450 stores a proposal table 300. The proposal table 300 is a table that manages the relationship between the type 312 and the proposal 313 shown in FIG. 11 .

[0181] The storage 450 further stores a motion-related information acquisition module 451, a selection module 456, and a notification control module 457. The motion-related information acquisition module 451 is a module that acquires the acceleration data 111. The selection module 456 is a module that selects a physical health care suggestion using the acceleration data 111 and 112. The notification control module 457 is a module that notifies a predetermined notification destination of the selected physical health care suggestion. These modules 451, 456, 457, and a control program 458 are read into the application execution area 444 of the RAM 440 by the CPU 410 and executed. The control program 458 is a program for controlling the entire motion improvement suggestion device 100.

[0182] The input / output interface 460 interfaces input / output data with input / output devices. 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 may also be connected. Note that the RAM 440 and storage 450 shown in FIG. 12 do not include programs or data related to the general-purpose functions of the operation improvement proposal device 100 or other feasible functions.

[0183] Next, the processing procedure of the operation improvement suggestion device 100 will be described with reference to the flowchart shown in FIG. 13. This flowchart is executed by the CPU 410 in FIG. 12 using the RAM 440, and realizes the respective functional components of the operation improvement suggestion device 100 in FIG. 10. That is, each of the units shown in the functional components of FIG. 10 is realized by the CPU 410 and the respective modules in the RAM 440. As can be seen from this, FIG. 10 is a conceptual diagram, and therefore, it is not necessary that all of the components shown in FIG. 10 be present in the operation improvement suggestion device 100 at a particular time. This is obvious to those skilled in the art, and applies not only to this embodiment but also to all embodiments in this specification, but will be described here just to be sure.

[0184] In step S301, the motion-related information acquisition unit 201 acquires acceleration data 111 while the user 101 is walking. In step S303, the selection unit 206 normalizes the acquired acceleration data 111. In step S305, the selection unit 206 performs statistical processing, specifically averaging processing, on the normalized acceleration data 111 and past acceleration data 112 read from the storage unit 208. In step S307, the selection unit 206 extracts features of the user 101's gait from the acceleration data after averaging processing. In step S309, the selection unit 206 classifies the user 101's gait into a predetermined type based on the extracted features. In step S311, the selection unit 206 selects a physical health care suggestion based on the classified predetermined type. In step S313, the notification control unit 207 notifies the smartphone 104 of the selected physical health care suggestion.

[0185] According to this embodiment, physical health care suggestions are selected using the currently acquired acceleration data 111 and past acceleration data 112, so that more appropriate suggestions can be made to improve the movements of the user 101.

[0186] In addition, when the user 101 uses the motion improvement suggestion device 100 for the first time, or when no past acceleration data 112 exists, a physical health care suggestion may be selected using only the newly acquired acceleration data 111.

[0187] Furthermore, the selection unit 206 may use, as the motion-related information used to select physical health care suggestions, unprocessed motion-related information that is in the state acquired by the motion-related information acquisition unit 201. For example, in this embodiment, the acceleration data 111, 112 is subjected to processing such as normalization and statistical processing, but physical health care suggestions may be selected using the acceleration data 111, 112 without performing these processing on the acceleration data 111, 112.

[0188] At least one of the acceleration data 112 stored in the storage unit 208 and used by the selection unit 206 may be the most recent acceleration data 112 among the acceleration data 112 stored in the storage unit 208. In other words, it is not necessarily necessary to remove outlier data from the stored past acceleration data 112.

[0189] In this embodiment, the acceleration sensor is built into the smartphone 104, but it may also be built into other mobile terminals such as a tablet terminal. Furthermore, the acceleration sensor may be a wearable device worn on the body of the user 101, or a device such as a data logger that can record acceleration data.

[0190] The predetermined motion is not limited to walking, but may be, for example, running, standing up or sitting down, sports motion, or the like.

[0191] The movement-related information is not limited to acceleration data. For example, the movement-related information may be joint angle data. Furthermore, the movement-related information may be a numerical representation of the movement of a specific part of the body of the user 101.

[0192] The movement-related information stored in the storage unit 208 may be raw data before processing, normalized data, or statistically processed data. If statistically processed data is stored, the selection unit 206 preferably selects physical health care suggestions using raw data such as newly acquired acceleration data 111 and the stored statistically processed movement-related information. The storage unit 208 may also store classified types and selected physical health care suggestions as movement-related information. In this case, the statistical processing varies depending on the movement-related information.

[0193] [Fourth Embodiment] Next, an action-improvement proposing device 100 according to a fourth embodiment of the present invention will be described. The action-improvement proposing device 100 according to this embodiment differs from the above-described third embodiment in the functions of the storage unit 208 and the selection unit 206 in the following respects. The configuration of the action-improvement proposing device 100 according to this embodiment is the same as the configuration of the action-improvement proposing device 100 according to the third embodiment shown in FIG. 10. Since the functions of the storage unit 208 and the selection unit 206 are the same as those of the third embodiment, detailed description thereof will be omitted.

[0194] The storage unit 208 stores the motion-related information (acceleration data 111) acquired by the motion-related information acquisition unit 201, as well as physical health care suggestions selected using the motion-related information and the implementation status of the physical health care suggestions by the user 101. In this embodiment, the physical health care suggestions are product suggestions such as insoles and supports.

[0195] The storage unit 208 stores, as the implementation status, whether or not a product suggestion has been made. "Product suggestion has been made" means that the user 101 has purchased the suggested product, and "product suggestion has not been made" means that the user 101 has not purchased the suggested product.

[0196] The selection unit 206 selects a physical health care suggestion according to the implementation status stored in the storage unit 208. The operation of the selection unit 206 will be described below.

[0197] The selection unit 206 first selects a product proposal using the acceleration data 111 acquired by the motion-related information acquisition unit 201. Here, the selection may be made using only the currently acquired acceleration data 111, or may be made using the currently acquired acceleration data 111 and at least one of the stored acceleration data 112.

[0198] Next, the selection unit 206 determines whether the user 101 is implementing the same product proposal as the product proposal selected using the acceleration data 111. Specifically, the determination is made by referring to the product proposals and implementation status stored in the storage unit 208. If the user 101 is implementing the same product proposal as the product proposal selected using the acceleration data 111, the selection unit 206 newly selects another product proposal or a physical health care proposal other than the product proposal, such as exercise.

[0199] According to this embodiment, a physical health care suggestion is selected depending on the implementation status of physical health care suggestions that have been made in the past, so that the selection of a physical health care suggestion can be made more appropriately.

[0200] Even if user 101 makes the same product proposal as the one selected using acceleration data 111, if a certain period of time has passed since the previous product proposal, the product proposal selected using acceleration data 111 may be notified to user 101's smartphone 104.

[0201] Fifth Embodiment Next, a motion improvement suggestion system 1000 according to a fifth embodiment of the present invention will be described with reference to FIGS. 14 to 24. FIG. 14 shows an overview of the motion improvement suggestion system 1000 according to this embodiment. The motion improvement suggestion system 1000 is realized as an information processing system having multiple information processing devices, including a server 1001, which is the motion improvement suggestion device of the present invention, a user terminal (smartphone 1004), and a network 603 connecting these. Here, the server 1001 may be a single computer device or a collection of multiple computer devices. The motion improvement suggestion system 1000 may include any number of smartphones 1004, but it is preferable to have one smartphone 1004 per user, i.e., one per user ID. The hardware configuration of the computer device or smartphone 1004 that constitutes the server 1001 is well known to those skilled in the art, and therefore, a description thereof will be omitted. The user terminal does not have to be a smartphone 1004; however, in this embodiment, since the motion data is acceleration data, it is preferable for the user terminal to have a built-in acceleration sensor. Furthermore, for example, a user terminal can be configured by combining a so-called smart watch (not shown) worn on the user's wrist or a pedometer (not shown) worn on the waist with the smartphone 1004. It is preferable to use the Internet or other public line networks as the network 603, since there is no need to impose restrictions on the location where the user can perform a predetermined operation.

[0202] The following describes user operations and the like when using the motion improvement suggestion system 1000 of this embodiment. In this embodiment, as shown in FIG. 15 , the user installs an application program (hereinafter also referred to as an app) ( S701 ), practices a predetermined motion according to instructions from the user terminal ( S703 ), and then performs a practice completion confirmation step ( S705 ) in which the user responds to a query from the user terminal as to whether the predetermined motion has been mastered. In the practice completion confirmation step ( S705 ), if the user inputs a response indicating that the predetermined motion has been mastered into the user terminal ( YES in the practice completion confirmation step ( S705 )), an initial care suggestion is displayed on the terminal ( initial care suggestion reception step ( S707 )). As will be described in detail later, the initial suggestion is selected based on motion data obtained from repeated practice of the predetermined motion. The user then executes the care suggestion according to the suggestion ( care suggestion execution step ( S709 )). In response to a query from the terminal ( care implementation inquiry step ( S711 )), if the user responds that the suggested care has been performed, the terminal prompts the user to perform the predetermined motion again (the next predetermined motion). When the user performs the predetermined movement again (predetermined movement re-execution step S713), the user receives a new care suggestion (care re-suggestion) at the terminal (care suggestion re-receiving step S715). The user repeats steps S711 to S715 until the predetermined movement is deemed acceptable, in other words, until no improvement is required. As will be described later, the user can understand whether or not improvement is required based on the display content shown in S715. Although omitted from FIG. 15 to avoid complexity, in this embodiment, if the user's initial predetermined movement is an ideal predetermined movement and no improvement is required, the process ends with initial care suggestion receiving step S707. In this embodiment, the predetermined movement is walking. That is, both the initial predetermined movement and the re-predetermined movement are the same walking movement.

[0203] An outline of the information processing procedure in the server (motion improvement suggestion device) 1001 in this embodiment will be described with reference to Figures 15 and 16. Time-series acceleration data (raw data) measured by the smartphone 1004 in step S703 for practicing a predetermined motion and step S713 for re-executing a predetermined motion in Figure 15 is received by the server 1001, normalized by a normalization unit 801 for each walking cycle, and then temporarily stored in a "0th time before" area (see Figure 17A) of a user database (DB) 802, which is a storage unit that stores motion-related information. The normalized motion data newly stored in the user DB 802 is passed to the motion-related information acquisition unit 803 together with saved past motion data. In the motion-related information acquisition unit 803, the averaging processing unit 831 first averages the newly acquired and stored motion data with past motion data. Then, the feature extraction unit 832 extracts feature amounts of a predetermined motion from the averaged motion data, and passes the extracted feature amounts to the evaluation unit 833. The evaluation unit 833 uses the passed feature amounts to determine a type (walking type), which is the motion-related information of this embodiment. That is, in this embodiment, the motion-related information acquisition unit 803 includes the averaging processing unit 831, the feature extraction unit 832, and the evaluation unit 833. Note that, as in the first embodiment, the motion data is data normalized to a periodic unit by expanding or contracting raw data, which is time-series acceleration information obtained from an acceleration sensor, along the time axis. In this embodiment, normalization is performed by the server 1001, but may also be performed by the smartphone 1004. That is, the normalization unit 801 may be provided in the smartphone 1004 rather than the server 1001.

[0204] The selection unit 804 selects a care suggestion from the care information using the obtained movement-related information, i.e., the walking type. That is, the selection unit 804 uses the movement data stored in the user DB 802 (storage unit) in addition to the latest movement data, in other words, the movement data obtained by acquiring a predetermined movement multiple times, the movement-related information acquisition unit 803 acquires an evaluation, which is movement-related information, and selects a care suggestion using the acquired evaluation, which is movement-related information for selecting care suggestions (selection information).

[0205] Whether it is the first time or the second time or thereafter, the gait type and the selected care suggestion are notified to the smartphone 1004, which is the user terminal, by the notification control unit 805 of the server, and are transmitted to the user. The notification control unit uses information from the user DB 802 to determine the smartphone 1004 to which the gait type and the care suggestion should be notified.

[0206] The user DB 802 is a collection of information about each user stored in a storage unit in a nonvolatile memory, such as a magnetic disk, of the server 1001. FIG. 17A shows the contents of data 901 stored for each user. The data 901 includes an implementation status 911. The implementation status 911 indicates the implementation status of the user's care suggestions. FIG. 17B shows details of the implementation status 911. In this embodiment, as shown in FIG. 17A , the user DB 802 stores user information such as a user ID, a user terminal ID (e.g., a MAC address), a name, and an address to which care products and the like are sent. It also stores result information associated with each user ID, including movement data, the date of movement data acquisition (notification to the user), the type of user movement notified to the user, the care suggestions notified to the user, and the implementation status 911. In this embodiment, only five movement-related information (movement data) (from the zeroth to the fourth movement) is stored, and all information after the user's new registration is stored for the other items. In Figure 17A, the "movement data" field is marked with "-" for the five previous times and earlier, meaning that there is no storage space for the data. This reduces the storage capacity of the movement data, which requires a larger storage space than other fields. The implementation status 911 is divided into an exercise column and a product column, as shown in Figure 17B. In this embodiment, the exercise column of the implementation status 911 is a column for recording whether or not the user performed the exercise. When a user plays a sample video on the user terminal, it is assumed that the user performed the exercise, and "Performed" is recorded in the exercise column. The product column of the implementation status 911 is a column for recording whether or not the user used a suggested product. When a user purchases a suggested product, it is assumed that the user used the product, and "Performed" is recorded in the product column.

[0207] The user information area stores information entered by the user in the terminal initial module P3, which will be described later. It is also possible to design the server 1001 so that only part of the information in the user DB 802 is stored on the server 1001 side, such that user information other than the user ID is not stored in the user DB 802 of the server 1001, but is instead stored in the smartphone (user terminal) 1004, and only the necessary information is sent from the smartphone 1004 to the server 1001 each time. In other words, the information in the user DB 802 can be stored separately between the server 1001 and the user terminal (smartphone 1004). There are various possible specific configurations for this, but those skilled in the art would understand this as a simple design change.

[0208] This embodiment is realized by the cooperative operation of each module, including the terminal initial module P3 and the repetition module P4, that constitute the program of the server 1001, and each module that constitutes the application of the smartphone 1004. First, the cooperation of operations between the modules will be described.

[0209] When the app is installed on the smartphone 1004 and activated in response to a user operation, the terminal initial module P3 is activated, acquires raw data (acceleration data) obtained when the user performs a predetermined movement practice, and transmits the acquired data to the server 1001. In response, the server 1001 determines the user's walking type and returns the type information to the smartphone 1004. If the user is satisfied with the returned walking type, the smartphone 1004 issues a care suggestion request to the server 1001, and the server 1001 sends an initial care suggestion to the smartphone 1004. Thereafter, the repetition module P4 is activated on the smartphone 1004 automatically, for example, once a week, or upon request by the user. The activated repetition module P4 again transmits the raw data obtained when the user performs a predetermined movement to the server 1001. Upon receiving the raw data, the server 1001 again activates the suggestion module P2 and returns the type information and care suggestion to the smartphone 1004. The cooperative operation between the repeat module P4 and the re-suggestion module P2 is repeated until the re-suggestion module P2 determines that further care suggestions are unnecessary and notifies the smartphone 1004 of this.

[0210] The operations of the terminal initial module P3 and the repetition module P4 that constitute the application on the smartphone 1004 side will be described with reference to FIGS.

[0211] In the present embodiment, the terminal initial module P3 first trains the user to acquire motion data in a motion data acquisition practice step S1. In the motion data acquisition practice step S1, the user is first instructed to prepare for a predetermined motion, i.e., walking, by standing up and holding the smartphone 1004 in front of the abdomen.

[0212] In the motion data acquisition exercise step S1, after issuing a command to prepare for a predetermined action, an acceleration sensor within the smartphone detects that the smartphone has been stationary for at least one second, preferably three seconds, and then issues a command to start the predetermined action. In this embodiment, after detecting stationary motion, the smartphone's built-in vibration function is activated, causing the smartphone to vibrate, thereby issuing a command to start the predetermined action to the user holding the smartphone 1004. The command to start the predetermined action may be displayed on the screen, but is preferably vibrated by the smartphone's internal vibrator or output as audio from the smartphone's 1004 speaker. This is because holding the smartphone on the abdomen prevents the user from seeing the screen. When issuing an audio command, the command to start the predetermined action is issued by outputting audio from the smartphone's built-in speaker, for example, "Please continue walking forward for six steps." Note that the number of steps output, i.e., the number of steps instructed by the smartphone to the user, is at least four, preferably six to ten.

[0213] After issuing a command to start a predetermined movement, i.e., to start walking, raw data is subsequently acquired from the acceleration sensor every 100 ms for 10 seconds, for example. The acquired movement data from the acceleration sensor is temporarily stored in the storage device of the smartphone 1004. Once the raw data acquisition is complete, the raw data stored in the storage device of the smartphone 1004 is transmitted to the server 1001.

[0214] In the motion data acquisition practice step S1, the above-described walking preparation command and raw data acquisition and transmission are repeated twice. After repeating the raw data transmission twice, the smartphone 1004 waits for the gait type to be sent from the server 1001. When the gait type is sent, the smartphone 1004 presents the gait type to the user, informing them of its characteristics, for example, by displaying it on a screen. If the user is not satisfied with the gait type sent, the smartphone 1004 operates a remeasurement button on a screen (not shown). In response to the operation of the remeasurement button, the smartphone 1004 performs a remeasurement. The remeasurement consists of a single walking preparation command, raw data acquisition, and raw data transmission. In other words, in this embodiment, practice, i.e., raw data measurement, is repeated until the user is satisfied. If the user is satisfied with the gait type sent, the smartphone 1004 operates a proposal request button on a screen (not shown). When the user operates the proposal request button, the process proceeds to care proposal request step S3.

[0215] In care suggestion request step S3, the smartphone 1004 transmits a care suggestion request to the server. Once transmission is complete, the process proceeds to care suggestion first reception display step S5, where the smartphone 1004 waits for a care suggestion to be sent from the server 1001. In care suggestion first reception display step S5, once a care suggestion has been sent from the server 1001, the smartphone 1004 displays the gait type, corresponding precautions, and the sent care suggestion on the screen, and then proceeds to user registration request confirmation step S7.

[0216] In this embodiment, the precautions according to the walking type are stored in an app on the smartphone 1004 and are displayed on the screen by referring to the walking type sent from the server 1001. Instead of storing the precautions in the smartphone 1004, the server 1001 may send the precautions according to the walking type in addition to the walking type and care suggestions, and these may be displayed on the screen of the smartphone 1004.

[0217] When a user's desire for user registration is entered in the user registration confirmation step S7, the user registration step S9 is executed. Specifically, the user operates the smartphone 1004 according to instructions displayed on the smartphone 1004 screen to enter information such as the user's name, the address to which care products and other items will be sent, their age, and their gender. Finally, the user registration step S9 ends by setting the next start date of the repeat module P4 in the schedule module, and the system transitions to a standby state. The schedule module is a so-called scheduler that starts various modules according to predetermined dates and times. In this embodiment, the start of the repeat module P4 is set to one week later.

[0218] If the gait type sent is type "1," which will be described later, that is, if there are no problems with the walking motion that need to be improved, the care suggestion sent is "none." In this case, the gait type becomes "1 (no problems)" in the care suggestion initial reception display step S5, and instead of displaying the precautions and the care suggestion sent, a sentence such as "Please continue to walk well" is displayed on the screen. In this embodiment, user registration is also accepted in this case, but the start date of the repeat module P4 set in the scheduler may be set to a different date, such as one month later, or the start date may not be set at all.

[0219] If it is input in the user registration confirmation step S7 that the user does not wish to register, the process moves to registration cancellation step S11, where a message such as "Thank you" is displayed, the app for this system existing in the smartphone is deleted by the app itself, and the process ends.

[0220] The operation of the repeat module P4 will be described with reference to FIG. 19 . When the repeat module P4 is activated by a user operation or a schedule module, a care implementation confirmation step S101 is first executed. In the care implementation confirmation step S101, the care proposal implementation status field recorded in the user DB 802 is read, and in the implementation determination step S103, a determination is made as to whether or not the proposed care has been implemented using the read content. Alternatively, in the care implementation confirmation step S101, a question may be asked on the screen as to whether or not the user has implemented the proposed care, and the user's response may be awaited. In this case, once the user's response, i.e., input into the smartphone 1004, the process proceeds to the implementation determination step S103. If it is determined that the proposed care has been implemented, i.e., if there is a record of implementation or an input that the proposed care has been implemented, the process proceeds to the predetermined movement start instruction step S105. Note that the question as to whether or not the proposed care has been implemented may be a question as to whether or not the proposed care has been implemented, even if only a small amount of implementation may result in improvement in the predetermined movement, i.e., walking. Therefore, it is preferable to ask whether or not the proposed care has been implemented, even partially.

[0221] If there is no record of the care being performed or if the user has input that the care was not performed, the process proceeds to care suggestion redisplay step S113. In care suggestion redisplay step S113, the server 1001 queries the user DB 802 for the user's gait type and care suggestions previously notified to the user, and displays the gait type, corresponding notes, and the care suggestions sent on the screen, as well as a message urging the user to perform the care suggestions, and sets the next startup date for repeat module P4 in the scheduler, and then ends (standby state).

[0222] When it is determined that the measurement has been performed and the process proceeds to step S105, the measurement is retaken and another health care suggestion is made after issuing a command to prepare for the measurement and a command to start the measurement. The details of the operations of step S105 to instruct the start of the measurement for the retake in the repetition module P4 and step S107 to acquire raw data are the same as those of the command to prepare for the measurement and the command to start the measurement in the terminal initial module P3, and the raw data acquisition, respectively, and therefore will not be described again.

[0223] Once the acquisition of motion data in raw data acquisition step S107 is completed, the process proceeds to re-data transmission step S109, in which the user ID stored in the memory device of the smartphone 1004 and the acceleration data (raw data) acquired in raw data acquisition step S107 are transmitted to the server 1001.

[0224] Once the raw data has been sent in the re-data sending step S109, the process proceeds to the care suggestion etc. re-receiving display step S111, where the system waits for the gait type and care suggestions to be sent from the server 1001. Once these have been sent, the gait type, the corresponding precautions, and the sent care suggestions are displayed on the screen. Finally, the date for the next recurrence module P4 to be activated is set in the schedule module, and the system ends and goes into standby mode. Here, if the gait type sent is type "1," described below, the operation is the same as that in the care suggestion initial receiving display step S5, and therefore will not be described here.

[0225] Next, the server-side programs, ie, the sorting module P0, the new registration module P1, and the re-proposal module P2, will be described with reference to FIGS. 20A to 20C.

[0226] When the server 1001 receives an operation request from the smartphone 1004, the server 1001 first executes the allocation module P0 shown in Fig. 20A. In the allocation module P0, a determination is made in allocation step S1201 as to whether the operation request is from a registered user. In allocation step S1201, depending on whether the operation request includes the user ID of a registered user, if it does not (NO in allocation step S1201), the server 1001 proceeds to the new registration module P1, and if it does (YES in allocation step S1201), the server 1001 proceeds again to the proposal module P2.

[0227] The new registration module P1 shown in FIG. 20B includes a user information acquisition step S121 for acquiring terminal ID information for identifying the smartphone 1004 and assigning a temporary user ID, an initial action-related information acquisition and transmission step S123 for acquiring raw data of the first two predetermined actions, determining a walking type using the acquired raw data, and transmitting the determined walking type to the smartphone 1004, a request determination step S125 for determining whether the information sent from the user is a proposal request or action-related information, and, when raw data obtained by re-measurement is sent, determining a walking type using the sent raw data and action data stored in the user DB 802, and The server 1001 executes the following steps: a movement-related information acquisition and transmission step S127, in which the determined, i.e., last-transmitted, walking type is transmitted to the smartphone 1004; a first-day care proposal selection step S131, in which, when a proposal request is received, a care proposal is selected and determined using the determined, i.e., last-transmitted, walking type; a first-day care proposal notification step S133, in which the determined care proposal is returned to the smartphone 1004; and a first-day movement-related information storage step S135, in which the temporary user ID is changed to a legitimate user ID and user information about the new user and result information such as the initial type (movement-related information) and the initial care proposal are associated with the user ID and recorded in the user DB 802. The movement data recorded in the first-day movement-related information storage step S135 in the user DB 802 is the movement data after averaging processing that was last used to determine the type. The location in the user DB 802 where various information is recorded in the first-day movement-related information storage step S135 is the previous column shown in FIG. 17A. 21A, the action-related information acquisition and transmission step S127 is made up of an action-related information acquisition step S161 and an action-related information transmission step S163. If the user does not wish to register as a user, the temporary user ID is discarded and the action data and other related information are removed from the user DB 802 in the first-day action-related information, etc. storage step S135.

[0228] The re-suggestion module P2 shown in FIG. 20C acquires the user ID and sensor information, which is raw data obtained by the user performing and measuring a predetermined movement again, reads normalized past raw data, i.e., past movement data, stored from the user DB 802, and determines a walking type using the acquired raw data and the past movement data stored in the user DB 802. The server 1001 executes the following steps: a movement-related information acquisition step S137, a past proposal acquisition step S139, which reads past care proposals for the user from the user DB 802; a care proposal reselection step S141, which selects and determines a care proposal using the walking type determined in the movement-related information acquisition step S137 and the past proposal contents read in the past proposal acquisition step S139; a care proposal renotification step S143, which sends the care proposal determined in the care proposal reselection step S141 to the smartphone 1004; and a re-motion-related information, etc. storage step S145, which additionally registers result information, including newly obtained movement data, movement-related information (type), date, and notified care proposal, in the user DB 802.

[0229] In this embodiment, the action-related information acquisition step S161 of the new registration module P1 and the action-related information acquisition step S137 of the re-proposal module P2 are implemented by the same action-related information acquisition module P13. As shown in FIG. 21B , the action-related information acquisition module P13 includes an averaging process step S165 for obtaining average action data (action-related information) for determining a gait type using past action data and the latest raw data stored in the user DB 802, a feature extraction step S167 for extracting features from the obtained average action data, and a type determination step S169 for determining a gait type from the features. The action-related information acquisition module P13 implements the action-related information acquisition unit 803 of FIG. 16 in cooperation with the hardware of the server 1001. More specifically, the averaging process step S165 implements an averaging processing unit 831, the feature extraction step S167 implements a feature extraction unit 832, and the type determination step S169 implements an evaluation unit 833.

[0230] Details of the averaging process step S165 will be described with reference to FIG. 22 . The averaging process step S165 is a process of obtaining average movement data, which is movement data obtained by performing a new moving average using past movement data and currently obtained raw data. First, a latest data extraction normalization step S171 is executed, in which the newly obtained raw data, i.e., data transmitted from the smartphone 1004, is divided into walking cycles and time (period) normalization is performed by compressing and expanding the data along the time axis. The process in this normalization step S171 corresponds to the operation of the normalization unit 801 shown in FIG. 16 . In the normalization step S171, the current movement data obtained by normalization is written into the data (0) area of ​​the user DB 802. Next, the current movement data and previous movement data stored in the user DB 802 are read (movement data read step S173). Then, it is determined whether the past two movement data have been recorded (count determination step S175). If the past two motion data sets are recorded, the current motion data and the most recent two motion data sets are averaged (three-time average step S179). If no motion data sets are recorded, the current motion data set and the stored one motion data set are averaged (two-time average step S177). As described above, due to the allocation in the count determination step S175, for the second proposal, for which only the most recent motion data set is stored in the user DB 802, the first two motion data sets are averaged, and for the third and subsequent proposals, the most recent three motion data sets, including the current motion data set, are averaged. The averaged result is used to select the proposal. Note that in this embodiment, the past five motion data sets are stored. Therefore, it is also possible to remove outliers before averaging, as in the third embodiment, and then average the most recent three motion data sets excluding the outliers. Alternatively, the normalized current motion data may be directly subjected to the averaging process. That is, the current motion data may be averaged directly without being read from the user DB 802. In either case, the averaging is performed using both the newly acquired current motion data and the previously recorded motion data.In other words, the motion-related information acquisition unit uses both the newly acquired motion-related information and the previous motion-related information stored in the memory unit to select physical health care suggestions, regardless of whether the newly acquired motion-related information has passed through the memory unit. Note that although various modifications are possible to the details of the averaging process in addition to those shown here, further description will not be given to avoid complication.

[0231] Although not shown in the figure, the initial action-related information acquisition and transmission step S123 calls the action-related information acquisition module P13 for type determination. Here, since two sets of raw data are sent, the latest data extraction and normalization step S171 extracts and normalizes both sets of raw data. The normalized data for the two sets is then written to the data (0) and data (1) areas of the user DB 802. Whether the latest data extraction and normalization step S171 extracts and normalizes the raw data and writes the data to the user DB 802 once or twice can be easily achieved by enabling the latest data extraction and normalization step S171 to recognize whether the read module is the newly registered module P1 or the re-proposed module P2. The action data read step S173 reads the two sets of action data that have been extracted and normalized. That is, the two sets of action data before averaging are temporarily stored in the user DB 802. If the user practices three or more times, the data is shifted sequentially and written to the data (0) area, and the average of the most recent three times is used for the following processing. When saving the first day movement data, only the last calculated average movement data is left in the data (1) area, and the rest is deleted and not saved.

[0232] In the feature extraction step S167, the symmetry (posture) of the joint motion obtained from the acceleration and the magnitude (movement) of the joint motion obtained from the acceleration are each divided into A to C, as in the third embodiment. Then, in the type determination step S169, the walking motion types are classified into seven types 1 to 7, as in the third embodiment. Note that, as in the third embodiment, the classification method is not limited to this.

[0233] In this embodiment, the first-day care suggestion selection step S131 of the new registration module P1 and the care suggestion reselection step S141 of the re-suggestion module P2 are implemented by the same selection module P14. The selection module P14 selects care suggestions using the gait type, which is movement-related information acquired by the movement-related information acquisition module P13. The selection unit 804 is implemented by cooperation between the selection module P14 and the hardware of the server 1001. Details of the care suggestion selection process will be described below with reference to FIGS. 23A, 23B, and 24.

[0234] As shown in FIG. 23A, in the selection module P14, a care to be proposed is selected from candidates (care proposal selection step S181), and past proposal contents recorded in the user DB 802 are referenced to determine the recommended exercises and recommended products, which are the care contents to be finally proposed to the user (care proposal determination step S183).

[0235] In the care suggestion selection step S181, the classified movement-related information, which is the walking type, is used to select suggested care information from the care suggestion candidate table 806. FIG. 24 shows stored data 1601 stored in the care suggestion candidate table 806. In the stored data 1601, movement-related information 1611, exercise suggestions 1612, and product suggestions 1613 are associated with each other. The movement-related information 1611 is movement-related information of a predetermined movement performed by the user in the past. The exercise suggestions 1612 are care suggestions related to exercise selected using the movement-related information 1611. The product suggestions 1613 are care suggestions related to products selected using the movement-related information 1611. Note that "stretch" in FIG. 24 refers to exercise, and "insole" refers to a product. Insoles are classified as follows according to arch height and heel cup depth: The larger the number for stretch, the greater the movement. Low arch, deep heel; insole 1 High arch, deep heel; insole 2 High arch, shallow heel; insole 3

[0236] In the care suggestion determination step S183, care information to be suggested to the user is determined based on the care information selected using the motion-related information, taking into account the content of suggestions made in the past, etc. Details of the care suggestion determination step S183 will be described below with reference to FIG. 23B .

[0237] A DB past reading step S185 is executed to read past suggestions and implementation details from the user DB 802. In a product suggestion determination step S187, the read contents of the user DB 802 are used to determine whether there are four or more suggestion records and whether a product has been purchased during the past four times. If there are four or fewer suggestion records or if a product has been purchased during the past four times, no product suggestion is made. That is, a product suggestion deletion step S191 is executed to delete the product from the care information selected in the care suggestion selection step S181, and the care suggestion determination step S183 is completed. On the other hand, if there are four or more suggestion records and no product has been purchased during the past four times, the selected care information is not changed (care product purchase suggestion step S189). Note that, although no substantial processing is performed in the care product purchase suggestion step S189 in this embodiment, a product may not be selected as care information in the care suggestion determination step S183, and the product in the care information may be added to the suggested care in the care product purchase suggestion step S189. In this case, no substantial processing is performed in the product suggestion deletion step S191.

[0238] The reason why product suggestions are not made in the first few times (four times in this embodiment) is that the user is more likely to accept suggestions and purchase products once they have become familiar with and trusted the system. Furthermore, the reason why product suggestions are not made if the user has purchased a product in the past few times (four times in this embodiment) is that it takes a certain amount of time for the effects of using a care product to become established. Therefore, a product suggestion may be made if no product purchases have been made for a predetermined period of time, such as one month. For example, in the case of products consumed by the user, such as supplements or chemical warmers, it is preferable to use the predetermined period to determine whether a new care product suggestion is necessary.

[0239] The processing details of step S145 for saving motion-related information, etc., will now be briefly explained. When newly acquired motion data, motion-related information (type), date, notified care suggestions, and other result information are added to the user DB 802, the newly added information is stored in the "0th time before" column in FIG. 17A , and the number for each time must be incremented by one, such as "4th time before" for "3rd time before," "3rd time before," and so on. By performing this operation, the newly added information is moved to the "1st time before" column. In this embodiment, instead of actual addition, an address "0th time before" is stored as the starting position (entrance) for each field, and shifting this address achieves the same effect as addition. Those skilled in the art with general knowledge of database technology will readily understand that various implementation methods are possible. In this embodiment, only the motion data from the past two times is used for averaging, whereas four times is saved. This is done to reduce storage capacity and to store spare motion data so that, if there are obvious outliers in the motion data, the averaging process can still be performed even if the outliers are removed. The processing of outliers will not be described here.

[0240] The server 1001, which is the behavior improvement suggestion device of the present invention, can also be used as a so-called standalone device rather than being connected to a user terminal (smartphone 1004) via the network 603. That is, health care suggestions can be made by measuring acceleration data during walking using a wearable device or data logger, and acquiring the results directly via a wired or wireless connection or a storage medium. In this case, the notification control unit can notify the selection results to a display device, for example, to display them on the screen, or to a printer device, for printing. Alternatively, the user's smartphone can be notified by email.

[0241] The server 1001 does not necessarily have to be the action-improvement suggestion device of the present invention. That is, some of the functions of the action-improvement suggestion device may be provided on the terminal side. For example, the action-related information acquisition unit 803 may be provided on the user terminal (smartphone 1004) side, and type classification may be performed on the user terminal side. In other words, the action-related information acquisition unit 803, user DB 802, and other components described as components of the server 1001 in this embodiment may be provided on the user terminal.

[0242] Sixth Embodiment Next, a motion improvement suggestion system according to a sixth embodiment of the present invention will be described with reference to FIGS. 25 to 33B. As with the fifth embodiment, the motion improvement suggestion system according to this embodiment is realized as an information processing system having multiple information processing devices, including a server 1001 that serves as a motion improvement suggestion device, multiple smartphones (user terminals) 1004, and a network 603 connecting these. The outline of the motion improvement suggestion system according to this embodiment is the same as the outline of the motion improvement suggestion system 1000 according to the fifth embodiment shown in FIG. 14. The server 1001, smartphone 1004, and network 603 of this embodiment can be the same as the server 1001, smartphone 1004, and network 1002 of the fifth embodiment.

[0243] As shown in FIG. 25 , the overall flow of this embodiment for the user includes an application installation and user registration step S201, in which the user installs an application and registers the user; a first predetermined operation execution step S203, in which the user performs a first predetermined operation according to instructions from the device; a first care suggestion reception step S205, in which the user receives a first care suggestion at the device; a first care suggestion execution step S207, in which the user performs the first care suggestion; a care suggestion inquiry step S209, in which the user is inquired via the device about whether the care suggestion was performed; a next predetermined operation execution step S211, in which the user performs the next predetermined operation (next predetermined operation) according to instructions from the device if the user answers yes; and a next care suggestion reception step S213, in which the user receives a new care suggestion (next care suggestion) at the device. S209 through S213 are repeated until the predetermined operation is no longer problematic, in other words, until no further improvement is required. The user can determine whether repetition is no longer required based on the care suggestion content shown in S213. 25 to avoid complexity, if the user's initial prescribed motion is an ideal prescribed motion and no improvement is required, a message to that effect is displayed in the initial care suggestion execution step S207, and the process ends. In this embodiment, the prescribed motion is also walking.

[0244] An outline of the information processing procedure in the server 1001 in this embodiment will be described with reference to FIGS. 25 and 26 . Time-series acceleration data (raw data) measured by an acceleration sensor (not shown) of the smartphone 1004 in a first predetermined action execution step S203 and a next predetermined action execution step S211 in FIG. 25 is received by the sensor data acquisition unit 1811 of the server 1001, preferably normalized, and passed to the feature extraction unit 832. The feature extraction unit 832 extracts feature amounts of the predetermined action from the passed raw data and passes the extracted feature amounts to the evaluation unit 833. The evaluation unit 833 uses the passed feature amounts to determine a walking type (type), which is the action-related information of this embodiment. That is, the first action-related information acquisition unit 1801 in this embodiment includes the sensor data acquisition unit 1811, the feature extraction unit 832, and the evaluation unit 833, and acquires first predetermined information representing the state of the user's most recent, i.e., current, predetermined action, using raw data, which is time-series acceleration information measured during the user's predetermined action and obtained from the acceleration sensor.

[0245] When raw data relating to the second or subsequent predetermined motions of the user is sent to the server, in addition to acquiring the first predetermined motion-related information, the second predetermined motion determining unit 1821 determines second predetermined motion-related information representing states of the predetermined motions performed multiple times in the past, using past motion-related information stored in the user DB 1822. That is, the second predetermined motion acquiring unit 1802, which includes the user DB 1822 and the second predetermined motion determining unit 1821, acquires second predetermined motion-related information using information relating to past predetermined motions.

[0246] The selection unit 804 selects physical health care suggestions using the action-related information acquired by the action-related information acquisition unit (first action-related information acquisition unit 1801) and the result of statistical processing, specifically, majority voting, of the action-related information stored in the storage unit (user DB 1822). Specifically, the selection unit 804 initially selects care suggestions using only the first predetermined action-related information, i.e., the initial walking type. From the second time onward, the selection unit 804 reads one or more past walking types recorded in the user database (user DB 1822) and uses both the past walking type (second predetermined action-related information in this embodiment) determined using the read type and the latest (current) walking type (first predetermined action-related information in this embodiment) to select care information as care suggestions. That is, in this embodiment, from the second time onward, care information is selected using the evaluation of the current predetermined action and the evaluation of the past predetermined action acquired by determining the evaluation using the evaluation of one or more predetermined actions stored in the storage unit as action-related information for selecting care suggestions. Here, a feature of this embodiment is that when past predetermined motion-related information is recorded in the storage unit, the selector selects care suggestions based on a combination of the current predetermined motion-related information (first predetermined motion-related information) and the past predetermined motion-related information (second predetermined motion-related information). In other words, the first predetermined motion-related information is given a greater weight in the selection than in other embodiments.

[0247] Whether it is the first time or the second time or thereafter, the care suggestion, which is the care information selected by the selection unit 804 from multiple candidates, is notified to the user terminal by the notification control unit 805 of the server together with the current type, which is the first predetermined action-related information, and transmitted to the user. Note that the notification control unit uses information in the user DB 1822 to determine the user terminal to which the care suggestion and the current type are notified.

[0248] FIG. 27 shows the contents of data 1901 stored in the user DB 1822 of this embodiment. In this embodiment, as shown in FIG. 27 , the user DB 1822, which is a storage unit, stores user information, such as a user ID, a user terminal ID (e.g., MAC address or phone number) that identifies the user terminal, the user's name, and an address to which care products and other information are sent. The user information, including the type of user behavior notified to the user, the notification date, and the care suggestions notified to the user, is linked to each user ID and stored for at least the last five times. The user information, such as information entered by the user in the terminal initial module P7 (described later), is stored in the user DB registration step S251 of the new registration module P5 (described later). In this embodiment, the user DB 1822 is provided in the server 1001. As in the fifth embodiment, a portion of the information in the user DB 1822 may be stored in the smartphone (user terminal) 1004 and transmitted each time along with the measured raw data.

[0249] This embodiment is realized by the cooperative operation of each module, including the terminal-initial module P7 and the repetition module P8, that constitute the application of the smartphone 1004, and each module that constitutes the program of the server 1001. First, the cooperation of operations between the modules will be described.

[0250] When the app is installed on the smartphone 1004 and activated in response to a user operation, the terminal initial module P7 shown in FIG. 28A activates, acquires sensor information, which is raw data when the user performs a predetermined action, and transmits the sensor information to the server 1001 along with information for user registration. In response to this, the server 1001 activates the new registration module P5 shown in FIG. 29A, and returns type information and care suggestions to the smartphone 1004. Thereafter, the smartphone 1004 automatically activates the repetition module P8 shown in FIG. 28B, for example, once a week. The activated repetition module P8 again transmits the sensor information when the user performs a predetermined action to the server 1001. In the server 1001 that has received the sensor information, the suggestion module P6 again activates and returns type information and care suggestions to the smartphone 1004. The automatic startup of the weekly repeat module P8 on the smartphone 1004 and the corresponding operation of the re-suggestion module P6 on the server 1001 are repeated until the re-suggestion module P6 determines that no further care suggestions are necessary, notifies the smartphone 1004 of this, and stops the automatic startup of the weekly repeat module P8.

[0251] The operations of the terminal initial module P7 and the repetition module P8 that constitute the application on the smartphone 1004 side in this embodiment will be described with reference to FIGS. 28A and 28B.

[0252] The terminal initial module P7 first accepts user registration in a user registration step S221. Specifically, the user operates the smartphone 1004 to input information such as the user's name, the address to which care products and the like are to be sent, age, and gender, in accordance with instructions displayed on the screen of the smartphone 1004. The input user information is temporarily stored in the storage device of the smartphone 1004.

[0253] In the subsequent step S223 of instructing to start a predetermined operation, a command for the predetermined operation is issued to the user. In the step S223 of instructing to start a predetermined operation, first, a command to prepare for the predetermined operation is issued, and then, when it is detected that the user is ready using the acceleration sensor inside the smartphone 1004, a command to start the predetermined operation is issued. The details of the command to prepare for the predetermined operation and the command to start the predetermined operation in the step S223 of instructing to start a predetermined operation are the same as those in the fifth embodiment, and therefore description thereof will be omitted.

[0254] Next, the process proceeds to an operation data acquisition step S225. When the data acquisition is completed, the process proceeds to an initial data transmission step S227, in which the user information stored in the storage device of the smartphone 1004 and the operation data acquired in the operation data acquisition step S225 are transmitted to the server 1001.

[0255] Once data transmission in the initial data transmission step S227 is complete, the process proceeds to the care suggestion, etc., initial reception display step S229, where the process waits for data such as care suggestions to be sent from the server 1001. In this embodiment, the data sent from the server 1001 includes the user ID, gait type, and care suggestions. Once the data is sent, the user ID is stored in the non-volatile storage device of the smartphone 1004. Then, the care suggestion, etc., initial reception display step S229 displays the gait type, corresponding notes, and the sent care suggestions on the screen. Finally, in the end step S231, the date for the next activation of the recurring module P8 is set in the schedule module, and the process ends, transitioning to a standby state. In this embodiment, the activation of the recurring module P8 is set to one week later as a general rule.

[0256] If the walking type sent from the server 1001 in step S229 for displaying care suggestions and the like for the first time is "1", the same display as in the fifth embodiment is displayed.

[0257] In this embodiment, the smartphone 1004 app also stores and displays warnings according to the walking type, but like the fifth embodiment, it is also possible to display warnings sent from the server 1001.

[0258] When the repetition module P8 is activated by the schedule module, a care implementation inquiry step S233 is first executed. In the care implementation inquiry step S233, a question is asked on the screen as to whether the user has performed the proposed care, and a response from the user is awaited. When the user responds, i.e., inputs the response into the smartphone 1004, the process proceeds to an implementation determination step S235, where it is determined that the proposed care has been performed, i.e., if an input indicating that the proposed care has been performed is made, the process proceeds to a predetermined action start instruction step S237. Note that, when asking whether the proposed care has been performed, it is preferable to ask whether the proposed care has been performed, even partially.

[0259] If the user inputs that they have not performed the care, the smartphone 1004 queries the user DB in care suggestion re-display step S247, and displays the same walking type, precautions, and care suggestions as last time on the screen. In addition, a message urging the user to perform the care suggestion is displayed, and the scheduler is set to the next startup date for the repeat module P8, and the process ends (standby state (end step S245)).

[0260] When the user inputs that the measurement has been performed and proceeds to step S237, the measurement is retaken and another health care suggestion is made. The operations of step S237 for instructing to start a predetermined action for remeasurement and step S239 for acquiring action data in the repetition module P8 are the same as step S223 for instructing to start a predetermined action and step S225 for acquiring action data in the terminal initial module P7, respectively, and therefore will not be described here.

[0261] In this embodiment, similarly to the fifth embodiment, the status of proposal implementation may be automatically recorded in the user DB 1822, and it may be determined whether or not the proposal has been implemented without relying on user input.

[0262] Once the acquisition of the operation data in the operation data acquisition step S239 is completed, the process proceeds to the re-data transmission step S241, in which the user ID stored in the memory device of the smartphone 1004 and the operation data acquired in the operation data acquisition step S239 are transmitted to the server 1001.

[0263] Once data transmission in re-data transmission step S241 is complete, the process proceeds to care suggestion etc. re-reception display step S243, where the process waits for data such as care suggestions to be sent from the server 1001. The data sent from the server is the gait type and care suggestions. Then, care suggestion etc. re-reception display step S243 displays the gait type, corresponding notes, and the sent care suggestions on the screen. Finally, in end step S245, the date for the next recurrence module P4 activation is set in the schedule module, and the process ends and transitions to a standby state. Here, when the sent gait type is type "1," described below, the operation is the same as care suggestion etc. initial reception display step S229, and therefore description thereof will be omitted.

[0264] Next, the operation of the server-side new registration module P5 and re-propose module P6 will be described with reference to Figures 29A and 29B. As with the fifth embodiment, the sorting module will activate either the new registration module P5 or the re-propose module P6 depending on whether the access is from a registered user, so a description of this will be omitted.

[0265] The new registration module P5 executes on the server 1001 the following steps: a user DB registration step S251 for assigning a user ID to a new user of the smartphone 1004 and newly registering various information about the new user in the user DB 1822; a first action-related information acquisition step S253 for acquiring sensor information at the time of a first specified action and analyzing the acquired sensor information to determine the action type; an initial care suggestion selection step S255 for selecting and determining a care suggestion using the determined action type (action-related information); an initial notification step S257 for sending the assigned user ID and the initial care suggestion determined in the initial care suggestion selection step S2105 to the smartphone 1004; and a result information storage step S259 for registering result information about the new user, such as the initial type (action-related information) and the initial care suggestion, in the user DB 1822.

[0266] The re-suggestion module P6 executes the following steps on the server 1001: a first action-related information acquisition step S261, in which the server 1001 acquires sensor information, which is raw data obtained by the user performing and measuring a specified action again, analyzes the acquired sensor information, and determines the current action type (first action-related information); a second action-related information acquisition step S263, in which the server 1001 reads necessary information such as the user's past types from the user DB 1822 and acquires second action-related information, which is the action type based on the past action data; a care suggestion reselection step S265, in which the server 1001 selects and determines a care suggestion using both the action type based on the past action data acquired in the second action-related information acquisition step S263 and the current action type acquired in the first action-related information acquisition step S261; a care suggestion notification step S267, in which the server 1001 sends the care suggestion determined in the care suggestion reselection step S265 to the smartphone 1004; and a result information storage step S269, in which the server 1001 registers result information consisting of the first action-related information (type), date, the selected care suggestion, etc. in the user DB 1822.

[0267] In this embodiment, the first motion-related information acquisition step S253 of the new registration module P5 and the first motion-related information acquisition step S261 of the re-proposal module P6 are realized by the same first motion-related information acquisition module. The initial care suggestion selection step S255 of the new registration module P5 and the care suggestion reselection step S265 of the re-proposal module P6 are realized by the same care suggestion selection module P5C. Furthermore, the result information storage step S2109 of the new registration module P5 and the result information storage step S269 of the re-proposal module P6 are realized by the same result information storage module. The second motion-related information acquisition step S263 of the re-proposal module P6 is realized by the second motion-related information acquisition module P6B. Details of these modules are described below. For ease of understanding, the first motion-related information acquisition module, the result information storage module, the second motion-related information acquisition module P6B, and the care suggestion selection module P5C will be described in this order.

[0268] [First Action-Related Information Acquisition Module] The first action-related information acquisition module realizes the first action-related information acquisition unit 1801 in cooperation with the hardware of the server 1001. The first action-related information acquisition module extracts acceleration data corresponding to at least two steps, and preferably four steps, from the action data, i.e., acceleration information measured by the user holding the smartphone 1004 in front of the abdomen, more precisely, from a data sequence of acceleration versus time. Note that the extraction method can be a well-known method, such as selecting one step from the extreme value of the acceleration data.

[0269] In this embodiment, the degree of symmetry representing the left and right postures and the degree of movement are calculated as feature quantities from the extracted acceleration data, and each is classified into three levels: A, B, and C (feature quantity extraction unit 832). Specifically, if the difference between the maximum values ​​of the left and right accelerations, which indicates symmetry, i.e., left and right balance, is less than 5% of the maximum value of the larger left or right side and is not a problem, it is classified as A; if it is between 5% and 15% and is slightly out of balance, it is classified as B; and if it exceeds 15%, it is classified as C, which indicates a significant imbalance. Furthermore, in this embodiment, the degree of movement is measured using walking speed, which typically indicates the magnitude of movement. Specifically, if it is more than 4 km / h, it is classified as A; if it is 4 km / h or less and 3.6 km / h or more, it is classified as B; and if it is less than 3.6 km / h, it is classified as C.

[0270] After dividing the postures and movements into three levels, A, B, and C, the walking movement types are then classified into seven types, 1 to 7, as follows (evaluation unit 833 (first predetermined movement determination unit)): Posture A, movement A; type "1" Posture A, movement B; type "2" Posture A, movement C; type "2" Posture B, movement A; type "3" Posture B, movement B; type "4" Posture B, movement C; type "6" Posture C, movement A; type "3" Posture C, movement B; type "5" Posture C, movement C; type "7"

[0271] [Result Information Storage Module] How the contents of the user DB 1822 change as a result of acquiring movement-related information and providing care suggestions will be described with reference to Figures 30(a) to (f). Figures 30(a) to (f) chronologically show the result information area 2201, which is an area in the user DB 1822 that stores result information. Figure 30(a) shows the initial state of the result information area 2201 of the user DB 802.

[0272] The result information storage module measures the predetermined movement, determines the type, and selects care suggestions, and then writes the result information obtained into the area for one-before-previous result information after performing the shift operation described below on the previous result information stored in user DB 1822. The result information shift operation is an operation in which the contents of the four-before-previous result information are sequentially written into the area for five-before-previous result information, the contents of the three-before-previous result information are written into the area for four-before-previous result information, the contents of the two-before-previous result information are written into the area for three-before-previous result information, and the contents of the one-before-previous result information are written into the area for two-before-previous result information. Once the result information shift operation is complete, the latest result information is written into the area for one-before-previous result information, thereby completing the operation of the result information storage module. An example of the state of user DB1822 after saving the result information, i.e., the result information area 2201, is shown in Figure 30(b) after the first measurement, Figure 30(c) after the second measurement, Figure 30(d) after the third measurement, Figure 30(e) after the fourth measurement, and Figure 30(f) after the fifth measurement.

[0273] [Second Action-Related Information Acquisition Module P6B] Details of the second action-related information acquisition module P6B will be described with reference to Fig. 31. The second action-related information acquisition module P6B includes a most frequent type extraction step S271 that refers to the result information of the most recent five times stored in the user DB 1822 and extracts the most frequent type that is the type that appeared most frequently among them, an extraction success determination step S273 that assigns the step to proceed depending on whether the most frequent type was extracted, a most frequent type second predetermined action-related information conversion step S275 that uses the extracted most frequent type as second predetermined action-related information when extraction is successful, and a final time type second predetermined action-related information conversion step S277 that uses the last time, i.e., the type immediately before, as second predetermined action-related information when extraction fails. In the extraction success determination step S273, if only one type appears most frequently, it is determined that the most frequent type has been extracted; if there are multiple types that appear most frequently (e.g., type "1" appears twice and type "2" appears twice), it is determined that extraction of the most frequent type has failed. Upon completion of the most frequent type second predetermined action related information conversion step S275 or the final type second predetermined action related information conversion step S277, the second action related information acquisition module P6B terminates (second predetermined action related information determination completion step S279). Note that, in extracting the most frequent type, "Null" data, where no type is recorded, is also considered a type. Therefore, as can be easily understood with reference to FIG. 30, if there is no record in the three-times-ago result area, the second predetermined action related information will always be "Null."

[0274] In this embodiment, the second action-related information acquisition module P6B is configured to extract the most frequently occurring type, i.e., the mode (median), which is the type that appears most frequently among the action-related information stored in the user DB 1822. However, the results of other statistical processing can also be used as the second information. For example, as in the fifth embodiment, raw data can be stored, and the type calculated from the average value can be used as the second predetermined action-related information. Alternatively, the median (mode) of the numbers indicating the stored types can be calculated, and the type of that number can be used as the second predetermined action-related information. When the mode or median is used as the result of statistical processing, it is preferable to use discrete values ​​such as type as the action information, as in this embodiment. On the other hand, it is preferable to perform the averaging process using raw data or data normalized from the raw data. When performing the averaging process, it is not necessary to determine the type; the results of the averaging process can be directly provided to a care suggestion selection module using, for example, a deep learning model, to select care suggestions.

[0275] The second motion-related information acquisition module can also be configured to read out only one of the most recently acquired past types. In this case, the user DB 1822 only needs to store one type of past motion-related information, thereby saving storage space. Furthermore, the weight of the current motion-related information and the past motion-related information will naturally be the same. This modification will be described in a later embodiment.

[0276] [Care Suggestion Selection Module P5C] The care suggestion selection module P5C implements a selection unit in cooperation with the server hardware. As shown in FIG. 32 , the care suggestion selection module P5C includes a care suggestion selection step S281 for selecting a care suggestion from the first movement-related information and the second movement-related information, and a care suggestion determination step S283 for determining a care suggestion to be proposed to the user. Upon completion of the care suggestion determination step S283, the care suggestion selection module P5C ends (care suggestion selection completion step S285).

[0277] In the care suggestion selection step S281, the first movement-related information, which is the walking type currently classified by the first movement-related information acquisition module, and the second movement-related information obtained from the user's past walking types stored in the user DB 1822 are used to select a care suggestion to be proposed from the care information in the care suggestion candidate data 2501-2508 shown in FIGS. 33A and 33B. For ease of explanation, the care suggestion candidate data 2501-2508 are data stored in the care suggestion candidate table 1803, categorized by first movement-related information. Note that "stretching" and "insoles" in FIGS. 33A and 33B are the same as those in the fifth embodiment, and therefore will not be described here.

[0278] For example, if the first motion-related information is "4" and the second motion-related information is "3," then "Stretch 1" is selected as the exercise suggestion and "Insole 2" is selected as the product suggestion, as shown in Fig. 33B(d). If the first motion-related information is type "5" and the second motion-related information is type "4," then "Stretch 2" is selected as the exercise suggestion and "Insole 2" is selected as the product suggestion, as shown in Fig. 33B(e). If the second motion-related information is "Null" or type "1," then only the exercise suggestion is selected, and "none" is selected as the product suggestion, i.e., no product suggestion is selected.

[0279] In this embodiment, the care suggestion determination step S283 is executed following the care suggestion selection step S281, and if the past five pieces of second movement-related information contain null, the product suggestion is deleted from the selected care information. This allows the user to try to improve their movement by only exercising for about the first month without the burden of purchasing products, thereby helping to establish a user base.

[0280] 33A(b), even if the second movement-related information is type "1" (no problem), exercise suggestions are made unless the first movement-related information is type "1." This allows care suggestions to be repeated until the patient's walking becomes stable and good, ensuring improvement in movement.

[0281] The server 1001 of this embodiment can also be used as a so-called standalone behavior improvement suggestion device, rather than being connected to a user terminal (smartphone 1004) via the network 1002. That is, health care suggestions can be made by measuring acceleration data during walking using a wearable device or data logger, and acquiring the results directly via a wired or wireless connection or via a storage medium. In this case, the notification control unit can, for example, notify a display device to display the results on the screen, or a printer device to print the results. Alternatively, the notification can be sent by email to the user's smartphone, etc.

[0282] [Seventh Embodiment] Next, a proposal selection system according to a seventh embodiment of the present invention will be described with reference to FIG. 34. In this embodiment, the second action-related information acquisition module of the sixth embodiment is configured to read out only one recently acquired past type. In this case, the user DB 1822 only needs to store one type of past action-related information, thereby saving storage space. Furthermore, the weight of the current action-related information and the past action-related information will naturally be the same. Below, the same configuration as the sixth embodiment will be explained briefly or omitted, and the differences will be mainly explained.

[0283] In this embodiment, the predetermined motion is also walking. That is, both the first predetermined motion and the second predetermined motion are the same walking motion. Therefore, in this embodiment, the first predetermined motion is referred to as the first predetermined motion, and from the second time onwards, the first predetermined motion is referred to as the first predetermined motion, and the second predetermined motion is referred to as the second predetermined motion.

[0284] In this embodiment, too, the movement-related information is a "type" that classifies movements. That is, raw data obtained from the acceleration sensor is used to classify the user's walking movements into types, which will be described later, and movement-related information for selection is obtained. The first time, care suggestions are selected using only the first walking type, but care suggestions based on remeasurements from the second time onwards are selected using the previous walking type (first movement-related information) and the current walking type (second movement information) recorded in the user database (user DB). The classified type and care suggestions are notified to the smartphone (user terminal) 1004 via the server's notification control unit and conveyed to the user.

[0285] The user DB 1901 is the same as in the sixth embodiment, and therefore the description thereof will be omitted.

[0286] This embodiment is realized by the cooperative operation of each module constituting the program of the server 1001 and each module constituting the application program (app) of the smartphone 1004, including a terminal initial module and a repeat module. The cooperation of operations between the modules will be described below.

[0287] When the app is installed on the smartphone 1004 and launched in response to a user operation, a terminal initial module is launched, acquires sensor information when the user performs a predetermined action, and transmits the information to the server 1001 along with user registration information. In response to this, a new user registration module P7 is launched in the server 1001, and type information and care suggestions are returned to the smartphone 1004. A repetition module P8 is then automatically launched in the smartphone 1004, and the sensor information when the user performs a predetermined action is again transmitted to the server 1001. Upon receiving the sensor information, the suggestion module is again launched in the server 1001, and type information and care suggestions are returned to the smartphone 1004. The automatic launch of the weekly repetition module on the smartphone 1004 and the corresponding operation of the re-suggestion module on the server 1001 are repeated until the re-suggestion module determines that further care suggestions are unnecessary, notifies the smartphone 1004 of this, and stops the automatic launch of the weekly repetition module. The operation of the smartphone 1004 is the same as in the sixth embodiment, and only the operation on the server side is different, which will be explained below.

[0288] The server side consists of three modules: a distribution module, a new registration module, and a re-proposal module.

[0289] When the server receives an operation request from the smartphone 1004, the server first executes a sorting module to determine whether the operation request is from a registered user. If the operation request does not include a registered user ID, the server proceeds to a new registration module, and if it does include a registered user ID, the server proceeds to a suggestion module again.

[0290] The new registration module assigns a user ID to the new user received from the smartphone 1004 and newly registers various information about the new user in the user DB. Furthermore, the module acquires sensor information at the time of the first predetermined movement, analyzes the acquired sensor information to determine the movement type, and selects and decides a care suggestion using the determined movement type (predetermined movement information). The module then returns the assigned user ID and the initial care suggestion to the smartphone 1004.

[0291] The re-suggestion module executes the following steps on the server 1001: a re-motion information acquisition step S1101 acquires the user ID and sensor information obtained when the user performs a predetermined motion again and measures it, analyzes the acquired sensor information, and determines the current walking type, which is first motion-related information; a user DB reading step S1103 reads necessary information such as the user's previous type, i.e., second motion-related information, from the user DB; a care suggestion reselection step S1105 selects and determines a care suggestion using the previous walking type, which is the second motion-related information read in the user DB reading step S1103, and the current walking type determined in the re-motion information acquisition step S1101; a notification step S1107 returns the current walking type determined in the re-motion information acquisition step S1101 and the care suggestion determined in the care suggestion reselection step S1105 to the smartphone 1004; and a re-motion information etc. saving step S1109 overwrites and registers result information consisting of the re-motion information, date, and selected care suggestion in the user DB.

[0292] In this embodiment, the initial motion information acquisition step and the second motion information acquisition step are executed by the same motion information acquisition module, and the initial care suggestion selection step and the care suggestion reselection step are executed by the same care suggestion selection module.

[0293] The operation of the motion information acquisition module is the same as that of the first motion-related information acquisition module of the sixth embodiment, and therefore a description thereof will be omitted.

[0294] The care suggestion selection module uses the walking type (first movement-related information) currently classified by the movement information acquisition module and the previous walking type (second movement-related information) stored in the user DB to select a care suggestion to be proposed from the care suggestion candidate table shown in Figures 33A and 33B. Since there is no previous walking type stored in the user DB the first time, a previous walking suggestion is selected from 2501, which is the range where there is no data, i.e., "Null".

[0295] In this embodiment, too, only exercise, i.e., stretching, is suggested initially, and the insoles, which are care products, are not suggested. This is because if care products are suggested from the beginning, the purchase of the care products may become a barrier and the user may not continue with health care.

[0296] In this embodiment, both exercise and products, i.e., stretching and insoles, are selected as care suggestions from the second time onwards. As in the sixth embodiment, it is possible to not suggest care products from the fifth time onwards or until one month has passed since the first time.

[0297] The present invention has been described above with reference to the embodiments, but 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. Note that suitable examples of the proposal selection method, proposal selection program, and proposal selection device are the same as those described above for the proposal selection system.

[0298] For example, in the motion improvement suggestion system of the present invention, the server does not necessarily have to be the motion improvement suggestion device of the present invention. That is, some of the functions of the motion improvement suggestion device may be provided on the terminal side. For example, a motion information acquisition unit may be provided on the terminal side, and type classification may be performed on the terminal side. For example, the motion information acquisition unit 1303 of the third embodiment and the first motion information acquisition unit 2401 of the fourth embodiment may be provided on the user terminal rather than on the server. That is, the motion information acquisition unit may be located on either the user terminal or the server. Furthermore, for example, a configuration in which only the normalization process of the motion information acquisition unit is performed on the user terminal and the normalized data is sent to the server would be easily achieved by a person of ordinary skill in the art, once they understand the description of this specification.

[0299] In the above-described embodiment, the raw data is data from an acceleration sensor, but it is also possible to, for example, capture a predetermined movement of the user with a camera, measure the acceleration and range of motion of each part of the body during the predetermined movement from the video image, evaluate the predetermined movement of the user, and use the stored evaluation result and the evaluation result of the predetermined movement obtained by newly measuring it to select care suggestions. There are also various other methods for measuring the predetermined movement of the user, such as a rangefinder, a pressure sensor, and an electromyograph, and the evaluation classification of the predetermined movement differs depending on the data obtained, but in any case, the technical idea of ​​the present invention, which is to select care suggestions by comparing the previous predetermined movement with the current predetermined movement, is maintained.

[0300] The present invention may also be applied to a system consisting of multiple devices or to a single device. Furthermore, the present invention may also be applied when an information processing program that realizes the functions of the embodiments 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 realize the functions of the present invention, a medium storing the program, a WWW (World Wide Web) server from which the program is downloaded, and a processor that executes the program. In particular, the technical scope of the present invention includes at least a non-transitory computer-readable medium storing a program that causes a computer to execute the processing steps included in the above-described embodiments.

[0301] The following supplementary notes are further disclosed regarding the above-described embodiment of the present invention. <1> A suggestion selection device comprising: a motion information acquisition unit that acquires first predetermined motion information while a user is performing a first predetermined motion by moving their body, and second predetermined motion information different from the first predetermined motion information while a user is performing a second predetermined motion different from the first predetermined motion, a selection unit that selects a physical health care suggestion for improving at least one of the first predetermined motion and the second predetermined motion using the first predetermined motion information and the second predetermined motion information, and a notification control unit that notifies a predetermined notification destination of the selected physical health care suggestion. <2> The suggestion selection device according to <1>, further comprising: a reception unit that receives input of a first implementation status of the first physical health care suggestion for improving the first predetermined motion selected by the selection unit, and a determination unit that determines whether the user has implemented the first physical health care suggestion based on the first implementation status, wherein the selection unit selects a second physical health care suggestion for improving the second predetermined motion when the determination unit determines that the user has implemented the first physical health care suggestion. <3> The proposal selection device according to <2>, wherein the determination unit notifies the user that a second predetermined movement is requested when the determination unit determines that the user has performed the first physical health care suggestion. <4> The proposal selection device according to any one of <1> to <3>, wherein the selection unit selects both a first physical health care suggestion for improving the first predetermined movement and a second physical health care suggestion for improving the second predetermined movement. <5> The proposal selection device according to any one of <1> to <4>, wherein the first predetermined movement information and the second predetermined movement information each include one or more selected from upper body trunk angle data, jaw joint angle data, lower body joint angle data, movement speed, and walking data. <6> The proposal selection device according to <5>, wherein the upper body trunk angle data and the jaw joint angle data are angle data in the sagittal plane, the frontal plane, and the horizontal plane, respectively. <7> The proposal selection device according to <5>, wherein the walking data is at least one of the number of steps, walking speed, and stride length.<8> The proposal selection device according to any one of <1> to <7>, wherein the first predetermined motion information and the second predetermined motion information each include joint angle data, a movement speed, and a stride length of a lower body, and further comprising: a first discrimination unit that determines, based on the first predetermined motion information, to which of a plurality of movement types the first predetermined motion belongs according to the joint angle data, the movement speed, and the stride length, and a second discrimination unit that determines, based on the second predetermined motion information, to which of the plurality of movement types the second predetermined motion belongs, and wherein the selector selects the physical health care proposal by taking into account at least one of the discrimination results of the first discrimination unit and the second discrimination unit. <9> The proposal selection device according to <8>, wherein the first judgment unit and the second judgment unit each score angle data of a pelvis, a hip joint, a knee joint, and ankle joint, the movement speed, and the stride length, and judge to which of the plurality of movements the first predetermined motion and the second predetermined motion belong based on a combination of these scores. <10> The proposal selection device according to <8> or <9>, further comprising: a first evaluation unit that calculates a first evaluation value of the first predetermined motion based on the type of motion to which the first predetermined motion applies; and a second evaluation unit that calculates a second evaluation value of the second predetermined motion based on the type of motion to which the second predetermined motion applies, wherein the selector selects the physical health care proposal by taking into account at least one of the first evaluation value and the second evaluation value. <11> The proposal selection device according to any one of <1> to <10>, wherein the physical health care proposal is at least one of a care product to be applied to muscles and joints of the lower body, a gait correction device, a food containing active ingredients, exercise, and rest. <12> The proposal selection device according to <11>, wherein the care product is at least one of taping and sports leggings. <13> The proposal selection device according to <11>, wherein the gait correction device is at least one of a corset for pelvic correction or the like, a supporter, and an insole that has the effect of correcting walking style or posture.<14> The suggestion selection device according to <11>, wherein the food containing an active ingredient is at least one of a supplement, a commercially available health drink, a food containing milk-derived sphingomyelin, which has been reported to improve motor function, and a food containing GABA or citric acid, which has been reported to improve fatigue. <15> The suggestion selection device according to <11>, wherein the exercise is at least one of stretching or yoga. <16> The suggestion selection device according to <11>, wherein the rest is at least one of long sleep; short naps, including power naps and daytime siestas; and staying still in a relaxed position, including sitting and lying down. <17> The suggestion selection device according to <11>, wherein the physical health care suggestion for improving the first predetermined movement is exercise, and the physical health care suggestion for improving the second predetermined movement is insoles. <18> The proposal selection device described in any one of <1> to <17>, wherein the motion information acquisition unit acquires, as the first predetermined motion information, first muscle activity acceleration data from an acceleration sensor positioned on a median line that is the center line between the left and right sides of the user's body, during which the user moves the body to perform the first predetermined motion and is in a muscle activity state, and acquires, as the second predetermined motion information, second muscle activity acceleration data from an acceleration sensor positioned on a median line that is the center line between the left and right sides of the user's body, during which the user moves the body to perform the second predetermined motion and is in a muscle activity state.<19> A proposal selection method using a proposal selection device including a motion information acquisition unit, a selection unit, and a notification control unit, the proposal selection method including: a motion information acquisition step in which the motion information acquisition unit acquires first predetermined motion information while a user is moving their body to perform a first predetermined motion, and second predetermined motion information different from the first predetermined motion information while a user is performing a second predetermined motion different from the first predetermined motion; a selection step in which the selection unit uses the first predetermined motion information and the second predetermined motion information to select a physical health care proposal for improving at least one of the first predetermined motion and the second predetermined motion; and a notification control step in which the notification control unit notifies a predetermined notification destination of the selected physical health care proposal. <20> A suggestion selection program that causes a computer to execute the following steps: a motion information acquisition step of acquiring first predetermined motion information while a user is moving their body to perform a first predetermined motion, and second predetermined motion information different from the first predetermined motion information while a user is performing a second predetermined motion different from the first predetermined motion; a selection step of selecting a physical health care suggestion for improving at least one of the first predetermined motion and the second predetermined motion using the first predetermined motion information and the second predetermined motion information; and a notification control step of notifying a predetermined notification destination of the selected physical health care suggestion. <21> A proposal selection system comprising a user terminal and a proposal selection device connected to the user terminal by wire or wirelessly, wherein the user terminal has a motion information acquisition unit that acquires first predetermined motion information while a user is moving their body to perform a first predetermined motion, and second predetermined motion information different from the first predetermined motion information while a user is performing a second predetermined motion different from the first predetermined motion, and the proposal selection device has: a selection unit that uses the first predetermined motion information and the second predetermined motion information to select a physical health care proposal for improving at least one of the first predetermined motion and the second predetermined motion, and a notification control unit that notifies the user terminal of the selected physical health care proposal.

[0302] The following supplementary notes are further disclosed in relation to the above-described embodiment of the present invention. <Supplementary Note 1> A motion improvement suggestion device comprising: a motion-related information acquisition unit that acquires motion-related information while a user is performing a predetermined motion; a selection unit that selects a physical health care suggestion for improving the predetermined motion; and a notification control unit that notifies a predetermined notification destination of the selected physical health care suggestion, wherein the selection unit selects the physical health care suggestion using the acquired motion-related information. <Supplementary Note 2> The motion improvement suggestion device according to Supplementary Note 1, further comprising: a memory unit that selects the physical health care suggestion using the motion-related information acquired by the motion-related information acquisition unit and past motion-related information of the user stored in the memory unit. <Supplementary Note 3> The motion improvement suggestion device according to Supplementary Note 2, wherein the past motion-related information of the user stored in the memory unit is motion information that directly represents the user's motion. <Supplementary Note 4> The motion improvement suggestion device according to Supplementary Note 3, wherein the predetermined motion is walking, and the motion information stored in the memory unit is normalized by a walking cycle. <Supplementary Note 5> The action improvement suggestion device according to <1> to Supplementary Note 4, wherein the action-related information acquisition unit acquires action-related information from action information while the user is performing a predetermined action. <Supplementary Note 6> The action improvement suggestion device according to Supplementary Note 2, wherein the action-related information acquisition unit acquires action-related information from past action information of the user stored in the storage unit. <Supplementary Note 7> The improvement suggestion device according to Supplementary Note 6, wherein the action information stored in the storage unit is time-series acceleration information output from an acceleration sensor, the action-related information acquisition unit averages a plurality of pieces of the action information stored in the storage unit, determines a plurality of feature amounts of the predetermined action from the averaged action information, and classifies the predetermined action of the user into types using the determined plurality of feature amounts, and the selection unit selects the physical health care suggestion using the type.<Supplementary Note 8> The improvement suggestion device according to Supplementary Note 7, further comprising: a normalization unit that normalizes currently acquired time-series acceleration information to acquire current normalized acceleration information, and stores the current normalized acceleration information in the storage unit; the motion information acquisition unit performs an averaging process using the current normalized acceleration information stored in the storage unit and one or more past normalized acceleration information stored in the storage unit to classify the user's predetermined motion into a type. <Supplementary Note 9> The improvement suggestion device according to Supplementary Note 7, further comprising: the motion information acquisition unit classifies the current predetermined motion into a type based on the currently acquired time-series acceleration information, and classifies the user's predetermined motion into a type based on the past acceleration information stored in the storage unit; and the selection unit selects the physical health care suggestion using both the type of the current predetermined motion and the type of the past predetermined motion. <Supplementary Note 10> The motion improvement suggestion device according to any one of Supplements 2 to 9, wherein the motion-related information used by the selection unit is newer motion-related information among the motion-related information stored in the storage unit that can be used to select the physical health care suggestion. <Supplementary Note 11> The improvement suggestion device according to any one of Supplements 1 to 5, wherein the movement information stored in the memory unit is a type of past predetermined movement into which the predetermined movement has been classified, the movement-related information acquisition unit determines a plurality of feature quantities of the predetermined movement from the acquired movement information and classifies the user's predetermined movement into a type of current predetermined movement using the determined plurality of feature quantities to determine first movement-related information, and determines second movement-related information using the type of past predetermined movement stored in the memory unit, and the selection unit selects the physical health care suggestion using the first movement-related information and the second movement-related information. <Supplementary Note 12> The improvement suggestion device according to Supplementary Note 11, wherein the second movement-related information is the latest type of past predetermined movement into which the predetermined movement has been classified. <Supplementary Note 13> The movement improvement suggestion device according to Supplementary Note 2 or 3, wherein the selection unit selects the physical health care suggestion using the first movement-related information and second movement-related information that is a result of statistical processing of the movement-related information stored in the memory unit.<Supplementary Note 14> The motion improvement suggestion device according to Supplementary Note 6, wherein the statistical processing is an averaging process. <Supplementary Note 15> The motion improvement suggestion device according to Supplementary Note 14, wherein the storage unit stores the motion-related information performed by the user, and the selection unit selects the physical health care suggestion using both the motion-related information of a current predetermined motion acquired by the motion-related information acquisition unit and past predetermined motion-related information resulting from statistical processing of the motion-related information stored in the storage unit. <Supplementary Note 16> The motion improvement suggestion device according to Supplementary Note 14, wherein the statistical processing is a majority vote process. <Supplementary Note 17> The movement improvement suggestion device according to any one of Supplements 2 to 15, further comprising a determination unit that determines whether the movement-related information is stored in the storage unit, wherein the selection unit, when the determination unit determines that the movement-related information is stored in the storage unit, selects the physical health care suggestion using the movement-related information currently acquired by the movement-related information acquisition unit and the past movement-related information stored in the storage unit, and when the determination unit determines that the movement-related information is not stored in the storage unit, selects the physical health care suggestion using the movement-related information acquired by the movement-related information acquisition unit. <Supplementary Note 18> The movement improvement suggestion device according to any one of Supplements 1 to 17, wherein the selection unit selects the physical health care suggestion using a feature amount of the predetermined movement extracted from the movement-related information. <Supplementary Note 19> The movement improvement suggestion device according to Supplementary Note 18, wherein the selection unit selects the physical health care suggestion using a feature amount of the predetermined movement extracted from the movement-related information. <Supplementary Note 20> The motion improvement suggestion device according to any one of Supplements 1 to 19, wherein the selection unit classifies the predetermined motion into which of a plurality of types according to feature amounts of the predetermined motion, and selects the physical health care suggestion using the classification result. <Supplementary Note 21> The motion improvement suggestion device according to any one of Supplements 1 to 20, wherein a display urging the user to perform the predetermined motion is displayed at the predetermined notification destination. <Supplementary Note 22> The motion improvement suggestion device according to any one of Supplements 1 to 21, wherein the predetermined motion is walking. <Supplementary Note 23> The motion improvement suggestion device according to Supplementary Note 22, wherein the motion-related information is at least one of number of steps, walking speed, and stride length.<Supplementary Note 24> The motion improvement suggestion device according to any one of Supplements 2 to 23, wherein the physical health care suggestions include at least a product suggestion, the storage unit stores an implementation status of the product suggestions by the user, and the selection unit selects the physical health care suggestion according to the implementation status. <Supplementary Note 25> The motion improvement suggestion device according to Supplementary Note 1, wherein the motion information acquisition unit acquires first predetermined motion information while the user is performing a first predetermined motion by moving their body, and second predetermined motion information different from the first predetermined motion information while the user is performing a second predetermined motion different from the first predetermined motion. <Supplementary Note 26> The motion improvement suggestion device according to Supplementary Note 25, further comprising: a reception unit that receives input of a first implementation status of the first physical health care suggestion for improving the first predetermined motion selected by the selection unit; and a determination unit that determines whether the user has implemented the first physical health care suggestion based on the first implementation status, wherein the selection unit selects a second physical health care suggestion for improving the second predetermined motion when the determination unit determines that the user has implemented the first physical health care suggestion. <Supplementary Note 27> The movement improvement suggestion device according to Supplementary Note 26, wherein the determination unit notifies the user of a request to perform a second predetermined movement 103 when it determines that the user has performed the first physical health care suggestion. <Supplementary Note 28> The movement improvement suggestion device according to any one of Supplements 25 to 27, wherein the selection unit selects both a first physical health care suggestion for improving the first predetermined movement and a second physical health care suggestion for improving the second predetermined movement. <Supplementary Note 29> The movement improvement suggestion device according to any one of Supplements 25 to 28, wherein the first predetermined movement information and the second predetermined movement information each include one or more selected from upper body trunk angle data, jaw joint angle data, lower body joint angle data, movement speed, and walking data. <Supplementary Note 30> The movement improvement suggestion device according to Supplementary Note 29, wherein the upper body trunk angle data and the jaw joint angle data are angle data in a sagittal plane, a frontal plane, and a horizontal plane, respectively. <Supplementary Note 31> The proposal selection device according to Supplementary Note 29, wherein the walking data is at least one of the number of steps, walking speed, and stride length.<Supplementary Note 32> The movement improvement suggestion device according to any one of Supplementary Notes 25 to 31, wherein the first predetermined movement information and the second predetermined movement information each include joint angle data, movement speed, and stride length of a lower body, and further comprises: a first discrimination unit that determines, based on the first predetermined movement information, to which of a plurality of movement types corresponding to the joint angle data, the movement speed, and the stride length the first predetermined movement corresponds; and a second discrimination unit that determines, based on the second predetermined movement information, to which of the plurality of movement types the second predetermined movement corresponds; and wherein the selection unit selects the physical health care suggestion using at least one of a discrimination result of the first discrimination unit and a discrimination result of the second discrimination unit. <Supplementary Note 33> The movement improvement suggestion device according to Supplementary Note 32, wherein the first and second discrimination units respectively score angle data of the pelvis, hip joints, knee joints, and ankle joints, movement speed, and stride length, and determine to which of a plurality of movements the first predetermined movement and the second predetermined movement apply based on a combination of these scores. <Supplementary Note 34> The movement improvement suggestion device according to Supplementary Note 32 or 33, further comprising: a first evaluation unit that calculates a first evaluation value of the first predetermined movement based on the type of movement to which the first predetermined movement applies; and a second evaluation unit that calculates a second evaluation value of the second predetermined movement based on the type of movement to which the second predetermined movement applies, wherein the selection unit selects the physical health care suggestion taking into account at least one of the first evaluation value and the second evaluation value. <Supplementary Note 35> The movement improvement suggestion device according to any one of Supplementary Notes 25 to 34, wherein the physical health care suggestion is at least one of a care product to be applied to the muscles and joints of the lower body, a gait corrector, a food containing an active ingredient, exercise, and rest. <Supplementary Note 36> The movement improvement suggestion device according to Supplementary Note 35, wherein the care product is at least one of taping and sports leggings. <Supplementary Note 37> The movement improvement suggestion device according to Supplementary Note 35, wherein the gait corrector is at least one of a corset for pelvic correction or the like, a supporter, and an insole that is effective in correcting walking style or posture.<Appendix 38> The motion improvement suggestion device of Appendix 35, wherein the food containing an active ingredient is at least one of a supplement, a commercially available health drink, a food containing milk-derived sphingomyelin which has been reported to have the effect of improving motor function, and a food containing GABA or citric acid which has been reported to have the effect of improving fatigue. <Appendix 39> The motion improvement suggestion device of Appendix 35, wherein the exercise is at least one of stretching or yoga. <Appendix 40> The motion improvement suggestion device of Appendix 35, wherein the rest is at least one of long sleep; short naps including power naps and daytime siestas; and staying still in a relaxed position including sitting and lying down. <Appendix 41> The motion improvement suggestion device of Appendix 35, wherein the physical health care suggestion for improving the first predetermined motion is exercise, and the physical health care suggestion for improving the second predetermined motion is insoles. <Supplementary Note 42> The motion improvement suggestion device according to any one of Supplementary Notes 1 to 41, wherein the motion information acquisition unit acquires, as the first predetermined motion information, first muscle activity acceleration data from an acceleration sensor positioned on a median line that is the center line between the left and right sides of the user's body, during which the user moves the body to perform the first predetermined motion and is in a muscle activity state, and acquires, as the second predetermined motion information, second muscle activity acceleration data from an acceleration sensor positioned on a median line that is the center line between the left and right sides of the user's body, during which the user moves the body to perform the second predetermined motion and is in a muscle activity state.<Supplementary Note 43> A motion improvement suggestion method executed by an information processing device, comprising: a motion-related information acquisition step of acquiring motion-related information while a user is performing a predetermined motion; a selection step of selecting a physical health care suggestion for improving the predetermined motion; and a notification control step of notifying a predetermined notification destination of the selected physical health care suggestion, wherein the selection step selects the physical health care suggestion using the acquired motion-related information, wherein the information processing device has a memory unit that stores past motion-related information which is motion-related information of the predetermined motion that the user has performed in the past, and the motion improvement suggestion method further comprises a reading step of reading out the motion-related information of the past predetermined motion, wherein the selection step selects the physical health care suggestion using the motion-related information acquired in the motion-related information acquisition step and the past motion-related information read in the reading step. <Supplementary Note 44> The movement improvement suggestion method according to Supplementary Note 43, wherein the movement-related information used in the selection step is the most recent movement-related information among the movement-related information that can be read in the reading step and that can be used to select the physical health care suggestion. <Supplementary Note 45> The movement improvement suggestion method according to Supplementary Note 43 or 44, wherein in the selection step, the physical health care suggestion is selected using a result of statistical processing of the movement-related information acquired in the movement-related information acquisition step and the past movement-related information read in the reading step. <Supplementary Note 46> The movement improvement suggestion method according to Supplementary Note 45, wherein the statistical processing is an averaging process. <Supplementary Note 47> The movement improvement suggestion method according to Supplementary Note 43, wherein in the selection step, the physical health care suggestion is selected using the movement-related information acquired in the movement-related information acquisition step and a result of statistical processing of the movement-related information read in the reading step. <Supplementary Note 48> The movement improvement suggestion method according to Supplementary Note 45, wherein the statistical processing is a majority vote process.<Supplementary Note 49> The movement improvement suggestion method according to Supplementary Note 43, further comprising a determination step of determining whether the past movement-related information has been stored in the storage unit, wherein in the selection step, if it is determined in the determination step that the past movement-related information has been stored, the physical health care suggestion is selected using the movement-related information acquired in the movement-related information acquisition step and at least one of the past movement-related information read in the read step, and if it is determined in the determination step that the past movement-related information has not been stored, the physical health care suggestion is selected using the movement-related information acquired in the movement-related information acquisition step. <Supplementary Note 50> The movement improvement suggestion method according to any one of Supplements 43 to 45, wherein in the selection step, the physical health care suggestion is selected using a feature amount of the predetermined movement extracted from the movement-related information. <Supplementary Note 51> The movement improvement suggestion method according to Supplementary Note 50, wherein the physical health care suggestion is selected using a feature amount of the predetermined movement extracted from the movement-related information. <Supplementary Note 52> The movement improvement suggestion method according to Supplementary Note 51, wherein in the selecting step, the predetermined movement is classified into one of a plurality of types according to feature amounts of the predetermined movement, and the physical health care suggestion is selected using the classification result. <Supplementary Note 53> The movement improvement suggestion method according to any one of Supplements 43 to 45, wherein a display urging the user to perform the predetermined movement is displayed at the predetermined notification destination. <Supplementary Note 54> The movement improvement suggestion method according to any one of Supplements 43 to 53, wherein the predetermined movement is walking. <Supplementary Note 55> The movement improvement suggestion method according to any one of Supplements 43 to 54, wherein the physical health care suggestion includes at least a product suggestion,<Supplementary Note 56> A motion improvement suggestion method executed by an information processing device, comprising: a motion information acquisition step of acquiring motion information while a user is performing a predetermined motion; a selection step of selecting a physical health care suggestion for improving the predetermined motion; and a notification control step of notifying a predetermined notification destination of the selected physical health care suggestion, wherein the selection step selects the physical health care suggestion using motion-related information obtained from the acquired motion information, wherein the information processing device has a memory unit that stores motion-related information of the predetermined motions previously performed by the user, and further comprises a reading step of reading out the motion-related information of the past predetermined motions, wherein the selection step selects the physical health care suggestion using the motion information acquired in the motion information acquisition step and the past motion-related information read in the reading step. <Supplementary Note 57> The movement improvement suggestion method according to Supplementary Note 56, wherein the predetermined movement is walking, the movement information is time-series acceleration data acquired from an acceleration sensor, a feature amount of the movement during walking is obtained from the time-series acceleration data, a walking type determined using the obtained feature amount of the movement is set as first movement-related information, and the selecting step selects a physical health care suggestion using the determined walking type and second movement-related information determined from past walking types stored in the memory unit. <Supplementary Note 58> The movement improvement suggestion method according to Supplementary Note 57, wherein the memory unit stores only the type based on the most recently acquired movement information among the past types.<Supplementary Note 59> A proposal selection method by a proposal selection device including a motion information acquisition unit, a selection unit, and a notification control unit, the proposal selection method including: a motion information acquisition step in which the motion information acquisition unit acquires first predetermined motion information while a user is moving their body to perform a first predetermined motion, and second predetermined motion information different from the first predetermined motion information while a user is performing a second predetermined motion different from the first predetermined motion; a selection step in which the selection unit selects a physical health care proposal for improving at least one of the first predetermined motion and the second predetermined motion, using the first predetermined motion information and the second predetermined motion information; and a notification control step in which the notification control unit notifies a predetermined notification destination of the selected physical health care proposal. <Supplementary Note 60> A motion improvement suggestion system comprising a user terminal and a motion improvement suggestion device connected to the user terminal via a network, wherein the user terminal has a sensor that acquires motion data while a user is performing a predetermined motion, the motion improvement suggestion device includes: a selection unit that selects a physical health care suggestion for improving the predetermined motion, and a notification control unit that notifies a predetermined notification destination of the selected physical health care suggestion, wherein a motion-related information acquisition unit acquires motion-related information for the predetermined motion using the motion data acquired by the sensor, a memory unit that stores the motion data or the motion-related information, and the selection unit selects the physical health care suggestion using at least one of the motion data or the motion-related information stored in the memory. <Supplementary Note 61> The motion improvement suggestion system according to Supplementary Note 60, wherein the user's past motion-related information stored in the memory unit is motion information that directly represents the user's motion. <Supplementary Note 62> The movement improvement suggestion system according to Supplementary Note 61, wherein the predetermined movement is walking, and the movement information stored in the storage unit is normalized by a walking cycle. <Supplementary Note 63> The movement improvement suggestion system according to any one of Supplementary Notes 60 to 62, wherein the movement-related information acquisition unit acquires movement-related information from movement information while the user is performing the predetermined movement.<Supplementary Note 64> The movement improvement suggestion device according to Supplementary Note 60, wherein the movement-related information acquisition unit acquires movement-related information from past movement information of the user stored in the storage unit. <Supplementary Note 65> The movement improvement suggestion system according to Supplementary Note 64, wherein the movement information stored in the storage unit is time-series acceleration information output from an acceleration sensor, the movement-related information acquisition unit averages a plurality of pieces of the movement information stored in the storage unit, determines a plurality of feature amounts of the predetermined movement from the averaged movement information, and classifies the predetermined movement of the user into types using the determined plurality of feature amounts, and the selection unit selects the physical health care suggestion using the type. <Supplementary Note 66> The movement improvement suggestion system according to Supplementary Note 65, comprising a normalization unit that normalizes currently acquired time-series acceleration information to acquire currently normalized acceleration information, and stores the currently normalized acceleration information in the memory unit, and the movement information acquisition unit performs an averaging process using the currently normalized acceleration information stored in the memory unit and one or more pieces of past normalized acceleration information stored in the memory unit, to classify the user's predetermined movement into a type. <Supplementary Note 67> The movement improvement suggestion system according to Supplementary Note 65, wherein the movement information acquisition unit classifies the current predetermined movement into a type based on the currently acquired time-series acceleration information, and classifies the user's predetermined movement into a type based on past acceleration information stored in the memory unit, and the selection unit selects the physical health care suggestion using both the type of the current predetermined movement and the type of the past predetermined movement. <Appendix 68> The movement improvement suggestion system according to any one of Appendices 60 to 67, wherein the movement-related information used by the selection unit is new movement-related information among the movement-related information stored in the storage unit that can be used to select the physical health care suggestion.<Supplementary Note 69> The motion improvement suggestion system according to any one of Supplements 60 to 63, wherein the motion information stored in the memory unit is a type of past predetermined motion into which the predetermined motion has been classified, the motion-related information acquisition unit determines a plurality of feature quantities of the predetermined motion from the acquired motion information, and classifies the user's predetermined motion into a type of current predetermined motion using the determined plurality of feature quantities to determine first motion-related information, and determines second motion-related information using the type of past predetermined motion stored in the memory unit, and the selection unit selects the physical health care suggestion using the first motion-related information and the second motion-related information. <Supplementary Note 70> The motion improvement suggestion system according to Supplementary Note 60 or 61, wherein the selection unit selects the physical health care suggestion using a result of statistical processing of the motion-related information acquired by the motion-related information acquisition unit and the motion-related information stored in the memory unit. <Supplementary Note 71> The motion improvement suggestion system according to Supplementary Note 70, wherein the selection unit selects the physical health care suggestion using a result of statistical processing of the motion-related information acquired by the motion-related information acquisition unit and the motion-related information stored in the memory unit. <Supplementary Note 72> The movement improvement suggestion system according to Supplementary Note 60, wherein the storage unit stores the movement-related information performed by the user, and the selection unit selects the physical health care suggestion using both the movement-related information of the current predetermined movement acquired by the movement-related information acquisition unit and past predetermined movement-related information obtained by statistically processing the movement-related information stored in the storage unit. <Supplementary Note 73> The movement improvement suggestion system according to Supplementary Note 72, wherein the statistical processing is majority voting processing. <Supplementary Note 74> The movement improvement suggestion system of any one of Supplementary Notes 60 to 73, further comprising a judgment unit that judges whether the movement-related information is stored in the memory unit, wherein the selection unit, when the judgment unit judges that the movement-related information is stored in the memory unit, selects the physical health care suggestion using the movement-related information currently acquired by the movement-related information acquisition unit and the past movement-related information stored in the memory unit, and when the judgment unit judges that the movement-related information is not stored in the memory unit, selects the physical health care suggestion using the movement-related information acquired by the movement-related information acquisition unit.<Supplementary Note 75> The movement improvement suggestion system according to any one of Supplements 60 to 74, wherein the selection unit selects the physical health care suggestion using a feature amount of the predetermined movement extracted from the movement-related information. <Supplementary Note 76> The movement improvement suggestion system according to Supplementary Note 75, wherein the feature amount includes a magnitude of joint movement. <Supplementary Note 77> The movement improvement suggestion system according to any one of Supplements 60 to 76, wherein the selection unit classifies the predetermined movement into which of a plurality of types according to the feature amount of the predetermined movement it falls, and selects the physical health care suggestion using the classification result. <Supplementary Note 78> The movement improvement suggestion system according to any one of Supplements 60 to 77, wherein a display urging the user to perform the predetermined movement is displayed at the predetermined notification destination. <Supplementary Note 79> The movement improvement suggestion system according to any one of Supplements 60 to 78, wherein the predetermined movement is walking. <Supplementary Note 80> The movement improvement suggestion system according to Supplementary Note 79, wherein the predetermined movement is walking. <Supplementary Note 81> The movement improvement suggestion system according to any one of Supplements 60 to 80, wherein the physical health care suggestions include at least a product suggestion, the storage unit stores an implementation status of the product suggestions by the user, and the selector selects the physical health care suggestion according to the implementation status. <Supplementary Note 82> A suggestion selection system comprising a user terminal and a suggestion selection device connected to the user terminal by wired or wireless connection, wherein the user terminal has a movement information acquisition unit that acquires first predetermined movement information while the user is performing a first predetermined movement by moving their body, and second predetermined movement information different from the first predetermined movement information while the user is performing a second predetermined movement different from the first predetermined movement, the suggestion selection device having: a selection unit that selects a physical health care suggestion for improving at least one of the first predetermined movement and the second predetermined movement using the first predetermined movement information and the second predetermined movement information, and a notification control unit that notifies the user terminal of the selected physical health care suggestion. <Supplementary Note 83> The user terminal used in the operation improvement suggestion system according to Supplementary Note 60, the user terminal having a predetermined operation start instruction unit.<Supplementary Note 84> A program for a user terminal used to have a user perform a predetermined action and acquire data related to the user's predetermined action, the program causing an information processing device of the user terminal to execute the following steps: an action preparation command step of instructing the user to prepare for the predetermined action, an action preparation completion determination step of determining whether the user is ready for the action, an action start command step of instructing the user to start the action, and a step of acquiring the data. <Supplementary Note 85> The program for a user terminal according to Supplementary Note 84, further comprising: a suggestion step of presenting to the user a care suggestion regarding the predetermined action based on the acquired data, and a restart setting step of activating an implementation determination step, which determines whether the user has implemented the suggestion, a predetermined period after the suggestion step is completed. <Supplementary Note 86> A suggestion selection program that causes a computer to execute the following steps: a motion information acquisition step of acquiring first predetermined motion information while a user is moving their body to perform a first predetermined motion, and second predetermined motion information different from the first predetermined motion information while a user is performing a second predetermined motion different from the first predetermined motion; a selection step of selecting a physical health care suggestion for improving at least one of the first predetermined motion and the second predetermined motion, using the first predetermined motion information and the second predetermined motion information; and a notification control step of notifying a predetermined notification destination of the selected physical health care suggestion.

[0303] According to the present invention, it is possible to make suggestions for improving the user's actions.

Claims

1. A movement improvement suggestion device comprising: a movement-related information acquisition unit that acquires movement-related information while a user is performing a predetermined movement; a selection unit that selects a physical health care suggestion for improving the predetermined movement; and a notification control unit that notifies a predetermined notification destination of the selected physical health care suggestion, wherein the selection unit selects the physical health care suggestion using the acquired movement-related information.

2. A motion improvement suggestion device as described in claim 1, further comprising a memory unit, wherein the selection unit selects the physical health care suggestion using the motion-related information acquired by the motion-related information acquisition unit and the user's past motion-related information stored in the memory unit.

3. The motion improvement suggestion device described in claim 2, wherein the motion-related information stored in the memory unit and used by the selection unit is newer motion-related information among the motion-related information stored in the memory unit that can be used to select the physical health care suggestion.

4. A motion improvement suggestion device as described in claim 2 or 3, wherein the selection unit statistically processes the motion-related information acquired by the motion-related information acquisition unit and the motion-related information stored in the memory unit, and selects the physical health care suggestion using the results of the statistical processing.

5. The operation improvement suggestion device according to claim 4, wherein the statistical processing is an averaging process.

6. A motion improvement suggestion device as described in claim 2 or 3, wherein the selection unit selects the physical health care suggestion using the motion-related information acquired by the motion-related information acquisition unit and the results of statistical processing of the motion-related information stored in the memory unit.

7. The operation improvement suggestion device according to claim 6, wherein the statistical processing is majority voting processing.

8. A motion improvement suggestion device as described in claim 2, further comprising a judgment unit that judges whether the motion-related information is stored in the memory unit, wherein the selection unit, when the judgment unit judges that the motion-related information is stored in the memory unit, selects the physical health care suggestion using the motion-related information acquired by the motion-related information acquisition unit and at least one of the motion-related information stored in the memory unit, and when the judgment unit judges that the motion-related information is not stored in the memory unit, selects the physical health care suggestion using the motion-related information acquired by the motion-related information acquisition unit.

9. A motion improvement suggestion device as described in any one of claims 1 to 3, wherein the selection unit selects the physical health care suggestion using features of the specified motion extracted from the motion-related information.

10. The motion improvement suggestion device of claim 9, wherein the selection unit classifies the specified motion into one of a plurality of types according to the characteristics of the specified motion, and uses the classification result to select the physical health care suggestion.

11. An action improvement suggestion device according to any one of claims 1 to 3, wherein a display prompting the user to perform the predetermined action is displayed at the predetermined notification destination.

12. A motion improvement suggestion device according to any one of claims 1 to 3, wherein the predetermined motion is walking.

13. The behavior improvement suggestion device described in claim 2, wherein the physical health care suggestions include at least product suggestions, the memory unit stores the implementation status of the product suggestions by the user, and the selection unit selects the physical health care suggestions according to the implementation status.

14. A motion improvement suggestion method executed by an information processing device, comprising: a motion-related information acquisition step of acquiring motion-related information while a user is performing a predetermined motion; a selection step of selecting a physical health care suggestion for improving the predetermined motion; and a notification control step of notifying a predetermined notification destination of the selected physical health care suggestion, wherein the selection step selects the physical health care suggestion using the acquired motion-related information.

15. A method for suggesting movement improvement as described in claim 14, wherein the information processing device includes a memory unit that stores the movement-related information of the specified movement performed by the user, and in the selection step, the physical health care suggestion is selected using the movement-related information acquired in the movement-related information acquisition step and the movement-related information stored in the memory unit.

16. A movement improvement suggestion method as described in claim 15, wherein in the selection step, the physical health care suggestion is selected using movement-related information that is the result of statistical processing of the movement-related information acquired in the movement-related information acquisition step and the movement-related information stored in the memory unit.

17. The method for suggesting improvements to an operation according to claim 16, wherein the statistical processing is an averaging process.

18. A movement improvement suggestion method as described in claim 15, wherein in the selection step, the physical health care suggestion is selected using the first movement-related information acquired in the movement-related information acquisition step and second movement-related information that is the result of statistical processing of the movement-related information stored in the memory unit.

19. The method for suggesting improvements to an operation according to claim 18, wherein the statistical processing is a majority voting process.

20. A movement improvement suggestion method as described in claim 15, further comprising a determination step of determining whether or not the movement-related information is stored in the memory unit, wherein in the selection step, when it is determined in the determination step that the movement-related information is stored in the memory unit, the physical health care suggestion is selected using the movement-related information acquired in the movement-related information acquisition step and at least one of the movement-related information stored in the memory unit, and when it is determined in the determination step that the movement-related information is not stored in the memory unit, the physical health care suggestion is selected using the movement-related information acquired in the movement-related information acquisition step.

21. The method for suggesting improvement of an action according to claim 14 or 15, wherein a message prompting the user to perform the predetermined action is displayed at the predetermined notification destination.

22. A method for suggesting improvement of a movement according to claim 14 or 15, wherein the predetermined movement is walking.

23. The behavior improvement suggestion method described in claim 15, wherein the physical health care suggestions include at least product suggestions, the storage step stores the implementation status of the product suggestions by the user, and the selection step selects the physical health care suggestions according to the implementation status.

24. A movement improvement suggestion system comprising a user terminal and a movement improvement suggestion device connected to the user terminal by wire or wirelessly, wherein the user terminal has a sensor that acquires movement data while a user is performing a predetermined movement, and the movement improvement suggestion device includes: a selection unit that selects a physical health care suggestion for improving the predetermined movement; a notification control unit that notifies a predetermined notification destination of the selected physical health care suggestion; and a memory unit, wherein a movement-related information acquisition unit acquires movement-related information for the predetermined movement using the movement data acquired by the sensor, the memory unit stores the movement data or the movement-related information, and the selection unit selects the physical health care suggestion using at least one or more of the movement data or the movement-related information stored in the memory unit.

25. A user terminal used in the behavior improvement suggestion system according to claim 24, comprising a predetermined behavior start instruction unit.

26. A program for a user terminal used to have a user perform a predetermined action and acquire data related to the user's predetermined action, the program causing an information processing device of the user terminal to execute the following steps: an action preparation command step of commanding the user to prepare for the predetermined action; an action preparation completion determination step of determining whether the user is ready for the action; an action start command step of commanding the user to start the action; and a step of acquiring the data.

27. A program for a user terminal as described in claim 26, further comprising: a suggestion step of presenting to the user care suggestions regarding the specified action based on the acquired data; and a restart setting step of starting an implementation determination step of determining whether the user has performed the suggestion after a predetermined period has elapsed after the end of the suggestion step.

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