Information processing apparatus, information processing method, program

Abstract

To provide a technique allowing for provision of support information for performing a sport tailored to an object person.SOLUTION: An information processing device 30 according to a disclosed embodiment comprises: an action data acquisition unit 301 for acquiring a plurality of pieces of data on a prescribed action of an object person; a result data acquisition unit 302 for acquiring data on a result acquired on the basis of the prescribed action; and a main factor action estimation unit 304 for estimating data having a relatively high influence degree to the result among the plurality of pieces of data on the prescribed action on the basis of the plurality of pieces of data about the prescribed action for multiple times and the data about the result.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus and the like.

Background Art

[0002] For example, a technique for analyzing a predetermined motion of a specific sport (e.g., a golf swing motion) is known (see, for example, Patent Document 1).

[0003] According to such a technique, using the analysis result, a store clerk or the like can propose an implement suitable for the subject person, or a sports instructor or the like can propose an improvement of the motion suitable for the subject person.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, although the above technique can perform motion analysis, it cannot provide support information such as a proposal of an implement for the subject person or a proposal of an improvement of the motion based on the analysis result, and depends on the experience of a store clerk or an instructor.

[0006] Therefore, in view of the above problems, an object is to provide a technique capable of providing support information for performing a sport suitable for a subject person.

Means for Solving the Problems

[0007] To achieve the above object, in one embodiment of the present disclosure, a subject person executed by a first acquisition unit that acquires a plurality of first data related to a predetermined motion, executed by the subject obtained based on the predetermined operation completed regarding the result second a second acquisition unit that acquires data executed by the subject for a plurality of times of the predetermined operation regarding the above a plurality of first data and the second based on the data executed by the subject for the predetermined operation regarding the above a plurality of first among the plurality of data obtainable based on the predetermined operation executed by the subject data having a relatively high influence degree on the result first an estimation unit that estimates the data an output unit that outputs support information for improving the result obtainable based on the predetermined operation executed by the subject, based on the estimation result of the estimation unit and includes the previous recording complex a plurality of first data includes data related to the movement of a predetermined body part of the subject in the predetermined operation the including view , The output unit outputs the support information for optimizing the result obtainable based on the predetermined operation executed by the subject, and represents the optimal value of the first data, among the plurality of first data, estimated by the estimation unit and having a relatively high influence degree on the result obtainable based on the predetermined operation executed by the subject an information processing apparatus is provided

[0008] Also, in another embodiment of the present disclosure an information processing method executed by an information processing apparatus, comprising a subject executed by a first acquisition step of acquiring a plurality of data related to a predetermined operation first and executed by the subject obtained based on the predetermined operation completed regarding the result second a second acquisition step of acquiring data executed by the subject for a plurality of times of the predetermined operation regarding the above a plurality of first data and the second based on the data executed by the subject for the predetermined operation regarding the above a plurality of first among the plurality of data obtainable based on the predetermined operation executed by the subject data having a relatively high influence degree on the result first an estimation step of estimating the data an output step of outputting support information for improving the result obtainable based on the predetermined operation executed by the subject, based on the estimation result in the estimation step and includes the previousrecording complex The number of first data includes data related to the movement of a predetermined body part of the subject in the predetermined operation the and an information processing method is provided. view , In the output step, the support information for optimizing the result obtainable based on the predetermined operation executed by the subject is output, and represents the optimal value of the first data, among the plurality of first data, estimated in the estimation step and having a relatively high influence degree on the result obtainable based on the predetermined operation executed by the subject

[0009] In still another embodiment of the present disclosure, an information processing apparatus is caused to execute executed by a first acquisition step of acquiring a plurality of first data related to a predetermined operation of a subject, a second acquisition step of acquiring data related to a result obtained based on the predetermined operation, executed by the subject completed and an estimation step of estimating data having a relatively high influence on the result among the plurality of second data based on the plurality of data and the executed by the subject regarding the above data related to the predetermined operation first for a plurality of times. second executed by the subject regarding the above first obtainable based on the predetermined operation executed by the subject first an output step of outputting support information for improving the result obtainable based on the predetermined operation executed by the subject, based on the estimation result in the estimation step recording complex first the view In the output step, the support information for optimizing the result obtained based on the predetermined operation executed by the target person, which represents the optimal value of the first data having a relatively high influence degree on the result obtained based on the predetermined operation executed by the target person among the plurality of first data estimated in the estimation step, is output.

[0010] The number of data includes data related to the movement of a predetermined body part of the subject in the predetermined operation the and a program is provided. view , In the output step, the support information for optimizing the result obtained based on the predetermined operation executed by the target person, which represents the optimal value of the first data having a relatively high influence degree on the result obtained based on the predetermined operation executed by the target person among the plurality of first data estimated in the estimation step, is output.

[0010] ​According to the above-described embodiment, the information processing apparatus can grasp data with a high degree of influence on the result of the target person among a plurality of data related to a predetermined operation. Therefore, the information processing apparatus can provide the target person with support information for improving the operation corresponding to the data with a high degree of influence on the result of the target person, support information regarding tools adapted to the operation corresponding to the data with a high degree of influence on the result of the target person, and the like.

Effect of the Invention

[0011] According to the above-described embodiment, it is possible to provide a technique capable of providing support information for performing sports adapted to the target person.

Brief Description of the Drawings

[0012]

Figure 1

Figure 2

Figure 3

Figure 4

Mode for Carrying Out the Invention

[0013] Hereinafter, embodiments will be described with reference to the drawings.

[0014] [Outline of Information Providing System] First, with reference to FIG. 1, the outline of the information providing system 1 according to the present embodiment will be described.

[0015] FIG. 1 is a schematic diagram of the information providing system 1.

[0016] As shown in FIG. 1, the information providing system 1 includes an operation data acquisition device 10, a result data acquisition device 20, and an information processing device 30. The operation data acquisition device 10 and the result data acquisition device 20 and the information processing device 30 may be installed in the same location (for example, the same facility), or may be installed in different remote locations from each other.

[0017] The operation data acquisition device 10 acquires a plurality of data (hereinafter, "operation data") related to a predetermined operation of a person. The operation data acquisition device 10 acquires, for example, a plurality of operation data related to a predetermined operation when a person performs a specific sport. The predetermined operation is, for example, a swing operation of golf or tennis. The operation data acquisition device 10 is communicably connected to the information processing device 30, and the plurality of operation data acquired by the operation data acquisition device 10 are taken into the information processing device 30.

[0018] The result data acquisition device 20 acquires data (hereinafter, "result data") related to the result obtained (output) by a predetermined operation. For example, when a person performs a golf swing operation, the result data may include, for example, data related to the club head speed and the flight distance of the golf ball. The result data acquisition device 20 is communicably connected to the information processing device 30, and the data acquired by the result data acquisition device 20 are taken into the information processing device 30.

[0019] The information processing device 30 provides the user with support information for improving the result according to the operation (motion characteristics) of the subject based on the plurality of operation data of the subject and the result data corresponding to the plurality of operation data input from the operation data acquisition device 10 and the result data acquisition device 20. The user includes, for example, a store clerk who proposes sports equipment to the subject. In addition, the user includes, for example, an instructor (for example, an instructor) who gives sports guidance to the subject. In addition, the user includes, for example, the subject corresponding to the operation data.

[0020] The support information includes, for example, information regarding tools for improving results (hereinafter referred to as "tool improvement support information"). The tool improvement support information includes, for example, information representing a specific product (tool) for improving results and information representing the functional characteristics of the tool for improving results. Further, the support information includes, for example, support information for suppressing the dispersion (variation) of results and improving the reproducibility (stability) of results (hereinafter referred to as "reproducibility improvement support information"). Further, the support information includes, for example, information for optimizing results (hereinafter referred to as "optimization support information").

[0021] In this way, the information providing system 1 provides the user with support information for improving the results in accordance with the operation (motion characteristics) of the target person through the information processing device 30.

[0022] [Configuration of Information Providing System] Next, in addition to FIG. 1, with reference to FIGS. 2 and 3, the specific configuration of the information providing system 1 will be described.

[0023] FIG. 2 is a diagram showing an example of the hardware configuration of the information processing device 30. FIG. 3 is a functional block diagram showing an example of the configuration of the information providing system 1.

[0024] The functions of the information processing device 30 may be realized by any hardware, or any combination of hardware and software, etc. For example, as shown in FIG. 2, the information processing device 30 includes a drive device 31, an auxiliary storage device 32, a memory device 33, a CPU 34, an interface device 35, a display device 36, and an input device 37, each of which is connected by a bus B.

[0025] The programs that implement various functions of the information processing apparatus 30 are provided, for example, by a portable recording medium 31A such as a CD-ROM (Compact Disc Read Only Memory), a DVD-ROM (Digital Versatile Disc Read Only Memory), or a USB (Universal Serial Bus) memory. When the recording medium 31A storing the program is set in the drive device 31, the program is installed from the recording medium 31A via the drive device 31 into the auxiliary storage device 32. Also, the program may be downloaded from another computer via a communication network and installed in the auxiliary storage device 32.

[0026] The auxiliary storage device 32 stores the installed various programs and also stores necessary files, data, etc.

[0027] When there is an instruction to start a program, the memory device 33 reads out the program from the auxiliary storage device 32 and stores it.

[0028] The CPU 34 executes the various programs stored in the memory device 33 and realizes various functions related to the information processing apparatus 30 according to the programs.

[0029] The interface device 35 is used as an interface for connecting to an external device through an external communication line (for example, a one-to-one communication line or a communication network, etc.). The interface device 35 may include a plurality of types of interface devices according to the difference in the communication form with the external device.

[0030] The display device 36 displays a GUI (Graphical User Interface), for example, according to the program executed by the CPU 34. The display device 36 is, for example, a liquid crystal display or an organic EL (Electroluminescence) display, etc.

[0031] The input device 37 is used to allow various instructions regarding the information processing device 30 to be input by an operator, administrator, or the like of the information processing device 30. The input device 37 includes, for example, an operation input device that receives a user's operation input. The operation input device may include, for example, a keyboard, a mouse, a touch panel mounted on the display device 36, a touch pad, buttons, toggles, levers, rotary switches, and the like. Further, the input device 37 may include, for example, a voice input device or a gesture input device that receives a user's voice input or gesture input. The voice input device includes, for example, a microphone. The gesture input device includes an imaging device that images the content of the user's gesture (for example, a moving image).

[0032] The information processing device 30 realizes various functions by executing, for example, a program installed in the auxiliary storage device 32 with the CPU 34. Specifically, as shown in FIG. 3, the information processing device 30 includes, as functional elements, an operation data acquisition unit 301, a result data acquisition unit 302, an analysis unit 303, a main factor operation estimation unit 304, and a support information providing unit 305.

[0033] The operation data acquisition unit 301 (an example of a first acquisition unit) acquires a plurality of operation data input (received) from the operation data acquisition device 10 from a reception buffer or the like.

[0034] The plurality of operation data includes, for example, data regarding the position of a predetermined body part (for example, each joint part, etc.) of the target person (person). Further, the plurality of operation data includes, for example, data regarding the speed of a predetermined body part of the target person. Further, the plurality of operation data includes, for example, data regarding the acceleration of a predetermined body part of the target person. Further, the plurality of operation data includes, for example, information regarding the angle of a predetermined body part (for example, two link parts constituting a joint part) of the target person. Further, the plurality of operation data includes, for example, data regarding the angular velocity of a predetermined body part of the target person beData is included. Also, the plurality of motion data includes, for example, data related to the angular acceleration of a predetermined body part of the subject. Also, the plurality of motion data includes, for example, data related to the energy (e.g., kinetic energy, potential energy, etc.) of a predetermined body part of the subject. Also, the plurality of motion data includes, for example, data related to the torque of a predetermined body part of the subject. Also, the plurality of motion data includes, for example, data related to the position of a sports equipment (e.g., a golf club, a tennis racket, etc.). Also, the plurality of motion data includes, for example, data related to the speed of a sports equipment. Also, the plurality of motion data includes, for example, data related to the acceleration of a sports equipment. Also, the plurality of motion data includes, for example, data related to the angle of a sports equipment. Also, the plurality of motion data includes, for example, data related to the angular velocity of a sports equipment. Also, the plurality of motion data includes, for example, data related to the angular acceleration of a sports equipment. Also, the plurality of motion data includes, for example, data related to the energy (kinetic energy, potential energy, etc.) of a sports equipment. Also, the plurality of motion data includes, for example, data related to the torque of a sports equipment. Also, the plurality of motion data includes, for example, data related to the approach state (e.g., speed, direction, etc.) of the equipment (e.g., a club) with respect to the ball (e.g., a golf ball). Also, the plurality of motion data includes, for example, data related to the plantar pressure of the subject (person). Also, the plurality of motion data includes, for example, data related to the ground reaction force acting on the subject.

[0035] The motion data acquisition device 10 includes, for example, an inertial sensor provided on at least one of a predetermined body part of a subject (person) and an implement. The inertial sensor may include, for example, an acceleration sensor, an angular velocity sensor, and the like. Further, the motion data acquisition device 10 includes, for example, an imaging device capable of imaging a moving image of at least one of a subject including an implement held (e.g., a golf club) and a ball (e.g., a golf ball). Further, the motion data acquisition device 10 includes, for example, a distance sensor that acquires (outputs) data regarding the distance between at least one of the body part of the subject and the implement. The distance sensor includes, for example, an ultrasonic sensor, a millimeter-wave radar, LIDAR (Light Detecting and Ranging), a depth sensor, and the like. Further, the motion data acquisition device 10 includes, for example, a foot pressure meter that acquires (outputs) data regarding the surface pressure of the sole of the subject's foot. Further, the motion data acquisition device 10 includes, for example, a floor reaction force meter that acquires (outputs) data regarding the floor reaction force acting on the subject.

[0036] The result data acquisition unit 302 (an example of the second acquisition unit) acquires the result data input (received) from the result data acquisition device 20 from a reception buffer or the like.

[0037] The result data includes, for example, data related to the entry state of the implement with respect to the ball. This is because the entry state of the implement with respect to the ball is an action that causes the state (result) of the subsequent ball after it is hit, and at the same time, it is also the result of the action at the previous timing. Similarly, a part of the operation data included in the above-described examples may be used as result data. Also, the result data includes, for example, data related to the state of the ball (such as speed and direction, etc.) when the ball is hit by the implement (for example, at the impact of a golf club on a golf ball). Also, the result data includes, for example, data related to the trajectory of the ball hit by the implement. Also, the result data includes data related to the flight distance of the ball (for example, a golf ball). Also, the result data includes, for example, data related to the surface pressure on the sole of the foot of the subject (person). Also, the result data includes, for example, data related to the ground reaction force acting on the subject. It is considered that the surface pressure on the sole of the foot and the change in the ground reaction force represent the situation of the swing operation and also represent the result as it occurs as a result of the swing operation. Also, the result data includes, for example, data related to the evaluation by the instructor (for example, an instructor). The evaluation by the instructor includes, for example, a round evaluation based on at least one of the actions, thoughts, and results of the subject during a round on a simulator simulating a golf course, the thinking of the subject, and the results of the swing operation. In the round evaluation, for example, evaluations are made for each item of situation judgment, club selection, routine, ball directionality, and distance perception. Also, the evaluation by the instructor includes, for example, an operation evaluation related to the flexibility and range of motion of the user's body parts. In the operation evaluation, an evaluation is made as to whether a predetermined operation (for example, seven defined operations) can be correctly performed.

[0038] The result data acquisition device 20 includes, for example, an inertial sensor attached to at least one of the tool and the ball held by the subject. Further, the result data acquisition device 20 includes, for example, an imaging device that captures a moving image of at least one of the tool and the ball held by the subject. Further, the result data acquisition device 20 includes, for example, a distance sensor that acquires (outputs) data regarding the distance from the tool and the ball held by the subject. The result data acquisition device 20 includes, for example, an orbit measurement device that acquires (outputs) data regarding the orbit of the ball hit by the tool. The orbit measurement device includes, for example, a GPS (Global Positioning System) sensor attached to the ball. Further, the motion data acquisition device 10 includes, for example, a foot pressure meter that acquires (outputs) data regarding the surface pressure of the sole of the subject's foot. Further, the motion data acquisition device 10 includes, for example, a ground reaction force meter that acquires (outputs) data regarding the ground reaction force acting on the subject.

[0039] Note that part or all of the motion data acquisition device 10 and the result data acquisition device 20 may have a common configuration.

[0040] The analysis unit 303 analyzes the relationship between the plurality of motion data and the result data based on a combination of a plurality of motion data and result data corresponding to a plurality of predetermined motions performed by the subject, which are acquired by the motion data acquisition unit 301 and the result data acquisition unit 302. The analysis unit 303 outputs the analysis result to the main factor motion estimation unit 304.

[0041] For example, the analysis unit 303 performs machine learning (supervised learning) based on a combination of a plurality of motion data and result data for a plurality of times, and creates a learned model (regression model) that estimates the result data from the plurality of motion data as a result of the machine learning. The regression model is, for example, a function that takes a plurality of motion data as input and outputs the result data. The regression model is represented, for example, by the following formula (1), where the motion data is Xn (n = 1, 2,..., N), the result data is Y, the weighting coefficient of each motion data Xn is wn, and the multiplier of the motion data Xn is kn.

[0042] Y = X1 k1 ·w1 + X2 k2 ·w2 +... + XN kN ·wN ··· (1) The analysis unit 303 may perform machine learning using a plurality of pieces of operation data and result data for a plurality of times, and identify the weighting coefficient wn and the multiplier kn.

[0043] Also, the analysis unit 303 may reduce the number of pieces of operation data used for analysis (machine learning) by using a known dimensionality reduction method (for example, principal component analysis, singular value decomposition, etc.). Thereby, the analysis unit 303 can create a regression model more easily.

[0044] The analysis unit 303 may perform machine learning using, for example, a combination of a plurality of pieces of operation data and result data for a plurality of times at a predetermined timing during a predetermined operation of the subject, generate a learned model, and output it to the main factor motion estimation unit 304 as an analysis result. The predetermined timing is, for example, the timing of the top, the timing of halfway down, the timing of halfway back, the timing immediately before the impact between the club and the ball, etc. in the golf swing motion. Also, the predetermined timing is, for example, the timing of the takeback, the timing immediately before the impact between the ball and the racket, the timing of the follow-through, etc. in the tennis swing motion.

[0045] Also, the analysis unit 303 may perform machine learning based on, for example, a combination of a plurality of pieces of operation data and result data for a plurality of times for each of a plurality of timings during a predetermined operation of the subject, and generate a learned model for each of the plurality of timings. Then, the analysis unit 303 may output the learned model with the highest estimation accuracy among the generated learned models to the main factor motion estimation unit 304 as an analysis result. The estimation accuracy of the generated learned model becomes higher as the difference between the estimated value of the result data obtained by inputting a plurality of pieces of operation data into the learned model and the actual result data becomes smaller, for example.

[0046] Based on the analysis result of the analysis unit 303, the main factor action estimation unit 304 (an example of an estimation unit) estimates action data (hereinafter, "main factor action data") with a relatively high degree of influence on the result data among a plurality of action data. The main factor action data is, for example, the action data with the highest degree of influence on the result data among the plurality of action data.

[0047] For example, the main factor action estimation unit 304 may estimate the main factor action data among a plurality of action data based on the weighting coefficients of the learned model (regression model). Specifically, the main factor action estimation unit 304 may determine that the greater the weighting coefficient, the higher the degree of influence on the result data of the action data, and the smaller the weighting coefficient, the lower the degree of influence on the result data.

[0048] In addition, for example, the main factor action estimation unit 304 may estimate the main factor action data among a plurality of action data based on the change rate of the result data when the action data of the learned model is changed. Specifically, the main factor action estimation unit 304 may determine that the higher the change rate of the result data when the action data of the learned model is changed, the higher the degree of influence on the result data of the action data, and the lower the change rate, the lower the degree of influence on the result data.

[0049] The main factor action estimation unit 304 may output information regarding the action of the subject corresponding to the main factor action data (hereinafter, "main factor action information"). The main factor action information includes, for example, information representing the main factor action item (hereinafter, "main factor action item") among the items (hereinafter, "action items") representing the partial actions of each body part constituting a predetermined action (for example, the action of the wrist, the action of the elbow, the action of the waist, etc.), which is represented by the main factor action data. Further, the main factor action information includes, for example, information representing the specific content of the main factor action item (for example, the specific numerical value of the rotation angle of the waist, etc.) (hereinafter, "action item content").

[0050] The support information providing unit 305 (an example of an output unit) generates (outputs) support information for improving the results of a predetermined action of the target person based on the main factor action data and the main factor action information output from the main factor action estimation unit 304, and provides it to the user through a display device 36 or the like.

[0051] The support information providing unit 305 outputs, for example, tool improvement support information for improving the results of a predetermined action of the target person. Specifically, tool improvement support information is associated in advance for each type of action item and action item content, and using the information representing this association relationship, the support information providing unit 305 may output tool improvement support information corresponding to the main factor action information. As a result, a store clerk can propose a tool suitable for the target person based on the tool improvement support information (for example, information specifying a specific product or information representing the functional characteristics of the tool). In addition, the target person can more easily select a tool that suits their own actions (movement characteristics).

[0052] In addition, the support information providing unit 305 may output, for example, reproducibility improvement support information for improving the reproducibility of the results of a predetermined action of the target person. Specifically, the support information providing unit 305 may output reproducibility improvement support information representing the average value of the main factor action data for a plurality of times or a specific value within the range of the main factor action data for a plurality of times. The specific value may be the value of the main factor action data (hereinafter, "appropriate value") from which the best result data can be obtained from the learned model when the main factor action data is changed within the range of the main factor action data for a plurality of times. As a result, for example, the target person can suppress the dispersion (variation) of the main factor action data and stabilize the result data by performing the improvement of the predetermined action while being conscious of matching the main factor action data to the average value or the appropriate value. In addition, the instructor can suppress the dispersion (variation) of the main factor action data of the student (target person) and stabilize the result data by guiding the main factor action data to match the average value or the appropriate value.

[0053] Further, the support information providing unit 305 may output optimization support information for optimizing, for example, the result of a predetermined operation of the target person. Specifically, the support information providing unit 305 may output optimization support information representing the value (optimal value) of the main factor operation data at which the predicted value of the result data output from the learned model when the main factor operation data is changed including outside the range of the main factor operation data for a plurality of times becomes optimal. Thereby, for example, the target person can improve a predetermined operation while being conscious of matching the main factor operation data to the optimal value. Further, the instructor can optimize the main factor operation data for a predetermined operation of the student (target person) by giving guidance so as to match the optimal value of the main factor operation data.

[0054] [Control Processing of Information Processing Apparatus] Next, with reference to FIG. 4, the control processing by the information processing apparatus 30 will be described.

[0055] FIG. 4 is a flowchart schematically showing an example of the control processing by the information processing apparatus 30. This flowchart is started, for example, when an input (hereinafter, “support function start input”) representing the start of the function of providing support information is received through the input device 37.

[0056] In step S102, the information processing apparatus 30 causes the display device 36 to display a screen (hereinafter, “selection screen”) for selecting a plurality of operation data and result data related to a predetermined operation for a predetermined number of times. On the selection screen, for example, a list of a plurality of combinations of operation data and result data that can be selected as a data set of combinations of a plurality of operation data and result data acquired by the operation data acquisition unit 301 and the result data acquisition unit 302 may be displayed. Thereby, the user can select a data set of a plurality of operation data and result data for a predetermined number of times a predetermined number of times using the input device 37. When the processing in step S102 is completed, the information processing apparatus 30 proceeds to step S104.

[0057] Further, the information processing apparatus 30 may cause the display device 36 to display a screen for requesting to newly acquire a data set of a plurality of operation data and result data for a predetermined number of times. Thereby, the information processing apparatus 30 can newly cause the subject person to perform a predetermined operation a predetermined number of times, and acquire the operation data and result data for the predetermined number of times.

[0058] In step S104, the information processing apparatus 30 determines whether or not the selection input of the data set of the combination of the plurality of operation data and the result data for the predetermined number of times is completed. If the selection input is not completed, the information processing apparatus 30 proceeds to step S106, and if the selection input is completed, the information processing apparatus 30 proceeds to step S108.

[0059] In step S106, the information processing apparatus 30 determines whether or not any of the conditions, that is, the reception of the cancellation input by the input device 37 and the elapse of a certain time from the start of the display of the selection screen, is satisfied. The cancellation input is an input for requesting the cancellation of the display of the selection screen. If any of the conditions is satisfied, the information processing apparatus 30 cancels the display of the selection screen and ends the processing of the present flowchart. If none of the conditions is satisfied, the information processing apparatus 30 returns to step S104.

[0060] In step S108, the analysis unit 303 analyzes the relationship between the plurality of operation data and the result data based on the data set of the combination of the plurality of operation data and the result data for the predetermined number of times. For example, the analysis unit 303 may perform machine learning based on the data set of the combination of the plurality of operation data and the result data for the predetermined number of times, and output a learned model (regression model) as an analysis result. When the processing of step S108 is completed, the information processing apparatus 30 proceeds to step S110.

[0061] In step S110, based on the analysis result (for example, the learned model) output in step S108, the main factor operation estimation unit 304 estimates and outputs the main factor operation data and the main factor operation information as described above. When the processing of step S110 is completed, the information processing apparatus 30 proceeds to step S112.

[0062] In step S112, the support information providing unit 305 causes the display device 36 to display support information for improving the result of a predetermined operation of the target person based on the estimation result (main factor operation data or main factor operation information) in step S112. Thereby, the support information providing unit 305 can present (provide) the support information to the target person.

[0063] In this way, in this example, the information processing device 30 can perform a series of processes through newly acquiring a data set by selection input or a combination of a plurality of pieces of operation data and result data for a plurality of times, and provide the user with support information for improving a predetermined operation of the target person.

[0064] [Specific application examples of the information providing system] Next, specific application examples of the information providing system 1 according to the present embodiment will be described.

[0065] <The first application example of the information providing system> First, the first application example of the information providing system 1 according to the present embodiment will be described.

[0066] In this example, the information providing system 1 provides the user with support information regarding improvement of a golf swing operation. The user is, for example, a target person who performs a swing operation, or an instructor who instructs the target person.

[0067] The motion data acquisition device 10 acquires a plurality of motion data (hereinafter referred to as "golf swing data") related to the golf swing motion of the subject. In this example, the plurality of golf swing data are data (hereinafter referred to as "energy data") related to the energy (such as kinetic energy or potential energy, etc.) that contributes to the head speed of each of the plurality of body parts of the subject. The motion data acquisition device 10 includes, for example, inertial sensors attached to a plurality of body parts of the subject. Also, the motion data acquisition device 10 may include, for example, an imaging device capable of imaging a moving image of the motion of a plurality of body parts of the subject. Further, the motion data acquisition device 10 includes, for example, a floor reaction force meter that outputs data related to the floor reaction force acting on the subject. The motion data acquisition device 10 can acquire (calculate) data related to the energy for each of the plurality of body parts based on the output of the inertial sensor or the imaging device and the output of the floor reaction force meter.

[0068] The result data acquisition device 20 acquires result data related to the golf swing motion of the subject. In this example, the result data is data related to the head speed in the subject's swing motion. The result data acquisition device 20 includes, for example, a distance sensor that acquires (outputs) data related to the distance from the golf club. Also, the result data acquisition device 20 may include an imaging device capable of imaging a moving image of the golf club. The result data acquisition device 20 can acquire (calculate) the head speed based on the output of the distance sensor and the output (moving image) of the imaging device.

[0069] The analysis unit 303 performs machine learning based on a data set of combinations of energy data and data related to head speed for each of the plurality of body parts for a plurality of times. Then, the analysis unit 303 generates a learned model (regression model) that estimates the head speed (related data) from the energy data for each of the plurality of body parts of the subject.

[0070] The main factor motion estimation unit 304 estimates that among the weighting coefficients for the energy data of a plurality of body parts in the generated regression model, the energy data of the body part with the largest weighting coefficient has the highest influence on the head speed (data related thereto). That is, the main factor motion estimation unit 304 estimates that the motion of the body part corresponding to the energy data with the largest weighting coefficient has the greatest influence on the head speed (data related thereto).

[0071] The support information providing unit 305 provides the user with support information (reproducibility improvement support information) representing the average value or appropriate value of the energy data of the estimated body part for a plurality of times through the display device 36 or the like. The appropriate value is the value of the energy data from which the best (fastest) head speed can be obtained from the learned data when changing the energy data of the estimated body part within the range (width) of the energy data for a plurality of times. Thereby, the subject (student) performing the swing motion can improve the swing motion while being conscious of adjusting the energy data of the estimated body part to the average value or the appropriate value. Therefore, the dispersion (variation) of the energy data (motion) of the body part can be suppressed, and the head speed can be stabilized. In addition, the subject can improve the swing motion in a form that can obtain the best result (head speed) within the range of variation of the energy data of the estimated body part based on the support information regarding the appropriate value of the energy data of the estimated body part. In addition, the instructor can suppress the dispersion (variation) of the energy data (motion) of the body part of the student (subject) and stabilize the head speed by guiding the student to adjust the energy data of the estimated body part to the average value or the appropriate value. In addition, the instructor can guide the improvement of the swing motion in a manner that can achieve the best result (face angle) within the range of variation of the energy data of the estimated body part based on the support information regarding the appropriate value of the energy data of the estimated body part.

[0072] <Second application example of the information providing system> Next, a second application example of the information providing system 1 according to the present embodiment will be described.

[0073] In this example, the information providing system 1 provides the user with support information regarding improvement of the golf swing motion. The user is, for example, a person who performs the swing motion or an instructor who instructs the person.

[0074] The motion data acquisition device 10 acquires a plurality of golf swing data regarding the golf swing motion of the person. In this example, the plurality of golf swing data includes data regarding the change in the angle around the axis of the shaft of the golf club, data regarding the angle between the club and the ground, and data regarding the face rotation. The face rotation represents the opening and closing state of the face during the swing motion, for example, the rotational angular velocity of the face around the shaft axis. Also, in this example, a plurality of golf swing data at each timing of halfway down, top, and halfway back during the swing motion are acquired. The motion data acquisition device 10 includes, for example, one or a plurality of inertial sensors attached to the golf club (for example, the grip portion or the like). The motion data acquisition device 10 can acquire (calculate) data regarding the change in the angle around the axis of the shaft of the club, data regarding the angle between the club and the ground, data regarding the face rotation, and the like based on the output of the inertial sensor provided on the club.

[0075] The result data acquisition device 20 acquires result data regarding the golf swing motion of the person. In this example, the result data is data regarding the face angle (hereinafter, "face angle data"). The face angle represents the orientation of the face surface in the horizontal direction at the time of impact with the golf ball. The result data acquisition device 20 includes, for example, one or a plurality of inertial sensors attached to the golf club. The result data acquisition device 20 can acquire the face angle data based on the output of the inertial sensor attached to the club.

[0076] When the clubhead is halfway down, at the top, and halfway back, the analysis unit 303 performs machine learning based on data sets that are combinations of multiple sets of golf swing data and result data (face angle data) for multiple swings. Then, the analysis unit 303 generates a plurality (three) of learned models that estimate the face angle (data) from the respective multiple sets of golf swing data when the clubhead is halfway down, at the top, and halfway back. The analysis unit 303 outputs the learned model with the highest accuracy (best) among the three learned models to the main factor motion estimation unit 304.

[0077] In the generated learned model, the main factor motion estimation unit 304 estimates that the golf swing data with the largest change amount of the face angle when the multiple sets of golf swing data are each changed by a predetermined amount has the highest influence degree on the face angle. The predetermined amount may be, for example, 1 degree. Further, the predetermined amount may be, for example, an amount (angle) corresponding to the standard deviation of the result data for multiple swings.

[0078] The support information providing unit 305 provides the user with support information (reproducibility improvement support information) representing the average value or appropriate value of multiple sets of golf swing data (hereinafter referred to as "main factor golf swing data") with the highest degree of influence on the face angle through the display device 36 or the like. The appropriate value is the value of the main factor golf swing data at which the best face angle data (for example, a value closest to 0 degrees) can be obtained from the learned data when the main factor golf swing data is changed within the range (width) of the main factor golf swing data for multiple sets. Thereby, the subject (student) performing the swing operation can improve the swing operation by consciously adjusting the main factor golf swing data to the average value or the appropriate value. Therefore, the dispersion (variation) of the main factor golf swing data (operation) can be suppressed, and the face angle can be stabilized. Also, the subject can improve the swing operation in a form that can obtain the best result (face angle) within the range of variation of their own main factor golf swing data based on the support information regarding the appropriate value of the main factor golf swing data. In addition, the instructor can suppress the dispersion (variation) of the main factor golf swing data (operation) of the student (subject) and stabilize the face angle by guiding the student to adjust a plurality of golf swing data to the average value or the appropriate value. Further, the instructor can guide the improvement of the swing operation in a manner that can achieve the best result (face angle) within the range of variation of the main factor golf swing data of the student based on the support information regarding the appropriate value of the main factor golf swing data.

[0079] <Third Application Example of the Information Providing System> Next, a third application example of the information providing system 1 according to the present embodiment will be described.

[0080] In this example, the information providing system 1 provides the user with support information regarding the club recommended in accordance with the golf swing operation of the subject. The user is, for example, the subject performing the swing operation, or a store clerk in a store that serves the subject.

[0081] The motion data acquisition device 10 acquires a plurality of golf swing data of a target person. In this example, the plurality of golf swing data are data related to face rotation, release timing, and the angle of the swing plane. The release timing represents the timing at which the cocked wrist returns to its original state (is released) during the downswing. The swing plane represents a virtual plane corresponding to the trajectory of the club (head). The motion data acquisition device 10 includes, for example, one or more inertial sensors attached to a golf club. The motion data acquisition device 10 can acquire data related to face rotation, release timing, and the angle of the swing plane respectively based on the output of the inertial sensor attached to the club.

[0082] The result data acquisition device 20 acquires result data related to the golf swing motion of the target person. In this example, the result data are data related to the attack angle and the club path. The attack angle represents the incident angle of the club (head) with respect to the golf ball based on the horizontal plane at the time of impact with the golf ball. The club path represents the trajectory (the direction of the head) of the club (head) in the horizontal direction from immediately before to immediately after the impact with the golf ball during the swing. The result data acquisition device 20 includes, for example, one or more inertial sensors attached to a golf club. The result data acquisition device 20 can acquire data related to the attack angle and the club path respectively based on the output of the inertial sensor attached to the club.

[0083] The analysis unit 303 performs machine learning based on a data set formed by a combination of a plurality of golf swing data and result data (data related to the attack angle and the club path) for a plurality of times. Then, the analysis unit 303 generates a learned model (regression model) that estimates data related to the attack angle and the club path respectively from the plurality of golf swing data.

[0084] For each of the angle of attack and the club path, the main factor motion estimation unit 304 estimates that the golf swing data with the largest weighting coefficient among the weighting coefficients for each of the plurality of golf swing data of the generated regression model has the highest influence on the result.

[0085] The support information providing unit 305 provides the user with support information (equipment improvement support information) regarding the club pre-associated with the main factor golf swing data through the display device 36 or the like. Thereby, the store clerk in the store can propose a club suitable for the target person based on the equipment improvement support information (for example, information specifying a specific product, information representing the functional characteristics of the equipment, etc.). In addition, the target person can more easily select a club that suits his / her own motion (motion characteristics).

[0086] <Fourth application example of the information providing system> Next, a fourth application example of the information providing system 1 according to the present embodiment will be described.

[0087] In this example, the information providing system 1 provides the user with support information regarding the club recommended according to the golf swing motion of the target person. The user is, for example, the target person who performs the swing motion, or the store clerk in the store who serves the target person.

[0088] The motion data acquisition device 10 acquires a plurality of golf swing data of the target person. In this example, the plurality of golf swing data is energy data that contributes to the head speed of each of the plurality of body parts of the target person. The motion data acquisition device 10 includes, for example, inertial sensors attached to a plurality of body parts of the target person. In addition, the motion data acquisition device 10 may include, for example, an imaging device capable of imaging a moving image of the motion of a plurality of body parts of the target person. Further, the motion data acquisition device 10 includes, for example, a floor reaction force meter that outputs data regarding the floor reaction force acting on the target person. The motion data acquisition device 10 can acquire data regarding the energy for each of the plurality of body parts based on the output of the inertial sensor or the imaging device and the output of the floor reaction force meter.

[0089] The result data acquisition device 20 acquires result data related to the golf swing motion of the subject. In this example, the result data is data related to the attack angle and data related to the club path. The result data acquisition device 20 includes, for example, one or more inertial sensors attached to the golf club. The result data acquisition device 20 can acquire data related to each of the attack angle and the club path based on the output of the inertial sensor attached to the club.

[0090] The analysis unit 303 performs machine learning based on a data set formed by a combination of energy data and result data (data related to the attack angle and the club path) for each of a plurality of body parts for a plurality of times. Then, the analysis unit 303 generates a learned model (regression model) that estimates data related to each of the attack angle and the club path from the energy data for each of the plurality of body parts.

[0091] For each of the attack angle and the club path, the main factor motion estimation unit 304 estimates that the energy data of the body part with the largest weighting coefficient among the weighting coefficients of the energy data for each of the plurality of body parts of the generated regression model has the highest influence on the result. That is, the main factor motion estimation unit 304 estimates that the motion of the body part corresponding to the energy data with the largest weighting coefficient has the greatest influence on the result (attack angle or club path).

[0092] The support information providing unit 305 provides the user with support information related to the club (tool improvement support information) pre-associated with the main factor golf swing data through the display device 36 or the like. Thereby, the store clerk in the store can propose a club suitable for the subject based on the tool improvement support information (for example, information specifying a specific product, information representing the functional characteristics of the tool, etc.). In addition, the subject can more easily select a club suitable for his / her own motion (motion characteristics).

[0093] <Fifth application example of the information providing system> Next, a fifth application example of the information providing system 1 according to the present embodiment will be described.

[0094] In this example, the information providing system 1 provides the user with support information regarding a golf ball recommended in accordance with the swing motion of the target person. The user is, for example, the target person performing the swing motion, or a store clerk in a store serving the target person.

[0095] The motion data acquisition device 10 acquires a plurality of golf swing data of the target person. In this example, the plurality of golf swing data are data regarding the attack angle, data regarding the dynamic loft, and data regarding the head speed. The dynamic loft represents the inclination angle of the face at the impact moment when actually hitting. The motion data acquisition device 10 includes, for example, one or more inertial sensors attached to the club. The motion data acquisition device 10 includes, for example, an imaging device capable of imaging a moving image of the club. Also, the motion data acquisition device 10 includes, for example, a distance sensor that acquires (outputs) data regarding the distance to the club. The motion data acquisition device 10 can acquire data regarding each of the attack angle, the dynamic loft, and the head speed based on the outputs of the inertial sensor, the imaging device, the distance sensor, and the like.

[0096] The result data acquisition device 20 acquires result data regarding the golf swing motion. In this example, the result data is data regarding the flight distance of the golf ball hit by the club. The result data acquisition device 20 includes, for example, an orbit measurement device that acquires (outputs) data regarding the orbit of the golf ball. Also, the result data acquisition device 20 includes, for example, a GPS sensor attached to the golf ball. Also, the result data acquisition device 20 includes, for example, an imaging device capable of imaging a moving image of the golf ball. The result data acquisition device 20 can acquire data regarding the flight distance of the golf ball based on the outputs of the orbit measurement device, the GPS sensor, the imaging device, and the like.

[0097] The analysis unit 303 performs machine learning based on a dataset of a combination of a plurality of pieces of golf swing data for a plurality of times and data related to the flight distance. Then, the analysis unit 303 generates a learned model (regression model) that estimates the flight distance (data related thereto) of a golf ball from the plurality of pieces of golf swing data.

[0098] The main factor motion estimation unit 304 estimates that the golf swing data with the largest weighting coefficient among the weighting coefficients for each of the plurality of pieces of golf swing data of the generated regression model has the highest influence on the flight distance (data related thereto).

[0099] The support information providing unit 305 provides the user with support information (equipment improvement support information) related to the golf ball that is pre-associated with the main factor golf swing data through the display device 36 or the like. Thereby, a store clerk can propose a golf ball suitable for the target person based on the equipment improvement support information (for example, information specifying a specific product, information representing the functional characteristics of the golf ball, etc.). In addition, the target person can more easily select a golf ball that suits his or her own motion (kinematic characteristics).

[0100] <Sixth application example of the information providing system> Next, a sixth application example of the information providing system 1 according to the present embodiment will be described.

[0101] In this example, the information providing system 1 provides the user with support information related to the improvement of the tennis swing motion. The user is, for example, a person who performs the swing motion or an instructor who instructs the person.

[0102] The motion data acquisition device 10 acquires a plurality of motion data (hereinafter, "tennis swing data") regarding the tennis swing motion of the subject. In this example, the plurality of tennis swing data are data regarding swing speed, data regarding swing angle, data regarding the angle of the racket face at impact, and data regarding the rotational angle of the racket. The motion data acquisition device 10 includes, for example, one or more inertial sensors attached to the racket. Further, the motion data acquisition device 10 includes, for example, an imaging device that captures a moving image of the movement of the racket. The motion data acquisition device 10 can acquire data regarding each of swing speed, swing angle, and the angle of the racket face at impact based on the outputs of, for example, inertial sensors and imaging devices.

[0103] The result data acquisition device 20 acquires result data regarding the tennis swing motion of the subject. In this example, the result data is data regarding the distance from the position of the subject to the landing position of the tennis ball (hereinafter, "landing distance"). The result data acquisition device 20 includes, for example, an orbit measurement device that outputs data regarding the orbit of the tennis ball. Further, the result data acquisition device 20 includes, for example, an imaging device that captures a moving image of the orbit of the tennis ball. The result data acquisition device 20 can acquire data regarding the landing distance based on the outputs of the orbit measurement device, imaging device, etc.

[0104] The analysis unit 303 performs machine learning based on a data set of combinations of a plurality of tennis swing data for a plurality of times and data regarding the landing distance. Then, the analysis unit 303 generates a learned model (regression model) that estimates the landing distance (data regarding) from the plurality of tennis swing data.

[0105] The main factor motion estimation unit 304 estimates that the tennis swing data with the largest weighting coefficient among the weighting coefficients for each of the plurality of tennis swing data of the generated regression model has the highest influence on the landing distance (data regarding).

[0106] The support information providing unit 305 provides the user with support information (reproducibility improvement support information) representing the average value and appropriate value of multiple sets of tennis swing data (hereinafter referred to as "main factor tennis swing data") with the highest degree of influence on the landing distance (data related thereto) through the display device 36 or the like. The appropriate value is the value of the main factor tennis swing data when the main factor tennis swing data is changed within the range (width) of multiple sets of main factor tennis swing data, and the best landing distance (for example, the value closest to 24 m corresponding to the length of the court) can be obtained from the learned data. As a result, the subject (student) performing the swing operation can improve the swing operation by being conscious of adjusting the main factor tennis swing data to the average value or the appropriate value. Therefore, the dispersion (variation) of the main factor tennis swing data (operation) can be suppressed, and the landing distance can be stabilized. In addition, the subject can improve the swing operation in a form that can obtain the best result (landing distance) within the range of variation of their own main factor tennis swing data based on the support information regarding the appropriate value of the main factor tennis swing data. In addition, the instructor can suppress the dispersion (variation) of the main factor tennis swing data (operation) of the student (subject) and stabilize the landing distance by guiding the main factor tennis swing data to match the average value or the appropriate value. In addition, the instructor can guide the improvement of the swing operation in a manner that can achieve the best result (landing distance) within the range of variation of the main factor tennis swing data of the student based on the support information regarding the appropriate value of the main factor tennis swing data.

[0107] As described in detail above with respect to the embodiments, the present disclosure is not limited to such specific embodiments, and various modifications and improvements are possible within the scope of the gist described in the claims.

Explanation of Reference Numerals

[0108] 1 Information providing system 10 Motion data acquisition device 20 Result data acquisition device 30 Information processing device 36 Display device 301 Action data acquisition unit (first acquisition unit) 302 Result data acquisition unit (second acquisition unit) 303 Analysis unit 304 Major cause action estimation unit (estimation unit) 305 Support information providing unit (output unit)

Claims

A first acquisition unit that acquires a plurality of first data regarding a predetermined operation performed by a target person; A second acquisition unit that acquires second data regarding a result obtained based on the predetermined operation performed by the target person; Based on the plurality of first data and the second data regarding the plurality of times of the predetermined operation performed by the target person, among the plurality of first data regarding the predetermined operation performed by the target person, an estimation unit that estimates first data having a relatively high degree of influence on the result obtained based on the predetermined operation performed by the target person; An output unit that outputs support information for improving the result obtained based on the predetermined operation performed by the target person based on the estimation result of the estimation unit, and includes: The plurality of first data includes data regarding the operation of a predetermined body part of the target person in the predetermined operation; The output unit outputs the support information for optimizing the result obtained based on the predetermined operation performed by the target person, and represents the optimal value of the first data having a relatively high degree of influence on the result obtained based on the predetermined operation performed by the target person among the plurality of first data estimated by the estimation unit; An information processing apparatus.

2. Based on the plurality of first data and the second data regarding the plurality of times of the predetermined operation, an analysis unit that analyzes the relationship between the plurality of first data and the second data regarding the predetermined operation performed by the target person is provided; Based on the analysis result of the analysis unit, the estimation unit estimates first data having a relatively high degree of influence on the result obtained based on the predetermined operation performed by the target person among the plurality of first data regarding the predetermined operation performed by the target person; The information processing apparatus according to claim 1.

3. Based on the plurality of first data and the second data regarding the plurality of times of the predetermined operation, the analysis unit performs machine learning; Based on the learning result by the machine learning, the estimation unit estimates first data having a relatively high degree of influence on the result obtained based on the predetermined operation performed by the target person among the plurality of first data regarding the predetermined operation performed by the target person; The information processing apparatus according to claim 2.

4. The analysis unit generates, as the learning result, a function representing the relationship between the plurality of first data and the second data regarding the predetermined operation performed by the subject. The estimation unit estimates, among the plurality of first data regarding the predetermined operation performed by the subject, first data having a relatively high influence degree on the result obtainable based on the predetermined operation performed by the subject, based on the weighting of each of the plurality of first data defined in the function. The information processing apparatus according to claim 3.

5. The estimation unit estimates, among the plurality of first data regarding the predetermined operation performed by the subject, first data having a relatively high influence degree on the result obtainable based on the predetermined operation performed by the subject, based on the rate of change of the estimated value of the second data output from the learning result when each of the plurality of first data is changed. The information processing apparatus according to claim 3.

6. The output unit outputs the support information for suppressing the dispersion of the result obtainable based on the predetermined operation performed by the subject. The information processing apparatus according to any one of claims 1 to 5.

7. The output unit outputs the support information regarding the tool for improving the result obtainable based on the predetermined operation performed by the subject. The information processing apparatus according to any one of claims 1 to 6.

8. The predetermined operation is a golf swing operation. The information processing apparatus according to any one of claims 1 to 7.

9. The plurality of first data are obtained by at least one of an inertial sensor attached to at least one of a club and a person performing a swing operation, an imaging device that images at least one of a person's swing operation and the trajectory of a ball, a distance sensor that outputs data regarding the distance between at least one of a body part of a person performing a swing operation and the ball, a trajectory measuring device that outputs data regarding the trajectory of the ball, a surface pressure measuring device that outputs data regarding the surface pressure of a person's sole, and a floor reaction force measuring device that outputs data regarding the floor reaction force acting on a person performing a swing operation. The information processing apparatus according to claim 8.

10. The plurality of first data includes data related to at least one of the position, velocity, acceleration, angular acceleration, energy, torque, sole surface pressure of a body part of a person performing a swing motion, the floor reaction force acting on the person performing the swing motion, the position, acceleration, angular velocity, angular acceleration of a predetermined part of a club, the trajectory of a ball, and the captured images of at least one of the person performing the swing motion and the ball. The information processing apparatus according to claim 8 or 9.

11. An information processing method executed by an information processing apparatus, a first acquisition step of acquiring a plurality of first data related to a predetermined motion executed by a subject; a second acquisition step of acquiring second data related to a result obtained based on the predetermined motion executed by the subject; an estimation step of estimating first data having a relatively high influence degree on a result obtained based on the predetermined motion executed by the subject among the plurality of first data related to the plurality of times of the predetermined motion executed by the subject, based on the plurality of first data and the second data; an output step of outputting support information for improving a result obtained based on the predetermined motion executed by the subject, based on an estimation result in the estimation step, the method including: the plurality of first data includes data related to the motion of a predetermined body part of the subject in the predetermined motion; in the output step, the support information for optimizing a result obtained based on the predetermined motion executed by the subject, which represents an optimum value of the first data having a relatively high influence degree on a result obtained based on the predetermined motion executed by the subject among the plurality of first data estimated in the estimation step, is output; An information processing method.

12. In an information processing apparatus, a first acquisition step of acquiring a plurality of first data related to a predetermined motion executed by a subject; a second acquisition step of acquiring second data related to a result obtained based on the predetermined motion executed by the subject; An estimation step of estimating first data among the plurality of first data regarding the plurality of predetermined operations executed by the subject, which has a relatively high degree of influence on a result obtainable based on the predetermined operation executed by the subject, based on the plurality of first data and the second data; An output step of outputting support information for improving a result obtainable based on the predetermined operation executed by the subject, based on the estimation result in the estimation step; are executed. The plurality of first data includes data regarding the movement of a predetermined body part of the subject in the predetermined operation. In the output step, the support information for optimizing the result obtainable based on the predetermined operation executed by the subject, which represents an optimal value of the first data estimated in the estimation step and having a relatively high degree of influence on the result obtainable based on the predetermined operation executed by the subject among the plurality of first data, is output. Program.

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