Motion analysis system, motion analysis method, and program

Abstract

To provide a user with a method for training a specific muscle.SOLUTION: A bodily movement analysis system includes a muscle moving part increasing a muscle output of only a muscle that a user wants to move so as to move only the muscle on a human body model of a finite element simulator, a position information calculation part for calculating, as time-series position information, a trajectory of movement of each joint when the muscle is moved by the muscle moving part on the finite element simulator, and a movement providing part for providing the user's movement of reproducing the time-series trajectory of each joint based on the position information calculated by the position information calculation part.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to a motion analysis system, a motion analysis method, and a program for analyzing human motion.

Background Art

[0002] There is known a muscle state estimation device that constructs an initial user model by reflecting a user's parameters on a general human body model based on skeleton data and muscle data (see, for example, Patent Document 1).

Prior Art Literature

Patent Literature

[0003]

Patent Document 1

Summary of Invention

Problem to be Solved by the Invention

[0004] However, the above-described muscle state estimation device only constructs an initial user model, and although devices using machine learning or the like are also conceivable, none of them provide a user with a method for training a specific muscle.

[0005] The present disclosure has been made to solve such problems, and a main object thereof is to provide a motion analysis system, a motion analysis method, and a program that provide a user with a method for training a specific muscle.

Means for Solving the Problem

[0006] One aspect of the present disclosure for achieving the above object is,[} a muscle motion unit that, on a human body model of a finite element simulator, increases muscle output only of a muscle that a user desires to move and causes only said muscle to perform motion; A position information calculation unit calculates the trajectory of each joint as time-series position information when the muscle is moved by the muscle movement unit on the finite element simulator, Based on the position information calculated by the position information calculation unit, the motion provision unit provides user actions that reproduce the time-series trajectory of each joint, A motion analysis system equipped with That is the case. In one embodiment, the motion provisioning unit may have a display unit that displays to the user the user's actions that reproduce the time-series trajectory of each joint. In one embodiment, the motion provider may include an orthotic device or teaching robot that assists the user's movements in performing actions that reproduce the time-series trajectories of each joint. On this flight, The aforementioned finite element simulator is The target angle input unit includes a target angle input unit into which the target angle of each joint to be moved in the human body model is input, A deviation calculation unit calculates the deviation between the target angle from the target angle input unit and the joint angle from the angle calculation unit. A PID muscle control unit performs PID control based on the deviation from the aforementioned deviation calculation unit and calculates the amount of manipulation for each muscle used for posture control. A muscle activity calculation unit calculates the muscle activity level of each muscle based on the amount of manipulation performed on each muscle from the PID muscle control unit, An angle calculation unit calculates the joint angles of each joint of the human body model based on the coordinates of the nodes fed back from the human body model of the muscle solid model, A muscle controller unit having, A muscle solid model unit having the aforementioned human body model and a model analysis unit that performs finite element analysis on the human body model based on the muscle activity level of each muscle calculated by the muscle activity level calculation unit, and operates each muscle of the human body model based on the analysis results of the finite element analysis, It may also be equipped with. One aspect of this disclosure for achieving the above objectives is: The process involves increasing the muscle output of only the muscles that the user wants to move on a human body model in a finite element simulator, thereby activating only those muscles. The steps include: calculating the trajectory of each joint as time-series positional information when the muscle is activated on the finite element simulator; The steps include providing a user action that reproduces the time-series trajectory of each joint based on the position information, Motion analysis method including That is the case. One aspect of this disclosure for achieving the above objectives is: On a human body model in a finite element simulator, the process involves increasing the muscle output of only the muscles that the user wants to move, thereby activating only those muscles. The process involves calculating the trajectory of each joint as time-series positional information when the muscle is activated on the aforementioned finite element simulator, A process that provides user actions that reproduce the time-series trajectory of each joint based on the position information, A program that causes a computer to execute That is the case. [Effects of the Invention]

[0007] According to this disclosure, it is possible to provide a motion analysis system, a motion analysis method, and a program that provide users with a method for training specific muscles. [Brief explanation of the drawing]

[0008] [Figure 1] This block diagram shows a schematic system configuration of the motion analysis system according to this embodiment. [Figure 2] This block diagram shows a schematic system configuration of the finite element simulator according to this embodiment. [Figure 3] This is a flowchart showing the flow of the motion analysis method according to this embodiment. [Figure 4] This figure shows the time change in the hip joint angle when only the iliopsoas muscle of a seated human body model is contracted on a finite element simulator. MODE FOR CARRYING OUT THE INVENTION

[0009] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Fig. 1 is a block diagram showing a schematic system configuration of a motion analysis system according to the present embodiment. The motion analysis system 1 according to the present embodiment presents a method for training specific muscles to a user.

[0010] The motion analysis system 1 according to the present embodiment includes a finite element simulator 2, a muscle motion unit 3, a position information calculation unit 4, and a motion providing unit 5.

[0011] The motion analysis system 1 has the hardware configuration of a standard computer including, for example, a processor such as a CPU (Central Processing Unit) or GPU (Graphics Processing Unit), an internal memory such as a RAM (Random Access Memory) or ROM (Read Only Memory), a storage device such as an HDD (Hard Disk Drive) or SSD (Solid State Drive), an input / output I / F for connecting peripheral devices such as a display, and a communication I / F for communicating with devices external to the apparatus.

[0012] The finite element simulator 2 according to the present embodiment is configured to actively move a human body model. Specifically, the finite element simulator 2 according to the present embodiment actively moves the human body model by including a muscle controller described later.

[0013] Conventional human body models are disclosed in, for example, Japanese Patent No. 3760793.

[0014] Fig. 2 is a block diagram showing a schematic system configuration of the finite element simulator according to the present embodiment. The finite element simulator 2 according to the present embodiment includes a muscle control unit 21 that controls muscles of the human body model 222, and a muscle solid model unit 22.

[0015] The muscle control unit 21 includes a target angle input unit 211, a deviation calculation unit 212, a PID muscle control unit 213, a muscle activity level calculation unit 214, and an angle calculation unit 215.

[0016] The target angle input unit 211 receives the time change of the target angle of each joint that you want to move in the human body model 222. The target angle input unit 211 may also receive the target angle of each joint corresponding to the movement of each joint as a time history.

[0017] For example, the target angle input unit 211 may receive input such as the knee joint being 180 degrees at 0 seconds, 90 degrees at 1 second, and so on. The input value may also be the time history of the angle change from the initial angle. The time history of the target angle is set according to, for example, the user's posture during training (angle changes of each joint). The target angle input unit 211 outputs the input target angle to the deviation calculation unit 212.

[0018] The deviation calculation unit 212 calculates the deviation between the target angle from the target angle input unit 211 and the joint angle from the angle calculation unit 215. The deviation calculation unit 212 outputs the calculated deviation to the PID muscle control unit 213.

[0019] The PID muscle control unit 213 performs PID (Proportional-Integral-Differential) control based on the deviation from the deviation calculation unit 212 and calculates the amount of manipulation for each muscle used for posture control. The PID muscle control unit 213 outputs the calculated amount of manipulation for each muscle to the muscle activity calculation unit 214.

[0020] The muscle activity calculation unit 214 calculates the muscle activity of each muscle based on the amount of manipulation performed on each muscle from the PID muscle control unit 213. The muscle activity calculation unit 214 outputs the calculated muscle activity to the model analysis unit 221 of the muscle solid model unit 22.

[0021] The angle calculation unit 215 calculates the joint angles of each joint of the human body model 222 based on the coordinates of the nodes fed back from the human body model 222 of the muscle solid model unit 22, as described later. The angle calculation unit 215 outputs the calculated joint angles of each joint to the deviation calculation unit 212.

[0022] The muscle solid model unit 22 includes a model analysis unit 221 and a human body model 222.

[0023] The model analysis unit 221 performs finite element analysis on the human body model 222 based on the muscle activity level of each muscle calculated by the muscle activity level calculation unit 214. Based on the results of the finite element analysis, the model analysis unit 221 activates each muscle of the human body model 222. As described above, the human body model 222 outputs the coordinates of the nodes resulting from its operation to the angle calculation unit 215 of the muscle control unit 21.

[0024] The coordinates of the nodes are, for example, the three points at the bottom, top, and front of each part of the human body model 222, such as the head, chest, and pelvis. The specific node locations are shown below in the order of bottom, top, and front.

[0025] ·Head: Center of gravity, top of head, between eyebrows ·Thorax: 12th thoracic vertebra, 1st thoracic vertebra, manubrium of the sternum • Pelvic region: tip of the coccyx, base of the sacrum, sacral promontory ·Femoral region: Femoral intercondylar fossa, femoral head center, femoral patellar surface ·Lower leg: tibia talocrural glenoid fossa, tibia intercondylar eminence, tibial tuberosity • Foot: Calcaneal tuberosity, medial process, talar trochlea, tip of the first toe • Scapular region: inferior angle of the scapula, superior angle of the scapula, anterior part of the superior angle of the scapula • Humerus: Trochlea of ​​the humerus, center of the humeral head, lesser tubercle of the humerus • Hand: Scaphoid bone, dorsal distal, scaphoid bone, dorsal proximal, scaphoid bone, palmar distal

[0026] Incidentally, while human joints such as the knee move with bones sliding against bone, conventional human body models consist of single-joint joints to reduce computational load. Furthermore, they only represent muscles and do not reproduce ligaments. As a result, the positional trajectories of the hands and feet in conventional human body models can be completely different from those of actual humans.

[0027] Furthermore, when a person's joints move, muscles contract and their cross-sectional area changes amidst friction between tissues such as muscles and ligaments. On the other hand, conventional human body models reproduce the attachment points of muscles, but only the shortening of multiple muscles within the tissue does not change the muscle cross-sectional area, nor does friction between tissues occur. For this reason, conventional human body models cannot accurately estimate the muscle contraction force when a person moves their joints.

[0028] In contrast, the human body model 222 according to this embodiment has a skeletal structure similar to that of a human, with muscles and ligaments attached to the skeletal structure. Tissue strain and stress distribution can be visualized. Contact between muscles can also be reproduced. Furthermore, the human body model 222 is configured such that the change in the cross-sectional area of ​​the muscle when the muscle contracts is reproduced, and the friction between the muscle, skin, and ligament tissues during that change is reflected.

[0029] The muscle action unit 3 increases the muscle output of only the muscles that the user wants to move (hereinafter referred to as target muscles) on the human body model 222 of the finite element simulator 2 described above, thereby activating only the target muscles. Alternatively, the muscle action unit 3 may also contract only the target muscles on the human body model 222 of the finite element simulator 2.

[0030] Information about the target muscles (such as the psoas major and iliacus muscles) is set in the muscle action unit 3, for example, via an input device.

[0031] For example, the muscle action unit 3 increases the muscle output of only the target muscle and activates only the target muscle by inputting a constant 100% muscle activity level to the target muscle and a constant 0% muscle activity level to the other muscles of the human body model 222 of the finite element simulator 2.

[0032] The position information calculation unit 4 calculates the trajectory of each joint as time-series position information when the target muscle is activated on the finite element simulator 2. The position information calculation unit 4 may also calculate the trajectory of each joint, hand, and foot as time-series position information when the target muscle is activated. The position information calculation unit 4 outputs the calculated position information to the motion provision unit 5.

[0033] The motion provision unit 5 provides user actions that reproduce the time-series trajectory of each joint based on the position information from the position information calculation unit 4.

[0034] The motion provisioning unit 5 may have a display unit 51 that displays to the user the user's movements, which reproduce the time-series trajectory of each joint. The display unit 51 displays, for example, the trajectory of joints, fingertips, toes, etc. By moving while looking at the trajectory of joints, fingertips, toes, etc. displayed on the display unit 51, the user can perform training by moving only the target muscles.

[0035] Furthermore, the motion provisioning unit 5 may have an orthotic device 52 or a teaching robot 53 that assists the user's movements to reproduce the time-series trajectory of each joint. The orthotic device 52 is worn by the user and is configured to forcibly perform the movement of that trajectory.

[0036] Furthermore, the user wears the teaching robot 53, and the teaching robot 53 performs the movement along its trajectory, causing the user to follow that movement. As a result, the user performs movements that reproduce the time-series trajectory of each joint, according to the orthosis 52 or the teaching robot 53.

[0037] Next, the flow of the motion analysis method according to this embodiment will be described in detail. Figure 3 is a flowchart of the flow of the motion analysis method according to this embodiment. First, a target muscle is set in the muscle action unit 3 (step S101).

[0038] The human body model 222 of the finite element simulator 2 operates according to the time change of the target angle of each joint or the muscle activity of the target muscle, which is input to the target angle input unit 211. At this time, the muscle action unit 3 increases the muscle output of only the target muscle on the human body model 222 of the finite element simulator 2 to activate the target muscle (step S102).

[0039] The position information calculation unit 4 calculates the trajectory of each joint as time-series position information when the target muscle is activated on the finite element simulator 2 (step S103).

[0040] The motion provision unit 5 provides the user's motion that reproduces the time-series trajectory of each joint based on the position information from the position information calculation unit 4 (step S104).

[0041] Next, we will explain the results of a simulation performed on the finite element simulator 2 in which the muscle output of only the iliopsoas muscles (psoas major and iliacus) of a seated human body model 222 was increased to contract only the iliopsoas muscles. Figure 4 shows the change in hip joint angle over time when only the iliopsoas muscles of a seated human body model 222 were contracted on the finite element simulator 2, as described above.

[0042] When the iliopsoas muscle of the human body model 222 is contracted on the finite element simulator 2, the hip joint angle in the flexion direction gradually increases, as does the hip joint angle in the adduction direction, as shown in Figure 4.

[0043] This shows that the hip joint flexes not just straight, but also bends inward. Therefore, if a user simply flexes the hip joint straight, other muscles will be engaged in the movement, not just the iliopsoas muscle.

[0044] According to the motion analysis system 1 of this embodiment, for example, if a deep muscle such as the iliopsoas muscle is set as the target muscle in the muscle action unit 3 as described above, the muscle action unit 3 increases the muscle output of only that deep muscle on the human body model 222 of the finite element simulator 2 to activate the deep muscle. The position information calculation unit 4 calculates the trajectory of each joint that moved when the deep muscle was activated on the finite element simulator 2 as time-series position information.

[0045] The motion provider unit 5 provides the user with movements that reproduce the time-series trajectory of each joint based on position information from the position information calculation unit 4. By simply following the movements provided by the motion provider unit 5, the user can efficiently train deep muscles, which are particularly difficult to train.

[0046] As described above, the motion analysis system 1 according to this embodiment includes a muscle action unit 3 that increases the muscle output of only the muscles that the user wants to move on a human body model 222 of a finite element simulator 2, thereby moving only those muscles; a position information calculation unit 4 that calculates the trajectory of each joint as time-series position information when the muscles are moved by the muscle action unit 3 on the finite element simulator 2; and a motion provision unit 5 that provides the user with movements that reproduce the time-series trajectory of each joint based on the position information calculated by the position information calculation unit 4. This makes it possible to provide the user with a method for training specific muscles.

[0047] While several embodiments of this disclosure have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These novel embodiments can be carried out in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims and their equivalents.

[0048] This disclosure can also be implemented, for example, by having a processor execute a computer program, as shown in Figure 3.

[0049] Programs can be stored and supplied to a computer using various types of non-transitory computer-readable media. Non-transitory computer-readable media include various types of tangible storage media. Examples of non-transitory computer-readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, CD-R / Ws, and semiconductor memory (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, RAMs (random access memory)).

[0050] Programs may be supplied to a computer by various types of transient computer-readable medium. Examples of transient computer-readable medium include electrical signals, optical signals, and electromagnetic waves. Transitory computer-readable medium can be supplied to a computer via wired communication channels such as electric wires and optical fibers, or via wireless communication channels.

[0051] Each component of the motion analysis system 1 according to the above-described embodiments can be implemented not only by program, but also partially or entirely by dedicated hardware such as an ASIC (Application Specific Integrated Circuit) or FPGA (Field-Programmable Gate Array). [Explanation of Symbols]

[0052] 1 Motion analysis system, 2 Finite element simulator, 3 Muscle motion unit, 4 Position information calculation unit, 5 Motion provision unit, 21 Muscle control unit, 22 Muscle solid model unit, 51 Display unit, 52 Orthotic device, 53 Teaching robot, 211 Target angle input unit, 212 Deviation calculation unit, 213 PID muscle control unit, 214 Muscle activity level calculation unit, 215 Angle calculation unit, 221 Model analysis unit, 222 Human body model

Claims

1. A muscle action unit that increases the muscle output of only the muscles that the user wants to move on a human body model in a finite element simulator, and activates only those muscles. A position information calculation unit calculates the trajectory of each joint as time-series position information when the muscle is moved by the muscle movement unit on the finite element simulator, Based on the position information calculated by the position information calculation unit, the motion provision unit provides user actions that reproduce the time-series trajectory of each joint, A motion analysis system equipped with the following features.

2. A motion analysis system according to claim 1, The motion provisioning unit is a motion analysis system having a display unit that displays to the user the user's movements that reproduce the time-series trajectory of each joint.

3. A motion analysis system according to claim 1, The motion provisioning unit is a motion analysis system having an orthotic device or teaching robot that assists the user's movements to reproduce the time-series trajectory of each joint.

4. The process involves increasing the muscle output of only the muscles that the user wants to move on a human body model in a finite element simulator, thereby activating only those muscles. The steps include: calculating the trajectory of each joint as time-series positional information when the muscle is activated on the finite element simulator; The steps include providing a user action that reproduces the time-series trajectory of each joint based on the position information, A motion analysis method, including the following.

5. On a human body model in a finite element simulator, the process involves increasing the muscle output of only the muscles that the user wants to move, thereby activating only those muscles. The process involves calculating the trajectory of each joint as time-series positional information when the muscle is activated on the aforementioned finite element simulator, A process that provides user actions that reproduce the time-series trajectory of each joint based on the position information, A program that causes a computer to execute something.

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