WO2010095636A1 - Méthode et dispositif d'évaluation d'une tension musculaire - Google Patents

Méthode et dispositif d'évaluation d'une tension musculaire Download PDF

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WO2010095636A1
WO2010095636A1 PCT/JP2010/052322 JP2010052322W WO2010095636A1 WO 2010095636 A1 WO2010095636 A1 WO 2010095636A1 JP 2010052322 W JP2010052322 W JP 2010052322W WO 2010095636 A1 WO2010095636 A1 WO 2010095636A1
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muscle
muscles
tension
group
activity
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PCT/JP2010/052322
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English (en)
Japanese (ja)
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仁彦 中村
克 山根
昭彦 村井
浩介 黒崎
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国立大学法人東京大学
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Priority to JP2011500620A priority Critical patent/JP5540386B2/ja
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/22—Ergometry; Measuring muscular strength or the force of a muscular blow
    • A61B5/224—Measuring muscular strength
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/389—Electromyography [EMG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/45—For evaluating or diagnosing the musculoskeletal system or teeth
    • A61B5/4519—Muscles
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/45—For evaluating or diagnosing the musculoskeletal system or teeth
    • A61B5/4523—Tendons
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/45—For evaluating or diagnosing the musculoskeletal system or teeth
    • A61B5/4528—Joints
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/45—For evaluating or diagnosing the musculoskeletal system or teeth
    • A61B5/4533—Ligaments

Definitions

  • the present invention relates to estimation of muscle tension and presentation of activity information inside the body based on the estimated muscle tension.
  • Non-patent document 1 Non-patent document 2
  • One solution is to model muscle contraction characteristics, such as the Hill-Stroeve muscle model (Non-patent document 1, Non-patent document 2), and calculate the parameters and muscle lengths obtained from physiology and experiments, and muscles calculated from the measured EMG.
  • a biomechanical approach to calculate muscle tension from the degree of activity can be mentioned. Since myoelectric potential, which is a parameter that can be measured relatively easily and best represents muscle tension, is used, it can be said that the estimated value is the most accurate. There is also an advantage that the calculation cost is small and the calculation can be performed at high speed.
  • it is necessary to measure EMG it is necessary to measure EMG, and it is necessary to attach electromyographs to all muscles that estimate muscle tension. Therefore, there is a limit to the number of muscles for which muscle tension is estimated from the limitation of the number of electromyographs. Even if countless electromyographs are available, it is impossible to attach them to all the muscles, and this restricts the behavior of the subject.
  • the optimization calculation at the time of muscle tension distribution involves calculations such as linear programming and quadratic programming, and there is a problem that the calculation cost is large and a lot of time is required.
  • More accurate calculation of muscle tension in the whole body by taking into account the error term with muscle tension obtained from the muscle activity measured with the Hill-Stroeve muscle model and electromyograph in the objective function in the optimization calculation (Patent Document 1, Non-Patent Document 3, Non-Patent Document 4)
  • the optimization calculation of muscle tension using inverse dynamics calculation is calculated when real-time estimation of muscle tension is considered. Cost becomes a problem.
  • the object of the present invention is to reduce the scale of the optimization calculation by reducing the variables in the optimization calculation for muscle tension estimation.
  • Another object of the present invention is to estimate the muscle tension during exercise in real time and to present the activity status inside the body acquired based on the muscle tension and / or muscle tension in real time.
  • the plurality of muscle groups M i at least one, one representative muscle and the representative muscle and bones origin stop electromyograph is mounted in one of said one or more sub-groups Is a first subgroup formed from muscles that are the same,
  • the muscle tension of the muscles belonging to the first subgroup is obtained from the myoelectric potential of the representative muscle measured during the exercise of the subject without using the optimization calculation, and is excluded from the optimization calculation target, thereby performing the optimization calculation.
  • the muscle activity representing each subgroup is estimated by the optimization calculation, thereby reducing variables in the optimization calculation. This is an estimation method of muscle tension.
  • the number n of the number of channels and muscle groups M i of electromyograph is not necessarily the same.
  • the muscle group in which the first group is formed typically one first group is formed per one muscle group, but two or more representative muscles in one muscle group. May be selected to form two or more first groups.
  • the muscle tension of the muscle belonging to the first subgroup is acquired from the myoelectric potential of the representative muscle measured during exercise of the subject, Optimizing muscle tension of muscles not belonging to the first subgroup so as to realize joint torque that cannot be realized by muscles belonging to the first subgroup in joint torque necessary to realize exercise of the subject; Estimated by
  • each muscle group M i the one or more subgroups are classified into the first subgroup and the muscles that do not belong to the first subgroup from the same muscle whose start and stop bones are the same.
  • the muscle activity representing each subgroup is estimated by optimization calculation.
  • the muscle activity obtained from the myoelectric potential should match the muscle activity calculated by the optimization calculation.
  • the measured muscle activity of the representative muscle is used as a reference value.
  • muscle grouping based on muscle movement directivity means, in other words, “muscle grouping related to each movement direction of each joint” or “based on the direction of torque that the muscle is involved in each joint. It can be called “grouping”. These represent the geometrical relationship between movement and muscle placement. Specifically, it means, for example, “muscle related to elbow joint extension” and “muscle related to hip joint flexion”. That is, the grouping of the muscle group M i is a classification according to the role of muscles involved in the direction of motion of each joint as such extend the elbow joint (extension) muscle for, bending the elbow (bend) muscle for .
  • the muscle groups M i of a joint contributes to a direction of bending the (contributing joints identical) muscle, a plurality of streaks of bones origin stop is different belongs, by bone to further origin stop this Classify into subgroups.
  • grouping of the muscle group M i is, the multi-joint muscle of influence ignored the movement directed by muscle classification, grouping of the sub-group is also considering the influence of the multi-joint muscle, to directly exercise when the muscle is contracted It can be said that the muscles of the affected joints are classified into the same group.
  • “Grouping based on alias muscle facilitation” represents muscles controlled by the same nerve bundle as a group.
  • the former is determined from the running of the muscle, and the latter is determined from the connection between the muscles by nerves. It has been shown that there is a relationship between these two in the field of sports science.
  • muscle grouping is “classified into cooperative muscles based on kinematics”.
  • the “cooperative muscle” can be defined as “a muscle that works to bend a certain joint in the same direction as the main muscle”.
  • Muscle directionality” and “cooperative muscle” are both thoughts from the viewpoint of kinematics, and as mentioned above, “sympathetic muscle facilitation” is an idea from the viewpoint of neurophysiology.
  • muscle grouping is performed in accordance with “muscle directionality” and “cooperative muscle”. For example, even with respect to flexion and extension, it may be an antagonistic muscle in adduction and abduction, even if it is a cooperative muscle. If necessary, it is desirable to confirm the grouping by “unknown muscle facilitation”.
  • the classification of the muscle group M i of cooperative muscle has been known to change by the displacement of the body posture and joint.
  • the classification can be treated as a static one that does not change approximately, the classification can be changed dynamically according to the posture of the body or the displacement of the joint in order to further improve the accuracy.
  • the second technical means is an invention of the device, Each joint torque during exercise of the subject is calculated by inverse dynamics calculation using a musculoskeletal model, and the muscle tension of each muscle is estimated by distributing the joint torque to the muscle tension by optimization calculation.
  • second grouping means in which the bones that start and stop form one or more subgroups from the same muscle; Become The muscle tension acquisition means regards the muscle activity level of muscles belonging to the same subgroup as the same, and estimates the muscle activity level representing each subgroup in the one or more subgroups by optimization calculation.
  • one of electromyograph is mounted A first subgroup formed of a representative muscle and a muscle having the same bone that starts and stops; For muscles belonging to the first group, it is assumed that the muscle activity obtained from the myoelectric potential should match the muscle activity calculated by the optimization calculation, and the muscle of the representative muscle measured in the optimization calculation Use activity as a reference value.
  • a first incision group M iEMG comprising the representative muscle of each muscle group M i
  • bones and origin stopped first muscle group M iEMG are the same (contributing joints are exactly the same) and the second incision group M Ihigh consisting muscle, A first muscle group M iEMG , a third muscle group consisting of muscles not included in the second muscle group M high ;
  • Divided into Obtaining the muscle tension of the muscles belonging to the first muscle group MiEMG and the second muscle group Mhigh from the myoelectric potential of the representative muscle measured during the exercise of the subject;
  • the muscle tension of the muscles belonging to the third muscle group is calculated by inverse dynamics calculation to calculate the joint torque necessary to realize the exercise of the subject, and in the joint torque, the first muscle group MiEMG and Estimating by optimizing to realize joint torque that cannot be realized by muscles belonging to the second muscle group M high , This is an estimation method of muscle
  • each electromyograph is attached to one representative muscle selected from the muscle group M i
  • the second grouping means includes the plurality of lines, A first incision group M iEMG comprising the representative muscle of each muscle group M i, In each muscle group M i, and a second incision group M Ihigh consisting muscle is a bone to the origin stop first muscle group M iEMG the same, A first muscle group M iEMG , a third muscle group consisting of muscles not included in the second muscle group M high ; Divided into The first muscle tension acquisition means acquires the muscle tension of the muscles belonging to the first muscle group MiEMG and the second muscle group Mhigh from the myoelectric potential of the representative muscle measured during the exercise of the subject, The second muscle tension acquisition means calculates the muscle torque of the muscles belonging to the third muscle group, and calculates the joint torque necessary for realizing the movement of the subject measured by inverse dynamics calculation. Estimating by optimizing to realize joint torque that cannot be realized by the muscles belonging to the first muscle group MiEMG and the second muscle group Mihigh ,
  • the third technical means has several modes.
  • the muscle that does not belong to any muscle group M i and muscle groups M others wherein the third muscle group, in each muscle group M i, contained the first muscle group M iEMG, and the second muscle group M are not included in ihigh muscle groups M Ilow, and the muscles M others, is .
  • a plurality of streaks, all muscle are classified as belonging to one of the muscle groups M i, Wherein the third muscle group, in each muscle group M i, the first muscle group M iEMG, include muscle which is not included in the second muscle group M Ihigh.
  • each muscle group M i a plurality of muscles belonging to the muscle group M high do not antagonize.
  • multi-joint muscles in one aspect, they are grouped so as to include mainly the joints involved.
  • the muscle tension of the muscles included in the first muscle group MiEMG and the second muscle group Mihigh is determined by measuring the muscle activity obtained from myoelectric potential data, muscle parameters obtained by empirical rules, and measurement. It is acquired from the muscle length obtained by the inverse kinematics calculation based on the exercise data and the change speed of the muscle length.
  • the myoelectric potential of the muscles included in the second muscle group M high is determined as a function of the myoelectric potential of the representative muscle.
  • the myoelectric potential of the muscle included in the second muscle group M high is regarded as the same as that of the representative muscle, but the myoelectric potential of the second muscle group M high is the muscle of the first muscle group Mi EMG. It does not have to be exactly the same as the electric potential, and can be determined by a function obtained from the geometric position, posture, etc. of these muscles.
  • the number n of the number of channels and muscle groups M i of electromyograph are the same. If the number n of the number of channels and muscle groups M i of electromyograph do not match, for example, when the number of channels of the myoelectric potential is small, sets the M iEMG for any group of muscle groups M i, myoelectric Wear a meter.
  • the optimization calculation is Assuming that the plurality of muscle groups drive the skeleton, a first step of estimating for each muscle group the joint torque to be output by each muscle group; A second step for estimating the muscle tension output by each muscle so as to realize the joint torque estimated in the first step in each muscle group; Consists of.
  • the idea of reducing the size of the optimization calculation problem by the number of muscles that can be solved using EMG information is also advantageous when obtaining some muscle tensions.
  • grouping is used to determine the line that EMG solves, but grouping is also useful for reducing the dimension of the line that is solved by the remaining optimization calculations.
  • the constraint condition means an inequality constraint condition in which the muscle does not exert a force in the extending direction.
  • an accurate solution can be obtained even if the constraint condition is only ambiguous if the relationship between the muscles considered in the optimization is not included. Therefore, by first grouping muscles, assuming that a plurality of muscle groups drive the skeleton, a torque to be output by each muscle group is obtained by the former method with high calculation cost.
  • the muscle dimension means the number of muscles. More specifically, the muscle dimension refers to the number of independent variables in determining the muscle tension throughout the body. If the tension is determined independently for each muscle, the total number of muscles becomes a dimension, which in this case becomes a large-scale optimization problem. If the muscles are grouped and the distribution rule of the tension within the group is determined, the independent variable in determining the muscle tension of the whole body is the number of groups. The muscle dimension in this case is the number of muscle groups.
  • muscle tension is estimated in real time as the subject exercises.
  • the muscle tension estimation device is a real-time muscle tension estimation device that estimates muscle tension in real time during exercise of a subject.
  • the fourth technical means adopted by the present invention is a method invention.
  • the subject's captured image or / and a composite image based on the captured image are displayed on the display unit, and a musculoskeletal model is overlaid on the displayed subject's image,
  • the activity information inside the body based on the muscle tension obtained by the above estimation method is reflected in the musculoskeletal model and displayed visually. It is a method for presenting activity information inside the body.
  • the fourth technical means is the invention of the device.
  • a real-time muscle tension estimation device Means for photographing the subject during exercise; Display means for displaying a photographed image of the subject or / and a composite image based on the photographed image; With The musculoskeletal model is overlaid on the image of the subject displayed on the display means, and the activity information inside the body based on the muscular tension estimated in real time by the real-time muscular tension estimation device is reflected in the musculoskeletal model to visually Configured to display real-time, A device for presenting activity information inside the body. In one aspect, internal body activity information is displayed in real time as the subject exercises.
  • the activity information inside the body is muscle activity.
  • muscle activity is visually displayed by a change in muscle color or / and shape of the musculoskeletal model.
  • the activity information inside the body represents muscle activity as activity of a spinal nerve bundle that governs the muscle activity.
  • the spinal nerves control a plurality of muscles, and the activity of all the muscles that control them is calculated as the activity of the spinal nerve bundle.
  • spinal nerve bundle activity is displayed visually by changing the color or / and shape of the symbol at each spinal nerve bundle location on the musculoskeletal model.
  • the scale of the optimization calculation is reduced.
  • muscle tension can be estimated in real time, and muscle activity based on muscle tension can be visualized in real time.
  • the scale of optimization calculation can be reduced by EMG information (used together with the Hill-Strove model) and grouping.
  • EMG information used together with the Hill-Strove model
  • the muscle tension of the whole body can be estimated in real time by combining optimization calculation methods with a comparatively small calculation amount. Therefore, somatosensory information can be presented during sports training or rehabilitation.
  • FIG. 5 shows a real-time overlay of a musculoskeletal model and estimated muscle tension information on a subject image during exercise of the subject.
  • the upper figure shows squats, and the lower figure shows pitching motion. Actually, when the muscle tension increases, the color of the muscle changes from yellow to red. It is a figure which shows the squat of FIG. 6 in the time series of several frames. It is a figure which shows the pitching operation
  • Embodiments of the present invention will be described in detail. First, the concept and technique that are the background of the present invention will be described. These concepts and techniques are not only the background art of the present invention, but also the techniques that can be used to implement the embodiments of the present invention. Next, an embodiment of muscle tension estimation according to the present invention will be described. In addition, about the number of a numerical formula, it assign
  • F max is the maximum muscle tension
  • F l (l) and F v (l (dot)) are functions representing the relationship between the normalized muscle tension, the muscle length, and the rate of change of the muscle length, respectively.
  • F l (l) corresponds to FIG. 1 and is approximated by a Gaussian function of Equation (2).
  • l 0 is the natural length of the muscle.
  • F v (l (dot)) corresponds to FIG. 2 and is approximated by equation (3).
  • K l , V sh , V shl , and V ml are constants, and in one embodiment, values shown in Stroeve (Table 1) are used. These values may be identified based on the motion capture data.
  • Data necessary for estimating muscle tension using the Hill-Stroeve muscle model includes muscle length, muscle length change rate, and muscle activity.
  • the muscle tension f * of each muscle is expressed by the following expression.
  • a i , l i , l (dot) i , and F max represent the activity, muscle length, muscle activity, and maximum muscle tension of the i-th muscle, respectively, and F l and F v are normalized, respectively. It is a function showing the relationship between the made muscle tension, muscle length, and muscle length change speed.
  • Nmus represents the total number of muscles included in the musculoskeletal model. Muscle length l 1 ,... L Nmus and muscle length change speed l (dot) 1 ,... L (dot) Nmus can all be calculated from motion data obtained from motion capture.
  • the myoelectric potential of multiple muscles for each joint was measured with an electromyograph, and the force expressed as% MVC (Maximal Voluntary Contraction (MVC)). Etc.) is used as the activity level of the muscle.
  • MVC Maximum Voluntary Contraction
  • FIG. 1 Musculoskeletal model A detailed whole body musculoskeletal model used in the embodiment of the present invention will be described.
  • the designed detailed human body model is composed of a skeletal rigid body model grouped with appropriate fineness and a muscle / tendon / ligament wire model stretched on the skeleton.
  • the skeletal model consists of 206 bones throughout the body. Of these, the skull, hand, and toe are treated as a single rigid body, and the model is composed of a total of 53 links. Between each link is a spherical 3 degrees of freedom joint, except for the tarsal bone-toe toe rotation 1 free joint and the first thoracic vertebra 6 breast joint.
  • the skeletal model has a total of 155 degrees of freedom, adding 6 degrees of freedom for the entire translational rotation.
  • Muscles, tendons, and ligaments are modeled as wires that pass through the start point, end point, and waypoint at each link.
  • Bones, muscles, tendons and ligaments have the following properties. Bone: A rigid link with mass. Muscle: A wire that actively generates tension. Tendon: A passively tensioning wire that connects to muscles and transmits muscle tension to bone. Ligaments: Passive tension wires that connect bones and constrain their relative movement. Differences in muscle, tendon, and ligament functions are modeled as follows. A simple part consisting of a series connection of muscles and tendons is represented by a single muscle wire.
  • tendons such as the upper arm bilateral muscle branch and the branched tendons connect to different bones. Since the start point, end point, and waypoint of the wire are all fixed to the link, a virtual link is placed at this branch point. The virtual link has no mass but transmits tension. The virtual link can move freely so that the force and moment are zero. Wide muscles such as the great pectoral muscle and latissimus dorsi are expressed by a plurality of parallel muscle wires.
  • a musculoskeletal model is also described in Patent Document 1, for example, and can be referred to.
  • the above-mentioned musculoskeletal model is merely an example, and the musculoskeletal model that can be applied to the present invention is not limited to these.
  • the device for acquiring muscle tension includes a plurality of imaging means (camera) for imaging a subject to which a marker is attached, a floor reaction force measuring means (force plate), and an electromyograph means (myoelectric meter).
  • the computer apparatus includes an arithmetic processing unit that performs various calculations, an input unit, an output unit, a display unit, and a storage unit that stores various data.
  • motion capture data exercise data
  • myoelectric potential myoelectric potential
  • floor reaction force are simultaneously measured and used for optimizing muscle strength, thereby obtaining appropriate muscle strength both mechanically and physiologically.
  • muscle tension is calculated as follows. (1) The motion of the subject is measured by the motion capture system, and time-series data of the three-dimensional position of the marker is obtained. (2) The motion information including the joint angle, the joint angular velocity, and the joint angular acceleration is calculated from the three-dimensional position of the marker by inverse kinematics calculation. (3) The joint torque required to realize the motion is calculated by inverse dynamics calculation using the Newton oiler method or the like. (4) The joint torque obtained in (3) is mapped to the floor reaction force and the tension of the muscle, tendon, and ligament using the relationship between the muscle, tendon, ligament length change obtained from the joint angle and each joint angular velocity.
  • inverse dynamics the tension of muscles, tendons, and ligaments that realize the movement is obtained based on the movement data obtained by the movement measurement.
  • the flow of inverse dynamics calculation is as follows: 1. Calculation of joint torque by inverse dynamics of rigid link system; 2. Calculation of Jacobian for wire length joint value; The joint torque is converted into wire tension.
  • the joint torque ⁇ g necessary for realizing the motion in the skeleton model.
  • muscle, tendon, and ligament tension f equivalent to ⁇ g is obtained by using Jacobian J of muscle, tendon, and ligament length l for joint angle ⁇ g . It is expressed.
  • Jacobian J Since the calculation method of Jacobian J is well known to those skilled in the art, detailed description thereof is omitted here for the purpose of avoiding complicated description. As for the calculation method of Jacobian J, for example, JP 2003-339673 or “DE Orin and WW Schrader. Efficient computation of the jacobian” for robot manipulators. Inter-national Journal of Robotics Research, Vol. 3, No. 4, pp. 66.75, 1984 ”can be referred to.
  • the wire tension f Non-patent document 3 in the non-patent document 4 models a 989-dimensional. Therefore, there arises a redundancy problem in which f is not uniquely determined from ⁇ g .
  • the inverse dynamics calculation of the musculoskeletal model there is an undetermined problem that the number of elements of muscles, tendons, and ligaments is very large with respect to the parameters that determine movement, and the force cannot be determined uniquely. It is well known to those skilled in the art, and the joint moment obtained by the inverse dynamics calculation is distributed to the muscle tension of the muscle that drives each joint by the optimization calculation.
  • Patent Document 1 A method of setting some evaluation function and constraint conditions in order to determine f and solving using optimization by mathematical programming or the like is disclosed in, for example, Patent Document 1 and Non-Patent Documents 3 and 4. Specific examples of optimization calculation are shown below. However, it is known to those skilled in the art that several methods have been proposed as optimization calculation used for muscle tension calculation, and optimization calculation that can be applied to the present invention. Those skilled in the art will appreciate that is not limited to what is described herein.
  • ⁇ G Generalization force
  • J Jacobian matrix from generalized coordinates to wire length
  • f wire tension
  • J C Jacobian matrix from the generalized coordinates to the point of contact with the floor
  • ⁇ C contact force with the floor
  • Equation (4) is solved by the following flow.
  • the contact force ⁇ C with the floor is calculated considering only the row corresponding to 6DOF of the hip joint in the equation (4).
  • optimization is performed using quadratic programming.
  • muscle tension is calculated using linear programming or quadratic programming.
  • the contact force with the floor is a typical example of the contact force with the outside world.
  • the contact force with a wall other than the floor can be used.
  • Such muscle tension estimation by subtracting the contact force with the outside world is disclosed in Patent Document 1, Non-Patent Document 3, and Non-Patent Document 4.
  • Equation (6) The first term of Equation (6), Equation (7), and Equation (8) are intended to minimize the error in Equation (5) and ensure dynamic consistency.
  • Equation (5) can be written in the form of an equation, but the condition is relaxed in consideration of the case where equation (5) has no solution. Since the objective function formula (6) includes a ⁇ T ⁇ ⁇ , the minimum ⁇ ⁇ positively constrained by the formula (8) is obtained. On the other hand, by the equation (7) is made smaller than the [delta] tau error of formula (5). Considering these constraint conditions, the error in equation (5) can be minimized.
  • Equation (6), Equation (9), and Equation (10) have the effect of bringing f closer to the given target value f * .
  • Equation (11) is the upper limit and lower limit constraints of muscle / tendon / ligament tension
  • f max ⁇ 0 represents the maximum muscle tension.
  • the maximum muscle tension f max can be determined independently for each muscle. Using the Hill-Stroeve muscle model, f max can be calculated from the muscle length and its rate of change to give the maximum muscle tension.
  • Equation (6) Equation (12), and Equation (13) have the effect of smoothing the muscle tension as much as possible within the cooperative muscle group.
  • This effect can be realized by adding a term of sum of squares of muscle tension to the objective function in quadratic programming.
  • n m made from this muscle m-th cooperative muscles G m.
  • the average value of muscle tension in this cooperative muscle group is Is calculated by
  • f k represents the muscle tension of the k-th muscle.
  • the difference between the muscle tension of the k (k ⁇ Gm) th muscle and the average muscle tension in the cooperative muscle group that contains it is Can be expressed as Where EGmk is the i-th element Is a row vector.
  • FIG. 5 shows a schematic diagram of a real-time muscle tension visualization system.
  • the muscle tension visualization system includes a muscle tension estimation means, a means for acquiring activity information inside the body using the estimated muscle tension, an image of a subject taken during exercise and an estimated muscle tension / acquired body. Means for displaying internal activity information. More specifically, the muscle tension visualization system displays a plurality of imaging means (camera 1) for photographing a subject having a plurality of markers attached to a plurality of predetermined parts of the body, and displays the subject in motion on the display means.
  • imaging means camera 1
  • Photographing means for photographing, ground reaction force measuring means (force plate 3), myoelectric meter means (wireless myoelectric meter 4) such as myoelectric meter, and one or more computer devices 5 and display means (screen 6).
  • the computer device includes an arithmetic processing unit that performs various calculations, an input unit, an output unit, a display unit, and a storage unit that stores various data. By simultaneously measuring motion capture data (exercise data), myoelectric potential, and floor reaction force, and using them in optimizing muscle force, a muscle tension that is appropriate mechanically and physiologically is acquired.
  • FIG. 5A shows a flow diagram of the real-time muscle tension visualization system.
  • Human body motion data and floor reaction force are measured using an optical motion capture and force plate, and myoelectric potential data is measured using a wireless electromyograph.
  • Each data is acquired in real time in synchronization with the system control PC.
  • IK inverse kinetic calculation
  • the joint angle, the muscle length, and the muscle length change speed can be obtained.
  • IK inverse kinetic calculation
  • ID inverse dynamics calculation
  • the estimated muscle tension is visualized by a change in the color of the muscles arranged on the musculoskeletal model (for example, the color is changed from yellow to red as the muscle tension increases). Furthermore, the actual experimental scenery is photographed using a DV camera synchronously, and the viewpoints are matched and superimposed on the musculoskeletal model for visualization.
  • FIG. 6 shows a screen shot of the actually presented video.
  • Muscle tension acquisition is roughly divided into the following two steps. First, using EMG data, the muscle tension of a muscle to which an EMG electrode is attached and the muscle tension of a muscle closely related to the muscle are obtained. Next, the relationship between muscle tension f and joint torque ⁇ G ′ Is used to estimate the muscle tension of other muscles. In addition to reducing the number of unknowns, the EMG data enables efficient estimation of solutions that satisfy the following constraint (3).
  • Table 2 shows the number of elements and the degree of freedom of the musculoskeletal model.
  • the left column is a model for conventional analysis in which all muscles such as the standing spine of the trunk are modeled.
  • the objective function of the optimization calculation is And inequality constraints Optimization calculation is performed so as to satisfy (see Non-Patent Document 3).
  • the simplified model in the right column is a model in which elements of low importance are thinned out from a complex model that is a detailed model in the left column.
  • the models shown in Table 2 are examples, and the present invention is not limited to these models.
  • the number of muscles in the simplified model is increased from 274 to 314.
  • the scale of the optimization calculation is reduced by reducing the number of elements by reducing the number of elements by further grouping the simplified model for the purpose of reducing the calculation cost for real-time estimation.
  • the muscle tension can be estimated at 16 ms (10 times or more faster than the conventional optimization calculation).
  • Nerve connection is the connection of muscles via interneurons, and facilitating and inhibitory properties are considered.
  • Muscles with spectacular bonds act as cooperative muscles and muscles with inhibitory bonds act as antagonistic muscles.
  • muscle groups cooperative muscles
  • This is based on the premise of synonymous muscle facilitation and antagonistic muscle suppression, which can be expected to be facilitating within the same muscle group, and suppressive binding between muscle groups that exhibit antagonism. This is because the function of nerve connection can be considered in a simplified manner.
  • the muscles of the whole body are classified into groups of aliasing muscles, one muscle is selected as the representative muscle in the group, and an electromyograph is provided to measure the myoelectric potential of the representative muscle.
  • the activity level is set as a representative value of the activity levels of all muscles in the group.
  • muscles of the whole body are measured with 16 channels, which is the number of channels of a general wireless electromyograph.
  • the muscles represented in each group are the anterior deltoid muscle, the posterior deltoid muscle, the long biceps long head, the triceps lateral head, the rectus femoris, the biceps long head, the anterior tibial muscle, the gastrocnemius lateral head and To do.
  • The% MVC of each muscle is measured, and the muscle activity is obtained from the muscle length and the muscle length change rate obtained from the motion capture, and the muscle tension is obtained from the muscle activity levels of all the muscles in the alias muscle promotion group including the muscle.
  • attention is paid to the movement of the limbs, and the five joints (10 in total) on the left and right sides of the body are considered.
  • the muscles are divided into 8 groups as shown in Table 3.
  • MiEMG Muscle groups of representative muscles whose EMG signals are measured.
  • M high A muscle group composed of muscles that have exactly the same joints as the M iEMG .
  • M ilow A muscle group composed of muscles that are the same in part of the joints that contribute to the muscle group MiEMG .
  • M EMG , M high , and M low are respectively
  • M EMG M 1EMG ⁇ M 2EMG ⁇ ... EMM 8EMG A muscle that does not belong to any of the muscle groups of Table 3, M others.
  • the muscle tension of these muscles is acquired in the following flow. First, for the muscles included in M EMG and M high , muscle tension is acquired from the myoelectric potential and the Hill-Stroeve muscle model. Then, the muscle tension of the muscles included in the remaining muscles, that is, the muscles included in M low and Others , is estimated by inverse dynamics calculation and optimization calculation.
  • the evolution of muscle activity a i is modeled by a first-order differential equation.
  • T is a time constant
  • u i is an input from a motor nerve calculated from an EMG signal normalized by MVC.
  • Several methods are known to those skilled in the art for calculating the degree of muscle activity from the EMG signal. For example, the calculation methods described in the following documents can be used. S.Stroeve. Learning combined feedback and feedforward control of a musculoskeletal system. Biological Cybernetics, Vol. 75, pp. 73.83, 1996.
  • the muscle tension of the representative muscle of each group can be calculated directly from Equation (4).
  • the muscle k ⁇ M high can be estimated from the activity of the representative muscle r ⁇ M iEMG of the same group by the following equation.
  • E r ⁇ k (*) represents the activity of a i of muscle k included in the group M i, the relationship between the activity of a r of the measurement representative muscle.
  • a method according to cosine tuning claimed by Georgepoulos et al. Can be considered, but here it is defined by the following equation.
  • the muscle tension f and Jacobian J in equation (1) are distributed to each muscle group.
  • J EMG , J high , J low , J others are the muscle length Jacobian matrix for each joint angle
  • M EMG , M high , M low , M others , f EMG , f high , f low , f others are , Muscle tension in each group.
  • ⁇ G ′ is a generalized force from which the floor reaction force ⁇ C has already been subtracted.
  • the deformation is made as follows. here, although the number of unknowns is reduced, it has an inequality constraint f ⁇ 0, and therefore it is necessary to perform an optimization calculation with an iterative calculation.
  • Equation (6) an initial estimated value of M low muscle tension is obtained.
  • k ⁇ M ilow is r ⁇ M iEMG. Since the muscle r and the muscle k belong to the same synonymous muscle promotion group, it can be said that the expression (11) is appropriate as an initial value.
  • the muscle tension is corrected using the joint torque obtained by the inverse dynamics calculation.
  • the algorithm repeats the following steps for each joint j.
  • Step 1 Drive joint j and collect all muscles belonging to M low and M others to form muscle group M Jj . Further, a matrix corresponding to the joint j in equation (9) and the muscle in the muscle group M Jj is extracted, And
  • Step 2 For all muscles k ⁇ M Jj , obtain an initial estimate of f jk0 by the following formula: By correcting f * jk0 for all k, f * j0 is formed.
  • Step 3 Subtract J T j f * j0 from equation (12) to obtain the following equation.
  • Step 4 J T j of SR-inverse, using J T * j, solving Delta] f j0, obtain f j updated by the following equation.
  • Step 5 Form a vector f j1max having the same size as f j1 and the element being the maximum value (positive) of f j1 .
  • Computing the second estimated value f * j1 f j1 -f j1max ⁇ 0.
  • Step 6 Subtract J T j f * j0 from equation (12) to obtain the following equation.
  • Step 7 Again, ⁇ f j1 is solved using SR-inverse of J T j and f j is updated by the following equation. Similar to the discussion in step 4 above, many elements of f j2 are negative and, if positive, are expected to be at least small. Therefore, f j2 can be used as an approximation of f j .
  • the above algorithm uses only J T j SR-inverse, and only the muscles that drive the joint j need to be considered, so the size of J j is small. Therefore, this algorithm is faster than the optimization calculation by iterative calculation.
  • the time required to estimate muscle tension of the whole body was 16 ms, and the time required to visualize somatosensory information was 68 ms (the computer used was 3.33 GHz Intel Xeon processor (3.25 GB RAM, NVIDIA Quadro FX3700). As a result, a 15fps frame rate visualization system was constructed.
  • a photographed image of a subject and / or a composite image based on the photographed image is displayed on a display unit, and the musculoskeletal is displayed on the displayed subject image.
  • the model is overlaid, and the activity information (somatosensory information) inside the body based on the muscle tension acquired by the above estimation method is reflected in the musculoskeletal model and displayed visually.
  • the ⁇ motor neurons in the spinal cord are activated in an excitatory manner by motor command signals from the upper center or signals from muscle proper sensory receptors. This signal goes out of the spinal cord through the spinal nerve bundle. From the ⁇ motor neuron to the endplate structure on each muscle, the “spinal nerve bundle” differentiates and signals are transmitted. In the endplate structure, excitatory signals are combined to give action potentials to the muscles. This leads to “muscle activity”. “Muscle tension” is generated when action potential is transmitted on the muscle. Therefore, in order to acquire and present the muscle activity level and spinal nerve bundle activity in real time, it is important to acquire muscle tension in real time.
  • the musculoskeletal model is overlaid and displayed on the video taken by the video camera, and the muscle activity is expressed by the color and shape of the muscle on the musculoskeletal model.
  • the muscle tension / muscle activity level is displayed by continuously changing the color of the muscle, for example, from yellow to red. Accordingly, in the overlay, the portion where the muscle is active is displayed in red, for example.
  • muscle fatigue may be expressed by muscle thickness. In one aspect, a value obtained by integrating the muscle tension over time is used as muscle fatigue.
  • a symbol for example, a sphere
  • the activity is expressed by its color (see FIG. 9).
  • a sphere is displayed at the position of the spinal nerve bundle in the musculoskeletal model displayed on the display unit, but this can be further overlaid on the image of the subject.
  • the following documents can be referred to. Murai, A, Yamane, K, and Nakamura, Y, "Modeling and Identification of Human Neuromusculoskeletal Network Based on Biomechanical Property of Muscle, "the 30 th IEEE EMBS Annual International Conference, pages 3706-3709, Vancouver, August 2008.
  • FIG. 5A the joint angle of the subject is obtained by optical motion capture and inverse kinematics calculation.
  • the joint torque is obtained by performing the reverse dynamics calculation from the joint angle obtained from the reverse kinematics and the floor reaction force obtained from the force plate.
  • optimization calculation is performed based on muscle grouping from EMG and joint torque, and muscle tension is estimated.
  • Muscle proper receptors sense changes in muscle length, rate of change, and muscle tension. Muscle length and the rate of change are sensed by the muscle spindle, and muscle tension is sensed by the Golgi tendon organ.
  • Properceptors contribute to central motor regulation from two aspects. One is the reflex effect, and the other is that information from proper receptors conveys the state of movement and posture to the upper brain. When movement occurs in response to a movement command, the state of the muscle changes, and the proper receptor reflex is inevitably triggered. The reflection effect is reflected in the motion program and contributes to the formation and correction of the motion pattern.
  • Stretch reflex is the firing of nerve fibers derived from the main spindle of the main muscle, which is the motor neuron that controls the muscle (Same muscle motor neuron ) And its synergistic motor neurons cause monosynaptic excitement.
  • the signal returned from the Ia group nerve fiber of that muscle gives excitement effect to the motor neuron of the synergistic muscle and signals to the synergistic muscle Will be sent.
  • muscle tension is distributed among the cooperative muscles in order to generate joint torque.
  • cooperative muscles are expected to have the same degree of muscle activity. Therefore, paying attention to the cooperative muscles, the cooperative muscles have the same degree of muscle activity, and the grouping is performed to reduce the calculation.
  • the synergistic muscle has not been clarified from the connection of group Ia nerve fibers and motor neurons.
  • cooperative muscles are considered from the viewpoint of kinematics rather than anatomy, and grouping of cooperative muscles is performed.
  • i and j are used as the muscle group index, and k is used as the muscle index.
  • n G is the number of groups of M i. Each group is further classified into the following two groups.
  • M ihigh Muscle where EMG representing the group is measured, and muscle where EMG is measured and the bone that starts and stops are the same. Muscles belonging to the same group are expected to have similar muscle activity.
  • M high in the second embodiment corresponds to M EMG + M high in the first embodiment.
  • M ilow A muscle not belonging to the above Mi high . Further, it is classified into M i, 1low , ..., M i, nilow according to the bone that has started and stopped.
  • n i is the number of groups of M i, jlow in M ilow .
  • M high M 1high ⁇ M 2high ⁇ ... ⁇ M nGhigh
  • M low M 1low ⁇ M 2low ⁇ ... ⁇ M nGlow defines M high and M low .
  • the number of muscles measuring myoelectric potential is n EMG ( ⁇ n G )
  • the group containing the muscles measuring myoelectric potential is M 1 , ..., M nEMG , M (nEMG + 1) high , ..., M nghigh is an empty set.
  • Table 4 can be referred to for the muscle that measures EMG and the movement of the joint to which the muscle contributes.
  • the reason why the number of muscles belonging to each group is slightly different from that in Table 3 is that the number of muscles in the musculoskeletal model (simplified model) that is a premise of grouping differs between the first embodiment and the second embodiment.
  • the muscles belonging to M high the muscles representing the group and for which the myoelectric potential is measured are shown in bold.
  • a musculoskeletal model such as the great pectoral muscle or latissimus dorsi muscle, one muscle may be represented by multiple wires, but here it is also represented as a single muscle when represented by multiple wires.
  • Groups 1-8 correspond to M 1 ,..., M nEMG (corresponding to groups 1-8 in Table 4).
  • M high is an empty set. It should be noted that the following grouping is merely an example, and those skilled in the art will understand that groupings that can be applied to the present invention are not limited to those described in this specification.
  • Group 1 Horizontal adduction of shoulder joint Group 2: Horizontal abduction of shoulder joint Group 3: Elbow joint flexion Group 4: Elbow joint extension Group 5: Hip joint extension and knee joint flexion Group 6: Hip flexion and knee extension Group 7: Ankle joint dorsiflexion Group 8: Ankle joint plantar flexion Group 9: Flexion of neck joint Group 10: Shoulder joint control Group 11: Raising the shoulder joint Group 12: wrist flexion Group 13: Wrist joint extension Group 14: External rotation of hip joint Group 15: Flexion of tarsal metatarsal joint Group 16: Trunk flexion Group 17: Trunk extension Group 18: Raising the trunk
  • the muscle tension f k of muscle k ( ⁇ M * ) is It can be expressed as F maxk is the maximum muscle tension of muscle k, F l (l k ) is the ratio of muscle tension that the muscle can exert when the length of muscle k is l k , F v (l (dot) k ) Is the ratio of muscle tension to maximum tension that can be exerted when the contraction speed of muscle k is l (dot) k .
  • the muscle activity vector a representing each group is obtained by quadratic programming.
  • Quadratic programming is an objective function, Is a method for obtaining x that minimizes x under linear equality constraints and inequality constraints on x.
  • x and c are n-dimensional vectors
  • Q is an n ⁇ n matrix.
  • the muscle tension of a muscle belonging to M high is obtained using the Hill-Stroeve muscle model using the muscle activity obtained from the myoelectric potential as it is, and the muscle tension of a muscle belonging to M low is reversed. It is calculated by kinematics and quadratic programming.
  • the muscle activity calculated by EMG is given as a reference value, and the muscle tension of all the muscles including the muscle belonging to M high is obtained by the quadratic programming method.
  • the reduction in the amount of calculation for optimization calculation mainly depends on the grouping of muscles. Further, the calculation speed can be increased by performing parallel processing of IK, ID / muscle tension estimation, and drawing calculation.
  • Condition 1 Muscle torque generated by joint torque and muscle tension obtained by inverse kinematics is equal. That is, Expression (7) is satisfied.
  • Condition 2 A muscle activity pattern is generated such that the sum of muscle activity is minimized.
  • Condition 3 The muscle activity of the muscle whose myoelectric potential is measured is equal to the muscle activity calculated from the myoelectric potential.
  • Condition 4 Muscle activity a * is between 0 and 1.
  • the muscle activity calculated by quadratic programming should match the muscle activity calculated from the measured myoelectric potential.
  • Equation (13) has the form of the quadratic programming objective function shown in Equation (8). Can be considered.
  • the inequality constraint condition is It becomes. If a is obtained by quadratic programming under the objective function Z and the inequality constraint condition (17), the muscle tension of the muscle k ( ⁇ M * ) can be obtained from the equation (1).
  • FIGS. 10 and 11 show the grouping of the technique of the first embodiment
  • FIG. 11 shows the grouping of the technique of the second embodiment. 10 and 11, the number of electromyographs is three for simplicity. In FIG. 11, a broken line is an empty set.
  • Activity of the muscle of the M ihigh is uniformly on which were the same as the M iEMG, put it together than the rest of all of the muscle (M ilow and M others).
  • All the remaining streaks are calculated from dynamic force balance using SR-Inverse (like a stable inverse matrix).
  • Each one of all the remaining streaks (about 350 in the first embodiment) is calculated as a variable, and the quadratic programming method is not used. In the previous optimization calculation, quadratic programming or linear programming was used to calculate about 1000 muscle activities.
  • the muscle group M i is further classified into a plurality of subgroups by grouping them into cooperative muscle groups having the same activity (muscle groups having common bones that start and stop).
  • muscle M Ihigh is all muscle other than M Ilow, classified into M Ilow further subgroup by summarized M Ilow each cooperative muscles (M i, consists Jlow) Is done.
  • M i, jlow is a muscle group having common bones that start and stop in M ilow .
  • the total number of subgroups is about 70.
  • the muscle activity belonging to each subgroup is uniformly expressed by about 70 variables, and this is subjected to optimization calculation of the quadratic programming method.
  • the muscle activity of the muscle M iEMG to which myoelectricity is applied is used as a reference value for the muscle of Mi high .
  • the present invention can be used in the fields of sports training, rehabilitation, medical diagnosis, health management, entertainment, and the like.

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Abstract

L'invention permet de réduire l'échelle de calcul d'optimisation servant à évaluer une tension musculaire. Plusieurs muscles sont catégorisés en plusiseurs groupes musculaires Mi (i=1, 2, …n) selon l'orientation du mouvement musculaire ou la facilitation hétéronyme musculaire. Pour chaque groupe musculaire, sont formés un ou plusieurs sous-groupes comprenant des muscles mus ou immobilisés par les mêmes os; le degré d'activité musculaire des muscles appartenant à un même sous-groupe est considéré comme similaire. Pour une partie ou la totalité de plusieurs groupes musculaires Mi, parmi un ou plusieurs des sous-groupes mentionnés, un sous-groupe consiste en un premier sous-groupe formé à partir d'un muscle représentatif sur lequel est disposé un électromyographe, et des muscles mus ou immobilisés par les mêmes os que le muscle représentatif. L'obtention, grâce au potentiel myoélectrique du muscle représentatif susmentionné mesuré lors du mouvement d'un sujet de l'expérimentation, de la tension musculaire d'un muscle appartenant au premier sous-groupe, permet de réduire une variable du calcul d'optimisation. Alternativement, l'évaluation, grâce à un calcul d'optimisation, du degré d'activité musculaire représentant chaque sous-groupe, permet de réduire une variable du calcul d'optimisation.
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WO2013144866A1 (fr) 2012-03-27 2013-10-03 B10Nix S.R.L. Système d'acquisition et d'analyse d'activité musculaire et son procédé de fonctionnement
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