JP6435302B2 - Exercise state and psychological state determination method, apparatus, and program - Google Patents

Description

  The present invention relates to a technique for determining an exercise state and a psychological state.

  It is extremely important that an actor objectively grasps his / her physical movements in order to appropriately acquire basic movements of sports such as pitching in baseball, swinging in batting, golf, and putting. It is an improvement of the behavior that the actor performs while looking at himself in the mirror, or the behavior of the actor is recorded on the video and the actor himself observes it to find the problem of the behavior. This is an effective approach. However, the information obtained by observing the body movement is only the mechanical movement state of the body part, and the activity state of the muscle that produces the movement cannot be directly grasped.

  On the other hand, there is a technique for acquiring a muscle activity state by a myoelectric potential signal and superimposing the information on an image of a body part (for example, see Non-Patent Document 1). However, performing an operation while watching a video may significantly hinder the task.

  On the other hand, it is easy to perform body movements while listening to acoustic signals, and auditory information is suitable for simultaneous acquisition while performing body movements compared to visual information. If the muscular strength state can be grasped in real time during task execution using auditory information, it becomes easier to confirm the timing and strength at which the actor himself exerts his power, and facilitates the discovery of problems in physical movement Is done. For this reason, a technique has been proposed in which changes in the activity state of muscles are reflected in changes in the characteristics of acoustic signals and presented to an actor in real time as auditory information (see, for example, Non-Patent Document 2).

  Similarly, a technique has been proposed in which “variation” and “rhythm”, which are points of exercise, are visualized and audible with images and sounds to make it easier to grasp the tips of exercise (see, for example, Non-Patent Document 3). .

Even if you can grasp the knack of exercise, it is not enough, and it is also important to maintain a better psychological state in order to perform as usual or higher. Extreme strength and tension is known to reduce performance. (For example, Non-Patent Document 4)
There are also known methods for quantifying tension / relaxation, for example by calculating the low frequency component (LF: 0.05-0.15 Hz) and the high frequency component (HF: 0.15-0.4 Hz) of heart rate variability. , HF is evaluated as the degree of relaxation, and LF / HF is evaluated as the degree of tension (Non-patent Document 5).

Naoto Igarashi, Kengo Suzuki, Hiroaki Kawamoto, Yoshiyuki Sankai, “Wearing Light-Emitting Sensor Suit Presenting Lower Limb Movement State”, Information Processing Society of Japan Interaction 2011 Masaki Matsubara, Yoko Terasawa, Hideki Kadone, Kengo Suzuki, Shoji Makino, “Muscle Activity Awareness for Understanding the Linkage of Body Movements”, Proceedings of the Autumn Meeting of the Acoustical Society of Japan, P.919-922, 2012 http://www.kecl.ntt.co.jp/openhouse/2014/exhibition/25/index.html Psychophysiology, 47 (2010), 1109-1118. Wiley Periodicals, Inc. “Psychological, muscular and kinematic factors mediate performance under pressure” http://www.frontiersin.org September 2014 | Volume5 | Article1040 | 1-19 “Ahealthy heart is not a metronome: an integrative review of the heart ’s anatomy and heart rate variability”

  As mentioned above, methods for visualizing and audible “variation” and “rhythm”, which are the points of exercise, with images and sounds have been proposed, but “correct exercise” and “target exercise” are unclear. Therefore, even if the “variation” decreases and the “rhythm” becomes constant, it cannot be said that it leads to improvement of exercise.

  In other words, by just visualizing and audibly exercising the current exercise, the acter of the exercise does not know whether the current exercise is close to the “correct exercise” or the “target exercise” or is not, and changes the current exercise. As a result, it is not known whether the changed exercise has approached the “correct exercise” or the “target exercise” or has gone.

  Taking the baseball pitcher's movement as an example, the initial movement is close to the “correct exercise”, but it may be off the “correct exercise” in the middle and return to the “correct” exercise in the second half. However, since such a judgment cannot be made, it is not sufficient to visualize and audible the current exercise, and improvement is desired.

  Further, it is difficult to determine which psychological state is preferable, and a mechanism for determining whether the current psychological state is preferable or not is desired.

  The present invention has been made by paying attention to the above circumstances, and the purpose of the present invention is to determine the current exercise and psychological state (determination target) for the reference exercise state and psychological state (correct exercise state and better psychological state). It is to provide an exercise state and psychological state determination method, apparatus, and program that output (exercise state and psychological state).

  (1) In order to achieve the above object, the exercise state and psychological state determination method according to the embodiment is based on at least primary biological information acquired from a primary subject during a predetermined exercise, and the exercise state of the primary subject Determining or storing the psychological state and determining the motor and psychological state of the secondary subject based at least on the secondary biological information acquired from the secondary subject during the predetermined exercise, and the primary subject. The movement state and psychological state of the second subject are compared with the movement state and psychological state of the secondary subject, and a comparison result is output.

  (2) Furthermore, in the exercise state and psychological state determination method according to (1) above, the primary biological information includes at least myoelectric potential data and cardiac potential data, and the secondary biological information also includes at least myoelectric potential data and cardiac potential. Contains data.

  (3) Furthermore, in the exercise state and psychological state determination method according to any one of (1) and (2) above, the primary patient's exercise state and psychological state are obtained from a plurality of the primary subjects. Or is determined based on the primary biometric information.

  (4) Furthermore, in the exercise state and psychological state determination method according to any one of the above (1) to (3), the primary patient's exercise state and psychological state are the primary during a plurality of predetermined exercises. It is determined or determined based on primary biological information from the subject.

  (5) Furthermore, in the exercise state and psychological state determination method according to any one of (1) to (4), the exercise state and the psychological state of the secondary subject are the plurality of times during the predetermined exercise. The determination is based on secondary biological information from the secondary subject.

  (6) Furthermore, in the exercise state and psychological state determination method according to any one of (1), (2), (4) to (5), the primary subject and the secondary subject are: , The same subject.

  (7) Furthermore, in the exercise state and psychological state determination method according to any one of (3) to (6), the exercise state and psychological state of the primary subject are determined based on the statistics of the primary biological information. Is or has been determined.

  (8) Furthermore, in the exercise state and psychological state determination method according to any one of (3) to (7) above, the secondary patient's exercise state and psychological state are determined by the statistics of the secondary biological information. Judgment based on this.

  (9) Furthermore, in the exercise state and psychological state determination method according to any one of (2), (4) to (6), the myoelectric potential data of the primary subject is a plurality of locations of the subject. The myoelectric potential data of the secondary subject is myoelectric potential data from a plurality of locations of the secondary subject.

  (10) Furthermore, in the exercise state and psychological state determination method according to (9), the exercise state of the primary subject is determined based on myoelectric potential data statistics from a plurality of locations of the primary biological information, or The movement state of the secondary subject is determined based on statistics of myoelectric potential data from a plurality of locations of the secondary biological information.

  (11) Furthermore, in the exercise state and psychological state determination method according to (9), the psychological state of the primary subject is acquired from the primary subject during a predetermined exercise in a first situation. The secondary biological information is determined or determined based on primary biological information, and the psychological state of the secondary subject is acquired from the secondary subject during a predetermined exercise in a second situation Based on the above, the psychological state of the secondary subject is determined.

  (12) Furthermore, in the exercise state and psychological state determination method according to (9), the first psychological state of the primary subject is acquired from the primary subject during a predetermined exercise at a first time. The second psychological state of the secondary subject is acquired from the secondary subject during a predetermined exercise at a second time. And determining the change in the psychological state of the secondary subject by comparing the first psychological state and the second psychological state.

  (13) The exercise state and psychological state determination apparatus according to the embodiment executes determination and comparison in the same manner as the exercise state and psychological state determination method according to any one of (1) to (12) above.

  (14) The exercise state and psychological state determination program according to the embodiment causes the computer to execute determination and comparison in the same manner as the exercise state and psychological state determination method according to any one of (1) to (12) above. .

  That is, according to this invention, the exercise state and the psychological state that output the current exercise and psychological state (the exercise state and the psychological state to be determined) with respect to the reference exercise state and the psychological state (the correct exercise state and a better psychological state) A determination method, apparatus, and program can be provided.

  According to the exercise state and psychological state determination method of (1) above, an exercise state based on at least primary biometric information acquired from a primary subject (for example, an advanced person or a professional (reference player)) during a predetermined exercise, A psychological state (primary index) and an exercise state based at least on secondary biometric information acquired from a substantially identical secondary subject during a predetermined exercise (for example, an aspiring candidate (unskilled person) or an advanced person); From the comparison result (difference from correct exercise) with the psychological state (secondary index), it is possible to determine the exercise state and psychological state (good or bad) of the secondary subject with respect to the primary subject. The primary biological information and the secondary biological information may be information from the same subject, for example, past information of the subject (for example, information when the condition is good) may be used as the primary biological information.

  According to the exercise state and psychological state determination method of (2) above, the primary biological information and the secondary biological information include at least myoelectric potential data and cardiac potential data. Comparison results between the exercise state and the psychological state based on the muscle activity level of the player who is) and the exercise state and psychological state based on the muscle activity level of the aspiring aspirant during substantially the same predetermined exercise (with correct exercise) From the difference), it is possible to determine the exercise state and the psychological state (good or bad) of the advanced candidate or the advanced candidate with respect to the professional exercise state.

  According to the exercise state and psychological state determination method of (3) above, the exercise state and psychological state based on the primary biometric information of 100 seniors and professionals (reference players) during a predetermined exercise are substantially the same. Based on the results of comparison between the physical state and psychological state based on the secondary biometric information of the aspiring candidates during a given exercise (difference from the correct motion), the motor state and psychological state of the advanced candidate and the professional state (Good or bad) can be determined.

  According to the exercise state and psychological state determination method of (4) above, the exercise state and the psychological state based on the primary biometric information of the advanced person or professional (reference player) during the predetermined 100 times of exercise are substantially the same. Based on the results of comparison between the physical state and psychological state based on the secondary biometric information of the aspiring candidates during a given exercise (difference from the correct motion), the motor state and psychological state of the advanced candidate and the professional state (Good or bad) can be determined.

  According to the exercise state and psychological state determination method of (5) above, from the exercise state and the psychological state based on the secondary biological information of the aspiring candidates during the substantially identical 100 times of predetermined exercise, It is possible to determine the motor status and psychological status (good or bad) of the candidate who wants to improve the motor status.

  According to the exercise state and psychological state determination method of (6) above, the exercise state (good or bad) can be determined with the primary subject and the secondary subject as the same subject.

  According to the motion state and psychological state determination method of (7) above, the motion state and psychological state (data when the ball speed is fast and control is good) based on the statistics of the primary biological information, and the motion state based on the secondary biological information And the psychological state (difference from correct exercise), it is possible to determine the exercise state and psychological state (good or bad) of an advanced candidate or an advanced candidate with respect to the exercise state and psychological state of a senior or professional.

  According to the exercise state and psychological state determination method of (8) above, from the exercise state and psychological state based on the statistics of the secondary biological information, the exercise state and psychological state of the advanced candidate and the advanced person and professional with respect to the motor state and psychological state. The state (good or bad) can be determined.

  According to the exercise state and psychological state determination method of (9) above, the predetermined predetermined state is substantially the same as the exercise state based on the activity levels of the muscles at a plurality of locations of a senior or a professional (reference player) during the predetermined exercise. From the results of comparison with the exercise status based on the activity level of the muscles at multiple locations of the aspiring candidates who are exercising (difference from the correct exercise), the exercise status (good or bad) of the aspiring candidates to the advanced or professional exercise status Can be determined.

  According to the method (10) for determining an exercise state and a psychological state, it is substantially the same as an exercise state based on statistics of myoelectric potential data from a plurality of locations of an advanced person or a professional (reference player) during a predetermined exercise. From the results of comparison with the motor status based on statistics of myoelectric potential data from multiple locations of the aspiring candidates during the predetermined exercise (difference from the correct exercise), the motor status of the advanced applicants to the advanced and professional motor status ( Good or bad) can be determined.

  According to the exercise state and psychological state determination method of (11) above, the psychological state of an advanced person or a professional (reference player) during a predetermined exercise in the first situation and the improvement during the predetermined exercise in the second situation From the comparison result with the psychological state of the candidate, it is possible to determine the psychological state (good or bad) of the advanced candidate or the advanced candidate with respect to the professional psychological state.

  According to the exercise state and psychological state determination method of (12) above, the psychological state of an advanced person or a professional (a reference player) during a predetermined exercise at the first time, and the improvement during the predetermined exercise at the second time From the comparison result with the psychological state of the candidate, it is possible to determine the psychological state (good or bad) of the advanced candidate or the advanced candidate with respect to the professional psychological state.

  According to the exercise state and psychological state determination device of (13) above, substantially the same effect as the exercise state and psychological state determination method described in any one of (1) to (12) above can be obtained.

  According to the exercise state and psychological state determination program of (14), substantially the same effect as the exercise state and psychological state determination method according to any one of (1) to (12) can be obtained.

It is a figure which shows an example of the feedback system for exercise | movement improvement. It is a figure which shows an example of a sensing part. It is a figure which shows an example of a state determination part. It is a flowchart which shows an example of the determination process of the exercise state by the exercise state and psychological state determination apparatus. It is a flowchart which shows an example of the determination process of the psychological state by an exercise state and a psychological state determination apparatus. It is a flowchart which shows an example of the determination process of the influence on the electromyogram data by the electrocardiogram data in an exercise state and psychological state determination apparatus. The block diagram for demonstrating the acquisition example of a myoelectric potential signal. The flowchart for demonstrating the example of the presentation methods, such as a myoelectric potential signal. The figure which shows the example of the mounting | wearing site | part of the myoelectric potential electrode A and the acceleration sensor B.

  Embodiments according to the present invention will be described below with reference to the drawings.

  FIG. 1 is a diagram illustrating an example of a feedback system 100 for improving exercise. As shown in FIG. 1, the feedback system includes an exercise state / psychological state determination device 130 and a feedback device 140. The exercise state and psychological state determination device 130 includes a sensing unit 131 and a state determination unit 132.

  In the present embodiment, the determination of the exercise state and the psychological state during exercise by the exercise state and the psychological state determination device 130 constituting the feedback system 100 will be mainly described. As an example of exercise, a baseball pitching operation will be described. Note that the feedback system described in the present embodiment is not limited to exercise improvement and high performance, but can also be used for rehabilitation, skill transfer, and the like.

  The sensing unit 131 senses signals from a plurality of myoelectric potential sensors 110 and at least one electrocardiographic sensor 120 attached to the primary subject and the secondary subject. The sensing unit 131 may sense a signal obtained from the chest, sense a signal obtained from the wrist instead of a signal obtained from the chest, or obtain a signal obtained from the chest and the wrist. It is also possible to sense the obtained signal and use either sensing result from the sensing results of both. The plurality of myoelectric potential sensors 110 and the electrocardiographic potential sensor 120 are configured by electrodes or the like. Each myoelectric potential sensor 110 outputs a myoelectric potential signal (biological information) corresponding to the activity level of the muscles. An electric signal (biological information) is output. For example, the plurality of myoelectric potential sensors 110 and the electrocardiographic potential sensors 120 are wearable sensors attached to the wear, and each myoelectric potential sensor 110 has a plurality of positions (arms, legs) on the primary subject and the secondary subject. The electrocardiographic sensor 120 is attached to the wear so as to correspond to the chest of the body of the primary subject and the secondary subject. Accordingly, the plurality of myoelectric potential sensors 110 and the electrocardiographic sensor 120 are used to detect myoelectric potential signals and electrocardiographic signals (primary subjects) corresponding to the activity levels of the muscles from a plurality of locations on the primary and secondary subjects' bodies. Primary biological information from the examiner and secondary biological information from the secondary subject) can be output, for example, myoelectric potential over a certain period of time (ie, during a predetermined exercise) from the start of the pitching operation to the end of the pitching operation. A signal and a cardiac potential signal can be output. Also, a plurality of myoelectric potential sensors 110 may be attached to a wristband, a glove, etc., and a myoelectric signal corresponding to the muscle activity level corresponding to the wearing position of the wristband, glove, etc. may be acquired. Alternatively, the electrocardiographic sensor 120 may be attached to a wristband, a hair band, or the like, and an electrocardiographic signal may be acquired from the mounting position of the wristband, the hair band, or the like. The primary biological information is not limited to the above-described electrocardiographic signal, and at least one of the electrocardiographic signal, pulse wave, breathing, sweating, brain wave, eye movement, and pupil diameter is used as the primary biological information. It can be.

  A plurality of myoelectric potential signals and cardiac potential signals from the plurality of myoelectric potential sensors 110 and the cardiac potential sensor 120 are input to the sensing unit 131. As shown in FIG. 2, the sensing unit 131 includes a signal amplifier 131a, etc., and the sensing unit 131 senses a plurality of myoelectric potential signals and cardiac potential signals amplified by the signal amplifier 131a, for example, before starting a pitching operation. Myoelectric potential data and electrocardiographic data are acquired over a certain period from the end of the pitching operation to the end of the pitching operation.

  For example, a plurality of myoelectric potential sensors 110 and an electrocardiographic sensor 120 are attached to the primary subject (the primary subject wears a wear on which the plural myoelectric potential sensors 110 and the electrocardiographic sensor 120 are attached), and the sensing unit 131 Acquires myoelectric potential data and cardiac potential data (primary biological information) over a certain period. Similarly, a plurality of myoelectric potential sensors 110 and an electrocardiographic sensor 120 are attached to the secondary subject (the secondary subject wears a wear on which the plural myoelectric potential sensors 110 and the electrocardiographic sensor 120 are attached), The sensing unit 131 acquires myoelectric potential data and electrocardiographic data (secondary biological information) over a certain period. In addition, the primary subject and the secondary subject may wear the same wear, and if the primary subject and the secondary subject have different physiques, different wear may be worn. In this case, the attachment positions of the plurality of myoelectric potential sensors 110 and the electrocardiographic sensor 120 in each wear are substantially the same corresponding positions.

  For example, the primary examinee is a senior or a professional pitcher, and the secondary examinee is a person who wants to improve baseball pitching skills (aspiring candidates). Myoelectric potential data and electrocardiographic data from one advanced pitcher or professional pitcher may be acquired and used as myoelectric potential data and electrocardiographic data from a primary subject, or myoelectric potential from 100 senior or professional pitchers. Data and electrocardiographic data may be acquired and used as myoelectric potential data and electrocardiographic data from the primary subject. For example, myoelectric potential data and electrocardiographic data from statistically 100 advanced players or professional pitchers are statistically processed to calculate ideal myoelectric potential data and electrocardiographic data. It may be myoelectric potential data and cardiac potential data from the subject.

  Further, the myoelectric potential data and the electrocardiographic data during 100 pitching operations of the same person may be acquired and used as the myoelectric potential data and the electrocardiographic data from the primary subject. For example, myoelectric potential data and electrocardiographic data from 100 pitching motions of one advanced player or professional pitcher may be acquired and used as myoelectric potential data and electrocardiographic data from the primary subject. And the secondary subject are the same person (aspiring candidate), and the myoelectric potential data and the electrocardiographic data from 100 pitching motions (for example, the pitching motion during practice) of the aspiring candidate are acquired and the secondary subject is examined. Myoelectric potential data and electrocardiographic potential data from a person, and the myoelectric potential data and electrocardiographic potential data from one pitching motion (for example, the pitching motion of the actual game) of the aspiring candidate are obtained and the myoelectric potential from the secondary subject Data and electrocardiographic data may be used. In this case, for example, a method may be considered in which a candidate who wants to improve becomes a primary subject when favorable, and becomes a secondary subject when not well (during malfunction). In addition, the myoelectric potential data and electrocardiographic data from 100 pitching motions are statistically processed to calculate ideal myoelectric potential data and electrocardiographic data, and the calculated myoelectric potential data and electrocardiographic data are used as the primary subject. The myoelectric potential data and the cardiac potential data may be used.

  As shown in FIG. 3, the state determination unit 132 includes a determination unit 132a, an exercise state and psychological state storage unit 132b, a switching unit 132c, and a comparator 132d. For example, the determiner 132a determines the exercise state and psychological state of the primary subject based on the myoelectric potential data and the electrocardiographic data from the primary subject, and the switching unit 132c receives the input from the operator (primary subject). Based on the information input instruction), the exercise state and psychological state of the primary subject are sent to the exercise state and psychological state storage unit 132b, and the exercise state and psychological state storage unit 132b transmits the exercise state and psychological state of the primary subject. Are stored as a reference motion state and a reference psychological state. Further, the determiner 132a determines the exercise state and psychological state of the secondary subject based on the myoelectric potential data and the electrocardiographic data from the secondary subject, and the switch 132c is input from the operator (secondary Based on the information input instruction from the subject), the movement state and psychological state of the secondary subject are sent to the comparator 132d. The comparator 132d compares the motion state and psychological state of the primary subject with the motion state and psychological state of the secondary subject, and outputs a comparison result (difference). For example, the movement state and psychological state of the secondary subject with respect to the movement state and psychological state of the primary subject (the state of movement and psychological state are good or bad) are output. The comparison result may include myoelectric potential data and cardiac potential data of the primary subject and the secondary subject.

  Hereinafter, with reference to FIG. 4A and FIG. 4B, the determination process of the exercise state and the determination process of the psychological state will be described separately, but these determination processes may be independent processes, The related processing may be reflected in the determination result.

  FIG. 4A is a flowchart illustrating an example of determination processing of the exercise state by the exercise state and psychological state determination device 130.

  For example, the sensing unit 131 acquires primary biological information (myoelectric potential data) from the primary subject in advance (ST11A), and the determiner 132a determines the exercise state from the primary biological information of the primary subject ( ST12A), the exercise state and psychological state storage unit 132b stores the exercise state of the primary subject (ST13A). For example, exercise status based on primary biometric information from one primary subject may be stored, or primary biometric information from multiple primary subjects may be statistically analyzed and stored as exercise status for one person. Alternatively, it may be stored as an exercise state for a plurality of persons based on primary biometric information from a plurality of primary subjects.

  Subsequently, the sensing unit 131 acquires secondary biological information (myoelectric potential data) from the secondary subject (ST14A), and the determiner 132a determines the exercise state from the secondary biological information of the secondary subject. The comparator 132d compares the exercise state from the primary subject with the exercise state from the secondary subject (ST16A), and outputs the comparison result (ST17A). For example, based on the change characteristic of the primary subject's movement state and the change characteristic of the secondary subject's movement state, the primary subject's movement state and the secondary subject's movement state are associated with each other, and the difference Is detected. Various methods can be applied to the difference detection method. The comparator 132d outputs the exercise state of the secondary subject (the exercise state is good or bad and the muscle usage is good or bad) relative to the exercise state of the primary subject. For example, the myoelectric potential data from the secondary subject during the pitching motion that is substantially the same as the myoelectric potential data from the primary subject during the pitching motion includes similar feature quantities at specific motion timings. “Specific operation timing” means the timing (time or time interval) of a specific operation event (for example, a foot lift or a ball release) in an operation (for example, a pitching operation) composed of a series of operation events. Extract feature values obtained at specific operation timings from time-series primary subject myoelectric potential data and time-series secondary subject myoelectric potential data. Based on the feature quantity extracted from the myoelectric potential data of the subject, the myoelectric potential data of the primary subject and the myoelectric potential data of the secondary subject are associated with each other to compare the myoelectric potential data and to compare the myoelectric potential data. Detection is possible.

  For example, compare the exercise status of the primary subject with the exercise status of the secondary subject, and the secondary subject's exercise status (muscle usage, etc.) relative to the exercise status of one primary subject. Can be output as a comparison result. Also, compare the primary patient's exercise status with the secondary subject's exercise status for multiple subjects, and the secondary subject's exercise status (muscle usage, etc.) for each primary subject's exercise status It is also possible to output good or bad.

  In the present embodiment, the case where the exercise state and psychological state storage unit 132b holds the exercise state serving as a reference (correct answer) has been described. However, the exercise state serving as a reference is received from a server or the like, and the received exercise state is used. You may do it.

  FIG. 4B is a flowchart illustrating an example of the determination process of the psychological state by the exercise state and psychological state determination device 130.

  For example, the sensing unit 131 acquires primary biological information (cardiac potential data) from the primary subject in advance (ST11B), and the determiner 132a determines a psychological state from the primary biological information of the primary subject ( ST12B), the exercise state and psychological state storage unit 132b stores the psychological state of the primary subject (ST13B). For example, a psychological state based on primary biometric information from one primary subject may be stored, or primary biometric information from a plurality of primary subjects is statistically analyzed and stored as a single psychological state. Alternatively, it may be stored as a psychological state for a plurality of persons based on primary biometric information from a plurality of primary subjects.

  Subsequently, the sensing unit 131 acquires secondary biological information (cardiac potential data) from the secondary subject (ST14B), and the determiner 132a determines the psychological state from the secondary biological information of the secondary subject. The comparator 132d compares the psychological state from the primary subject with the psychological state from the secondary subject (ST16B), and outputs the comparison result (ST17B). For example, the difference is detected based on the change characteristic of the psychological state of the primary subject and the change characteristic of the psychological state of the secondary subject. Various methods can be applied to the difference detection method. The comparator 132d outputs the psychological state of the secondary subject (the psychological state is good or bad) with respect to the psychological state of the primary subject.

  For example, compare the psychological state of one primary subject with the psychological state of a secondary subject, and compare the quality of the secondary subject's psychological state with respect to the psychological state of one primary subject Can be output as In addition, the psychological state of the primary subject and the psychological state of the secondary subject are compared, and the quality of the secondary subject's psychological state with respect to the psychological state of each primary subject is output. You can also

  Further, the first psychological state of the secondary subject is determined based on the electrocardiographic data acquired from the secondary subject during the predetermined exercise at the first time (5 defensives) during the game performance, The second psychological state of the secondary subject is determined based on the electrocardiographic data acquired from the secondary subject during the predetermined exercise at the second time (7 times defensive) during the game performance, and the first It is also possible to compare the psychological state of the subject and the second psychological state, and output a change in the psychological state of the secondary subject over time (for example, fatigue) as a comparison result.

  In the present embodiment, the case where the exercise state and psychological state storage unit 132b holds a psychological state serving as a reference (correct answer) has been described. However, the psychological state serving as a reference is received from a server or the like, and the received psychological state is used. You may do it.

  Next, an example of determination processing using the relationship between myoelectric potential data (exercise state) and cardiac potential data (psychological state) will be described. Excessive tension is known to inhibit smooth movement. For example, the exercise state and psychological state determination device 130 can determine whether or not the psychological state has an adverse effect on the exercise state.

  FIG. 4C is a flowchart illustrating an example of determination processing of influence on electromyogram data by electrocardiographic data in the exercise state and psychological state determination device.

  The state determination unit 132 analyzes the relationship (for example, ideal relationship) between the myoelectric potential data (exercise state) and the cardiac potential data (psychological state) of the primary subject (ST11C). Similarly, the state determination unit 132 analyzes the relationship (for example, non-ideal relationship) between the myoelectric potential data (exercise state) and the cardiac potential data (psychological state) of the secondary subject (ST12C).

  The state determination unit 132 determines the relationship between the myoelectric potential data (exercise state) and the cardiac potential data (psychological state) of the primary subject, the myoelectric potential data (motor state) and the cardiac potential data (psychological state) of the secondary subject. ) Are compared (ST13C), and the influence of the cardiac potential data (psychological state) of the secondary subject on the myoelectric potential data (motor state) is determined (ST14C). For example, it can be determined that exercise is disturbed due to tension.

  In addition, statistically, it is possible to determine that the electrocardiographic data has an influence on the myoelectric potential data by capturing the change of the myoelectric potential data according to the change of the electrocardiographic data. Further, from the relationship between the electrocardiogram data and the myoelectric potential data at this time, it is possible to detect (determine) the state in which the electrocardiographic data has an influence on the myoelectric potential data, and to output the result.

  For example, myoelectric potential data and electrocardiographic data (corresponding to the primary subject's myoelectric potential data and electrocardiographic data) during pitcher A's practice are accumulated, and the state determination unit 132 stores the accumulated muscles of pitcher A during practice. Potential data (motor status) and cardiac potential data (psychological status), myoelectric potential data (motor status) and cardiac potential data (motor status) during pitcher A's game (myopotential data and cardiac potential of secondary subjects) To the data). That is, the myoelectric potential data and electrocardiographic data (exercise state and psychological state) accumulated in the past of the same person are compared with the current myoelectric potential data and electrocardiographic data (exercise state and psychological state). When the exercise state (and psychological state) of the present (during a game) is poor with respect to the past (practice) exercise state (and psychological state), it is determined that the psychological state has an influence and the exercise state is deteriorated. That is, since the exercise state of the same person is extremely deteriorated, it is determined that the cause is the psychological state. Further, only when the time difference between the past and the present is small, it may be determined that the cause is the psychological state.

  In the above description, the case of sensing myoelectric potential data and cardiac potential data has been described. However, sensing of cardiac potential data is not essential. For example, the state determination unit 132 may determine the psychological state from the determination result of the exercise state based on the myoelectric potential data. For example, the psychological state can be statistically determined from the determination result of the exercise state. Moreover, the exercise state at the time of practice and the exercise state at the time of the game are compared, and the change in the psychological state can be determined from the comparison result. Furthermore, a change in psychological state can also be determined from a change in exercise state. For example, the change in the psychological state can be determined from the change in the exercise state in the first half of the game (first time) and the change in the exercise state in the second half of the game (second time).

  Hereinafter, the sensing unit 131 and the state determination unit 132 will be summarized. Here, not only the sensing, determination, and comparison of the psychological state, but also the sensing, determination, and comparison of the motion state will be described.

1. Sensing unit 131
The sensing unit 131 measures biological information (motion signal and psychological signal) from one or more objects. It does not matter what means the biometric information is acquired.

<Motion signal sensing>
The sensing unit 131 measures a myoelectric potential signal (biological electrode) from one or a plurality of muscles. Furthermore, the sensing unit 131 can also measure an acceleration signal (acceleration sensor), a pressure signal (pressure sensor), and a joint angle signal (bending sensor) at one or more parts.

<Psychological signal sensing>
The sensing unit 131 can also measure autonomic nerve activity in order to determine a psychological state, for example. For example, the sensing unit 131 measures a cardiac potential signal (biological electrode) and a pulse wave (photosensor). Thereby, autonomic nerve activity (excitement / relaxation) can be detected.

  The sensing unit 131 can also measure other physiological reactions. For example, the sensing unit 131 measures respiration, sweating, brain waves, eye movement, and pupil diameter. As a result, emotions (excitement / relaxation), emotions (surprise or preference), attention, intention, etc. can be detected.

  Possible measurement targets for baseball equipment include helmet, hat (electroencephalogram), sunglasses (eye movement (gaze direction, microsaccade), pupil diameter), gloves (sweat, pulse wave, pressure, acceleration), underwear (myoelectricity) , Electrocardiogram, breathing, acceleration), shoes (sweat, pulse wave, pressure, acceleration).

2. State determination unit 132
<(Exercise) determiner 132a>
The determiner 132a determines the following exercise state from the measured myoelectric potential data and the like.

  The determiner 132a determines an exercise pattern (knack or force). For example, the determiner 132a determines a muscle activity pattern for a certain movement (change in acceleration or joint angle), a mutual timing of the muscle activity, and the like.

  The determiner 132a determines a posture pattern (balance). For example, the determiner 132a determines an activity state or activity timing of a muscle combination with respect to a change in plantar pressure. For example, the determiner 132a determines the pressure change of the sole and how to use the muscles when skiing.

  The determiner 132a determines the degree of muscle fatigue. For example, the determiner 132a performs determination by performing frequency analysis on one or a plurality of myoelectric potential signals (when fatigued, the power of muscle activity shifts to a low frequency band). For example, this determination result can be used for determination at the time of a player change.

<(Motion) Comparator 132d>
The comparator 132d compares the information obtained from one or more primary subjects with the information obtained from the secondary subjects in order to determine changes in exercise status and good / bad.

  The comparator 132d compares the exercise state of the primary subject, which is a specific object, with the exercise state of the secondary subject. In advance, the determiner 132a determines the exercise state of a primary subject such as a specific advanced player or first-class player (example), and the comparator 132d determines the exercise state of the primary subject and the secondary subject. Compare the exercise state.

  The comparator 132d compares the exercise state obtained from the primary subject with a certain group with the exercise state obtained from the secondary subject. For example, the determiner 132a determines in advance a movement state (an average pattern, a pattern characterized by data mining, etc.) obtained from a certain group of primary subjects, and the comparator 132d The movement state and the movement state of the secondary subject are compared.

  Further, the comparator 132d sets itself (secondary subject) as the primary subject, and compares the exercise state of the primary subject with the exercise state of the secondary subject. The comparator 132d compares the normal (average value when throwing 100 balls in practice or the like) and the current (actual such as game) exercise state.

  Further, the comparator 132d may compare (determine) the relationship of the exercise state between the partners. For example, the determiner 132a determines the motion state (for example, the degree of strength) of the pitcher and the batter, and the comparator 132d compares the motion state of the pitcher and the batter. The comparison result can be used to judge the state of compatibility and compatibility.

<(Psychological state) determiner 132a>
The determiner 132a determines an autonomic state (balance of sympathetic and parasympathetic activity = tension / relaxation) by frequency analysis of heart rate and blood flow fluctuation (fluctuation) obtained from an electrocardiogram signal or a pulse wave. (For example, Non-Patent Document 5). To quantify tension / relaxation, for example, calculate the low frequency component (LF: 0.05-0.15 Hz) and the high frequency component (HF: 0.15-0.4 Hz) of the heart rate variability. LF / HF can be evaluated as tension.

In addition, the determiner 132a can also determine the state of emotion (excitement / relaxation), emotion (surprise / preference), attention, intention, etc. based on breathing, sweating, brain waves, eye movement, pupil diameter, etc. ) Comparator 132d>
The comparator 132d compares information obtained from one or a plurality of primary subjects with information obtained from the secondary subjects in order to determine changes in psychological state and good / bad.

  The comparator 132d compares the autonomic state obtained from the primary subject with a certain group with the autonomic state obtained from the secondary subject. For example, the determiner 132a determines in advance an autonomic state (average value, a value characterized by data mining, etc.) obtained from a group of primary subjects, and the comparator 132d The autonomic state of the subject and the autonomic state of the secondary subject are compared.

  The comparator 132d sets itself (secondary subject) as the primary subject, and compares the autonomic state of the primary subject with the autonomic state of the secondary subject. The comparator 132d compares the autonomic nerve state in the first situation (usually during practice, for example) and the autonomic nerve state in the second situation (currently, for example, during a game).

  The comparator 132d compares (determines) the psychological relationship between partners. For example, the determiner 132a determines the psychological state of the pitcher and the batter, and the comparator 132d compares the psychological state of the pitcher and the batter. The comparison result can be used to judge the state of compatibility and compatibility.

<(Exercise state and psychological state) comparator 132d>
The comparator 132d compares (determines) “relationship between the autonomic nerve state and the motor state” by combining the motor state and the autonomic nerve state. For example, if you are nervous, you can see the relationship that exercise is disturbed.

  Next, the determination of the motion state and the state of the autonomic nerve will be described in detail.

  As Example 1, we will explain the comprehensive monitoring of professional pitchers in actual battles.

  1. The pitcher A wears compression inner wear (for example, Hitoe (registered trademark)) equipped with a myoelectric potential sensor 110 (wearable sensor) on both upper and lower body. A compression inner wear (for example, Hitoe (registered trademark)) equipped with an electrocardiographic sensor 120 (wearable sensor) is worn on the upper body. In order to measure the myoelectric potential, the myoelectric sensor 110 is arranged in a plurality of locations corresponding to the wearer's arm, shoulder, chest circumference, and waist, for example. In order to measure the electrocardiogram in the upper body wear, for example, electrocardiogram sensors 120 are arranged at a plurality of locations (for example, 3 locations) corresponding to the wearer's heart. The lower body wear includes muscles at multiple locations corresponding to the wearer's buttocks to measure the myoelectric potential of the wearer's buttocks (or other muscles of the lower limbs) in order to measure the fatigue of the lower body. A potential sensor 110 is disposed.

  2. The state determination unit 132 can estimate the degree of muscle fatigue by frequency analysis of the myoelectric potentials of the upper and lower bodies. On the other hand, the state determination unit 132 can estimate the activity balance between the pitcher's sympathetic nerve and the parasympathetic nerve from the analysis of the heart rate variability based on the electrocardiogram.

  3. The myoelectric sensor 110, the electrocardiographic sensor 120, and the sensing unit 131 continuously measure the myoelectric potential and the electrocardiographic potential of the pitcher A from usual practice and games, and long-term data in various situations as listed below. To save.

3.1 Unpractical situation where batter is not standing in bullpen 3.2 Situation where a batter is played (practice)
3.3 Situation where a batter is played (match)
The following data acquired from the above situation is input to the state determination unit 132 that functions as a biological state estimator. The state determination unit 132 sequentially updates a model for estimating the latest future pitching performance with “3.1”, “3.2”, and “3.3” as inputs.

3.4.1 Objective muscle fatigue estimated from myoelectric potential 3.4.2 Motor chain efficiency estimated from whole body muscle activity pattern 3.4.2 Autonomic nervous activity balance estimated from heart rate variability 3 4.4 Performance indicators such as pitching speed, control variation, etc. <User use example 1: Assuming actual battle scenes>
The information in the above 3.4.1 to 3.4.4 is in a state where the secondary subject (the person whose data is being measured) and surrounding people can be monitored at all times. That is, the feedback device 140 outputs the information of the above 3.4.1 to 3.4.4.

  4). First half of the game: One of the challenges for pitcher A is that the performance immediately after the start of the game (rise) is unstable. From long-term data measurements, it is known that the mental state estimated from the electrocardiogram frequently falls into an overstress state. In addition, it has been found that there is a correlation between overstressing and a decrease in throwing performance. For this reason, when such a situation occurs during the match, the pitcher coach rarely disturbs the performance by taking action such as “getting a gap”.

  5. Mid game: When fatigue is increased, it is inferred from the monitored EMG data, but the muscle state inferred from muscle activity is inferior (for example, accumulation of fatigue) The leaders decide to continue.

  6). The second half of the game: If both the muscle fatigue and mental aspects of the condition are estimated to be degraded, and the muscle activity pattern throughout the body also shows a pattern specific to fatigue, the pitcher A must be released before being struck by the batter. Make a decision.

7). The use as described above not only makes it possible to change the player at a better timing, but also reduces the risk of injury due to a reduction in the chance of being forced. <User use case 2: Overcoming challenges in the game through practice>
8). Pitcher A has the problem of not being able to demonstrate the performance as usual in the game (although it may be influenced by mental), the surrounding people speculate that there may be a physical cause )

  9. In order to overcome the above problems, the muscle activity pattern of the whole body, the autonomic nerve activity balance, and the pitching performance index at the time of pitching in each of the preceding items 3.1 to 3.3 are compared.

  10. As a result, pitcher A is throwing in a very relaxed state only when throwing with a bullpen, and it is found that there is a great change in the mental aspect in a battle scene with a batter, particularly in a battle scene in a game. Furthermore, it is possible to pick up game situations that cause mental variations.

  11. Pitcher A receives the feedback of “10.” and discusses with the leader how to deal with the situation of the game (organization of the situation, how to hold feelings, etc.). Furthermore, in practice, it can be expected that the instability of performance at the time of the game will be improved by performing actual battle practice that reproduces the situation.

  As example 2, heart rate variability analysis as prevention of overtraining will be described.

  12 The young baseball player A (pitcher) must perform high-intensity training in parallel with many matches during the season. If you want to play a game with accumulated fatigue, you will not only be able to perform well, but also increase the risk of injury. Therefore, a mechanism that fluidly determines whether or not to climb the day can be useful by monitoring the condition of the player on the day.

  13. Overtraining syndrome is detected from heart rate variability data obtained from electrocardiograms when waking up.

  The young baseball player A continuously collects heart rate variability and myoelectric potential data by measuring the electrocardiogram and the myoelectric potential on a daily basis from the time of getting up. It has been reported that athletes who fall into overtraining have increased heart rate and decreased heart rate variability when waking up. It has also been reported that the degree of muscle fatigue estimated from myoelectric potential is related to the degree of fatigue estimated from heart rate variability. Together with these and the subjective fatigue level of the person, the conditioning coach determines whether or not pitcher A can climb on the morning of the day.

  At the same time, it is determined that pitcher B, which is estimated to be in the best condition in the same measurement, is to be pitched in place of young baseball player A.

  Hereinafter, an example of acquiring myoelectric potential signals and acceleration signals from the primary subject and the secondary subject will be described with reference to FIGS. In the above description, the myoelectric potential signal has been mainly described as an example of the body information, but the body information is not limited to the myoelectric potential signal but may include an acceleration signal. Here, an example of presentation of physical information including an electromyogram signal and an acceleration signal (an example of a physical information presentation device) will be described. The feedback system for improving exercise shown in FIG. 1 may be configured to include the physical information presentation device described here. The myoelectric potential electrode A shown in FIG. 5 corresponds to the myoelectric potential sensor 110 shown in FIG.

  As shown in FIG. 5, the body information presentation device includes a myoelectric potential signal storage unit 1, a myoelectric potential signal generation unit 2, a myoelectric potential signal storage unit 3, an acceleration electrical signal storage unit 4, an acceleration signal generation unit 5, and an acceleration signal storage. For example, a unit 6 and a modulation unit 10 are provided. The modulation unit 10 includes, for example, a modulation signal generation unit 7 and a wave signal modulation unit 8. The physical condition presentation method is realized by the physical information presentation device performing the processing from step S1 to step S5 in FIG.

  Assume that the myoelectric potential electrode A is attached to a muscle that plays a major role in the body movement in a desired exercise task, and the acceleration sensor B is attached to a body part on which the muscle acts. In FIG. 5, the myoelectric potential electrode A is attached to the upper arm, and the acceleration sensor B is attached to the hand.

  FIG. 7 shows an example of an attachment site of the myoelectric potential electrode A and the acceleration sensor B suitable for each task for some basic motor tasks. When the exercise task is wrist flexion, the myoelectric potential electrode A is attached to the carpal flexor and the acceleration sensor B is attached to the back of the hand. When the exercise task is wrist extension, the myoelectric potential electrode A is attached to the wrist extensor muscle, and the acceleration sensor B is attached to the back of the hand. When the exercise task is prorotation of the forearm, the myoelectric potential electrode A is attached to the supination muscle, and the acceleration sensor B is attached to the back of the hand or the wrist. When the exercise task is pronation of the forearm, the myoelectric potential electrode A is attached to the pronation muscle, and the acceleration sensor B is attached to the back of the hand or the wrist. When the exercise task is plantar flexion, the myoelectric potential electrode A is attached to the gastrocnemius or soleus, and the acceleration sensor B is attached to the instep of the foot. When the exercise task is dorsiflexion of the foot, the myoelectric potential electrode A is attached to the anterior tibial muscle and attached to the instep of the foot.

A myoelectric potential signal x _A (t), which is an electrical signal acquired from the myoelectric potential electrode A, is sampled at a predetermined sampling period T and stored in the myoelectric potential signal storage unit 1. The electromyogram signal storage unit 1, the sample values of the latest N _A number of myoelectric potential signal is stored. _A sample value series of the latest N _A myoelectric potential signals is expressed as x _A ^m (n) (0 ≦ n <N _A ). Each time a new M-number of sampled values from the myoelectric signal x _{A (t)} is generated, for example, the latest N sample values series _A number of electromyogram ^{_{x A m (n) (0}} ≦ n as follows <N _A ) is updated. However, the M <N _A.

Electromyogram signal generating unit 2 generates a is a signal representative of the activity level of muscle to be measured myoelectric potential signal _PA ^m (step S1). The generated myoelectric potential signal is stored in the myoelectric potential signal storage unit 3.

Electromyogram signal generating unit 2 is, for example, every time the sample value of the M new myoelectric potential signal is obtained, read from myoelectric signal storage unit 1 latest N sample values series _A number of electromyogram x _A with ^{m (n) (0 ≦ n} <n a), to calculate the amplitude of the electromyogram signal. The amplitude of the myoelectric potential signal is an example of the myoelectric potential signals _PA ^m is a signal representative of the activity level of muscle to be measured. For this reason, the amplitude of the myoelectric potential signal is also expressed as _PA ^m .

The myoelectric signal amplitude _PA ^m may be an average absolute amplitude that is an average of absolute values of the myoelectric signal defined by the equation (1), or the myoelectric signal defined by the equation (2). It may be the maximum absolute amplitude that is the maximum absolute value, or the mean square amplitude that is the geometric mean of the myoelectric potential signal defined by Equation (3).

The electromyogram signal storage unit 3, the latest M _A number of electromyogram _PA ^m is stored. The latest M _A number of myoelectric potential signals stored in the myoelectric potential signal storage unit 3 denoted as _{PA (m) (0 ≦ m} <M A). Each time a new myoelectric potential signal _PA ^m are generated, latest M _A number of electromyogram _PA, for example, as follows _{(m) (0 ≦ m <} M A) is updated.

The acceleration electrical signal x _B (t), which is an electrical signal acquired from the acceleration sensor B, is sampled at a predetermined sampling period T and stored in the acceleration electrical signal storage unit 4. The acceleration electric signal storage unit 4, sample values of the latest N _B number of the acceleration electric signal is stored. The sample value sequence of the latest N _B number of the acceleration electric signal is denoted as ^{_{x B m (n) (0}} ≦ n <N B). Each time a new M-number of sampled values from the myoelectric potential signal x _{B (t)} is generated, for example, the latest sample value series N _B number of myoelectric potential signals ^{_{x B m (n) (0}} ≦ as follows n <N _B ) Updated. However, M <N _B.

  The acceleration signal generation unit 5 generates an acceleration signal that is a signal representing the kinematic state of the body part on which the muscle to be measured acts (step S2). The generated acceleration signal is stored in the acceleration signal storage unit 6.

Acceleration signal generator 5, for example, every time the sample value of the M new acceleration electric signal is obtained, the sample value series of the latest N _B number of acceleration electric signal read from the acceleration electric signal storage unit 4 x _B ^m (n) The amplitude of the acceleration signal is calculated using (0 ≦ n <N _B ). The amplitude of the acceleration signal, the muscle to be measured is an example of the acceleration signal _PB ^m is a signal representative of the kinetic state of the body part to act. For this reason, the amplitude of the acceleration signal is also expressed as _PB ^m .

The amplitude _PB ^m of the acceleration signal may be an average absolute amplitude that is an average of the absolute values of the acceleration electrical signal defined by the equation (4), or may be an absolute value of the acceleration electrical signal defined by the equation (5). It may be the maximum absolute amplitude that is the maximum value, or the mean square amplitude that is the geometric mean of the acceleration electrical signal defined by Equation (6).

The electromyogram signal storage unit 3, the latest M _B-number of the myoelectric potential signal _PB are stored. The latest M _B-number of the myoelectric potential signal stored in the myoelectric potential signal storage unit 3 denoted as _{PB (m) (0 ≦ m} <M B). Each time a new myoelectric potential signal _PB ^m is produced, for example, the following manner latest M _B number of electromyogram _{PB (m) (0 ≦ m} <M B) is updated.

  The modulation unit 10 modulates a predetermined wave signal based on the relationship between the myoelectric potential signal and the acceleration signal (step S5). The process of the modulation unit 10 is realized by the process of step S3 by the modulation signal generation unit 7 and the process of step S4 by the wave signal modulation unit 8. Hereinafter, these processes will be described.

  The modulation signal generation unit 7 generates a modulation signal obtained by modulating the myoelectric potential signal with the acceleration signal (step S3). The generated modulation signal is output to the wave signal modulation unit 8.

Modulation signal generator 7, for example, read from the electromyogram signal storage unit 3 latest M _A number of electromyogram _{PA (m) (0 ≦ m} <M A) the most recent read from and the acceleration signal storage section 6 with M _B number of acceleration signal _{PB (m) (0 ≦ m} <M B), to generate a modulated signal _PC ^m which is defined by the following equation. M _A and M _B are integers of 1 or more. M _A and M _B may be particularly 1. _PA (m) ^rep is a representative value of the myoelectric signal _PA (m) (0 ≦ m <M _A ), and _PB (m) ^rep is a representative value of the acceleration signal _PB (m) (0 ≦ m <M _B ). It is.

In the equation above, although the _PA to _(m) ^rep and averaging the M _A number of electromyogram _{PA (m) (0 ≦ m} <M A), PA (m) rep is M _A number of electromyogram Other values may be used as long as they represent _PA (m) (0 ≦ m <M _A ). For example, _{PA (m)} ^rep is, M _A number of electromyogram _{PA (m) (0 ≦ m} <M A) may be a geometric mean of, M _A number of electromyogram _{PA (m)} ( The maximum value may be 0 ≦ m <M _A ).

Similarly, in the formula above, _PB and _(m) ^rep is the arithmetic mean of M _B-number of the acceleration signal _{PB (m) (0 ≦ m} <M B), PB (m) rep is M _B number of acceleration Other values may be used as long as they represent the signal _PB (m) (0 ≦ m <M _B ). For example, _{PB (m)} ^rep may be the geometric mean of M _B-number of the acceleration signal _{PB (m) (0 ≦ m} <M B), M B -number of the acceleration signal _{PB (m) (0} ≦ It may be the maximum value of m <M _B ).

The function f may be a function f1 that is monotonically non-decreasing for each of (1) _PA (m) ^rep and _PB (m) ^rep , or (2) is monotonically non-decreasing for _PA (m) ^rep. _It may be a function f2 that is monotonically non-increasing with respect to _PB (m) ^rep . The case of (1) is called method (1), and the case of (2) is called method (2). The merits of the method (1) and the method (2) will be described later. Examples of functions f1 and f2 are given below.

When the function f2 exemplified above is used as the function f, when _PB (m) ^rep = 0, _PC ^m = 0. Thereby, it is possible to avoid the problem that the value of _PC ^m is not determined due to the denominator becoming zero.

  As described above, the modulation signal generation unit 7 generates the modulation signal by calculating the output value when the representative value of the myoelectric signal and the representative value of the acceleration signal are input to the predetermined function f, for example.

The wave signal modulation unit 8 modulates a predetermined wave signal based on the modulation signal _PC ^m (step S4). The modulated wave signal is presented to the actor and observer. The wave signal modulator 8 may be a sound source signal modulator that modulates a predetermined sound source signal g (t), an optical signal modulator that modulates a predetermined optical signal, or a predetermined color. It may be a color signal modulation unit that modulates a signal. You may visualize by what is called a heat map (amplitude modulation), a spectrogram (frequency modulation), etc.

When the wave signal modulation unit 8 is a sound source signal modulation unit, the wave signal modulation unit 8 performs, for example, amplitude modulation or frequency modulation on the sound source signal g (t) on the basis of the modulation signal _PC ^m to generate an acoustic signal s ( t).

  Amplitude modulation is performed by the following equation, for example. D is a predetermined gain for determining the degree of the modulation effect. When amplitude modulation is performed, the sound source signal g (t) may be any signal.

  On the other hand, frequency modulation is performed by the following formula, for example. Gk means the amplitude of the kth harmonic. D is a predetermined gain for determining the degree of the modulation effect.

  In the case of performing frequency modulation, the sound source signal g (t) is a composite sine wave having a predetermined fundamental frequency f and an integer multiple thereof defined by the following equation, for example.

When the wave signal modulation unit 8 is an optical signal modulation unit, the wave signal modulation unit 8 performs amplitude modulation or frequency modulation on a predetermined signal based on the modulation signal _PC ^m .

When the amplitude modulation is performed, the wave signal modulator 8 modulates based luminance of a predetermined luminance of the light signal to the modulation signal _PC ^m. Thereby, the brightness of the light displayed on the LED or the display can be changed.

  When frequency modulation is performed, the wave signal modulation unit 8 modulates the frequency of an optical signal having a predetermined frequency based on the modulation signal. Thereby, the color of the light displayed on the LED or the display can be changed.

  In the case where the wave signal modulation unit 8 is a sound source signal modulation unit, when the method (1) is used, the acoustic signal changes and exercises only in a time interval in which the movement of the body part changes with the exertion of muscle strength. The state of muscular strength without change is not reflected in the change of the acoustic signal. Therefore, the method (1) is effective for grasping at what timing and with which strength the muscle activity directly related to the unit movement most important in the task has occurred.

  On the other hand, when the wave signal modulation unit 8 is a sound source signal modulation unit and the method (2) is used, in the method 2, the muscular strength exerted state without the motion change is reflected in the acoustic signal change, and the motion changes. The acoustic signal does not change during the time interval. Therefore, the method (2) is effective in grasping whether or not an excessive “force” state is generated in a task that should perform a smooth continuous motion with a minimum muscle activity.

  Moreover, the wave signal modulation | alteration part 8 may show a body information to an actor and an observer as visual information. In this case, the wave signal modulation unit 8 changes the visual information that reflects only the muscle activity directly related to the important motion in the exercise task (when the method (1) is used) and unnecessary force in the exercise task. Any of visual information changes reflecting only the state (when using method (2)) may be selectively presented to the actor or the observer.

  When the muscle activity level is directly reflected in the visual information, the presentation information changes even when the muscle is in an unnecessary force state during a series of physical movements and when the muscle strength is accurately demonstrated. Therefore, as the movement becomes faster and more complicated, the variation in the visual information presented increases, and it may become difficult to grasp how much each muscle has acted at what timing. This difficulty can be avoided by selectively presenting visual information as described above.

  In order to master tasks that are particularly difficult, it is required to reduce the excessive force state as much as possible and to exert muscular strength with appropriate timing and strength at the same time. By using such a body state presentation apparatus and method, the muscular strength exerted state in the body motion in the desired task can be accurately grasped in real time while the actor himself performs the task.

[Variations]
There is a time delay (electrodynamic delay) of less than about 100 milliseconds between the start time of the muscle activity observed with the myoelectric potential and the start time of the mechanical movement of the body part due to the activity. Therefore, a time shift corresponding to this electrodynamic delay is included between the myoelectric potential signal _PA (m) and the acceleration signal _PB (m). Therefore, _PC ^m may be calculated by shifting one of _PA (m) ^rep and acceleration signal _PA (m) ^rep by the time corresponding to the electrodynamic delay.

For example, _PA (m) ^rep delayed by the time corresponding to the electrodynamic delay is set as _PA (m) ^{rep + Δ} , and the modulation signal _PC ^m defined by the following equation is calculated. Specifically, _PA (m) ^{rep + Δ} is the _PA (m) ^{rep at} a time delayed by a discrete time Δ ′ / MT from the time of _PA (m) ^rep , where Δ ′ is the electrodynamic delay. is there.

Further, as the amount corresponding earlier was _{PB (m)} ^rep of time corresponding to the electrical time dynamic delay _{PB (m) ^rep-Δ,} may be calculated modulated signal _PC ^m which is defined by the following equation. _{PB (m)} ^rep-Δ, specifically, that the electrodynamic delay delta 'to the _{PB (m)} ^rep discrete-time from the time of delta' / MT only definitive early time _{PB (m)} ^rep It is.

  In the above embodiment, when the wave signal modulation unit 8 is a sound source signal modulation unit, one type of sound source is controlled using signals from one myoelectric potential electrode and one acceleration sensor. On the other hand, when there are muscles that are important for a desired task in multiple parts, one electrode is attached to each of those muscles, and one acceleration sensor is attached to the body part where each muscle acts. One sound source controlled by each myoelectric potential signal and acceleration signal may be assigned one by one. However, the individual sound sources are different types of sound sources that are audibly distinguishable from each other. Moreover, it is good also as a structure which shares an acceleration sensor regarding the muscle with which the body part which acts acts among several muscles. Moreover, it is good also as a structure which allocates one sound source controlled by the combination of a some muscle and some acceleration.

  As a means for acquiring the kinematic state of the body part, in addition to using the acceleration sensor B, a gyro sensor, an inclinometer, a geomagnetometer, or the like can be used. Or, using a device such as a video camera that acquires video in real time and an image processing arithmetic device that estimates the spatial position of a specific part of the body from the acquired video, the displacement, speed, acceleration, etc. of the desired body part Information may be acquired.

  The physical condition presentation device may include a differential dispersion modulation signal generation unit 9 indicated by a broken line in FIG.

Difference variance modulation signal generator 9, for example, and has a time-series data of the modulation signal ^ _PC ^m to be compared. The modulation signal ^ _PC ^m to be compared is generated in advance based on an example motion for a predetermined motion task. The differential dispersion modulation signal generation unit 9 calculates a difference Δ _PC ^m between _PC ^m and ^ _PC ^m generated by the modulation signal generation unit 7 and outputs the calculated difference Δ _PC ^m to the wave signal modulation unit 8. The wave signal modulation unit 8 modulates a predetermined wave signal in the same manner as described above based on the difference Δ _PC ^m . In this way, by presenting the physical state based on the difference Δ _PC ^{m from the} modulation signal ^ _PC ^m to be compared, the actor can determine the difference between the exemplary exercise and his own movement, in other words, You can effectively perceive how close your movement is to the exemplary movement.

Further, difference variance modulation signal generating unit 9 may store the modulated signal _PC ^m modulated signal generator 7 is generated so far, the variance of the modulation signal _PC ^m each time a new modulation signal _PC ^m is generated σ _PC ^m may be calculated, and the calculated dispersion σ _PC ^m may be output to the wave signal modulator 8. The wave signal modulation unit 8 modulates a predetermined wave signal in the same manner as described above based on the dispersion σ _PC ^m . In this way, by presenting the physical state based on the variance σ _PC ^m , the actor effectively perceives how much his movement has been reproduced, in other words, the magnitude of his movement blur. can do.

  The processes described in the apparatus and method are not only executed in chronological order according to the order of description, but may be executed in parallel or individually according to the processing capability of the apparatus that executes the processes or as necessary.

  Note that the above-described processing procedures such as determination and comparison can be executed by software. For this reason, the said process can be easily implement | achieved only by downloading the program which performs the procedure of the said process, installing this program in mobile terminals, such as a normal computer and a smart phone. Alternatively, the program can be transferred to a general-purpose computer or a mobile terminal such as a smartphone through a computer-readable storage medium storing a program for executing the above-described processing procedure, such as a magnetic recording device, an optical disk, a magneto-optical recording medium, or a semiconductor memory. The above processing can be easily realized simply by installing and executing.

  For example, the exercise state and psychological state determination device 130 can download the program, store the downloaded program, and complete the installation of the program. Further, the exercise state and psychological state determination device 130 can read the program from a computer-readable storage medium, store the read program, and complete the installation of the program. Thereby, the exercise state and psychological state determination apparatus 130 can easily realize the above processing based on the installed program.

  The present invention is not limited to the above embodiment. For example, biometric information from a plurality of primary subjects may be collected by a network server or the like, biometric information from a plurality of primary subjects may be analyzed, and a reference exercise state may be generated and distributed. . The exercise state and psychological state determination device 130 receives the exercise state serving as a reference to be distributed, compares the received exercise state with the exercise state of the secondary subject, and determines the exercise state of the secondary subject. can do.

  In addition, various modifications can be made without departing from the scope of the present invention.

  In short, the present invention is not limited to the above-described embodiment as it is, and can be embodied by modifying the constituent elements without departing from the scope of the invention in the implementation stage. Further, various inventions can be formed by appropriately combining a plurality of constituent elements disclosed in the embodiment. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, you may combine suitably the component covering different embodiment.

DESCRIPTION OF SYMBOLS 100 ... Feedback system 110 for exercise improvement ... Myoelectric potential sensor 120 ... Electrocardiographic sensor 130 ... Exercise state and psychological state determination device 131 ... Sensing unit 132 ... State determination unit 140 ... Feedback device 132a ... Determinator 132b ... Exercise state Psychological state storage unit 132c ... switch 132d ... comparator

Claims (3)

Determining or storing the exercise state and psychological state of the primary subject based at least on primary biometric information including myoelectric potential data and electrocardiographic data acquired from the primary subject during predetermined exercise; Determining or storing the motor and psychological state of the secondary subject based at least on secondary biometric information including myoelectric potential data and electrocardiographic data acquired from the secondary subject;
Comparing the movement state and psychological state of the primary subject with the movement state and psychological state of the secondary subject, and a method for determining the state of movement and psychological state, which outputs a comparison result,
The primary psychological state of the primary subject is determined based on electrocardiographic data corresponding to a first time in the primary biological information, and the secondary psychological state of the secondary subject is The first psychological state is compared with the second psychological state as determined based on electrocardiographic data corresponding to the second time among the secondary biological information, and the first psychological state A change in the psychological state of the secondary subject with reference to
Further, the relationship between the myoelectric potential data and the electrocardiographic data included in the primary biological information corresponding to the time interval before the first time, and the second corresponding to the time interval before the second time. Comparing the relationship between the myoelectric potential data and the electrocardiographic data included in the next biological information, and determining the influence on the exercise state by the psychological state of the secondary subject during the predetermined exercise,
Furthermore, an exercise state and psychological state determination method for determining a cause of a change in an exercise state based on a difference between myoelectric potential data corresponding to the first and second times. The exercise state and psychological state determination device has a state determination unit,
The state determination unit
Determining or storing the exercise state and psychological state of the primary subject based at least on primary biometric information including myoelectric potential data and electrocardiographic data acquired from the primary subject during predetermined exercise; Determining or storing the motor and psychological state of the secondary subject based at least on secondary biometric information including myoelectric potential data and electrocardiographic data acquired from the secondary subject;
Compare the primary subject's exercise state and psychological state and the secondary subject's exercise state and psychological state, and output a comparison result,
Furthermore, the state determination unit
The primary psychological state of the primary subject is determined based on electrocardiographic data corresponding to a first time in the primary biological information, and the secondary psychological state of the secondary subject is The first psychological state is compared with the second psychological state as determined based on electrocardiographic data corresponding to the second time among the secondary biological information, and the first psychological state A change in the psychological state of the secondary subject with reference to
Further, the relationship between the myoelectric potential data and the electrocardiographic data included in the primary biological information corresponding to the time interval before the first time, and the second corresponding to the time interval before the second time. Comparing the relationship between the myoelectric potential data and the electrocardiographic data included in the next biological information, and determining the influence on the exercise state by the psychological state of the secondary subject during the predetermined exercise,
Furthermore, an exercise state and psychological state determination device characterized in that the cause of a change in exercise state is determined based on a difference between myoelectric potential data corresponding to the first and second times. An exercise state and psychological state determination program for causing a computer to execute the exercise state and psychological state determination method according to claim 1.