JP6692019B2 - Exercise support device and exercise support method - Google Patents

Description

  The present invention relates to an exercise support device and an exercise support method that mainly support the movement of an athlete (athlete) for archery competitions.

  In recent years, wearable devices equipped with sensors such as an electrocardiograph and an accelerometer and a wireless communication function have been released due to downsizing and cost reduction of sensors, and are used in various applications including sports (for example, Non-Patent Document 1).

  A specific sport is archery competition. In archery competitions, stable shooting is required. For stable shooting, features such as heartbeat variability, posture stability, and respiration, which are obtained from electrocardiogram / RRI (heartbeat variability time series data), have been paid attention to. The characteristic amount is measured (for example, see Non-Patent Document 2).

  FIG. 20 shows the configuration of the main part of the wearable device shown in Patent Document 2. In the wearable device shown in Non-Patent Document 2, each characteristic amount is measured by a different sensor. In FIG. 20, 11 (11-1 to 11-3) are sensor terminals, and 12 is a child terminal that receives sensor data from the sensor terminals 11 (11-1 to 11-3).

  The sensor terminal 11-1 measures the cardiac potential as the bioelectric potential of the athlete (exercise person) by the voltage sensor 13, and sends the measured cardiac potential to the child terminal 12 as sensor data. The sensor terminal 11-2 measures the floor reaction force generated with the movement of the athlete by the floor reaction force meter (force plate) 14, and sends the measured floor reaction force to the child terminal 12 as sensor data. The sensor terminal 11-3 is provided with a thermometer (thermistor) installed on the nose of the athlete and a sensor 15 such as a belt for measuring the fluctuation of the chest as the inductance change by expanding and contracting the coil. The obtained sensor data is sent to the child terminal 12.

  The child terminal 12 includes a storage unit 12-1 and an analysis unit 12-2. The sensor data from the sensor terminals 11-1 to 11-3 is stored in the storage unit 12-1 of the child terminal 12. The analysis unit 12-2 obtains a characteristic amount such as heartbeat fluctuation, posture stability, and respiration based on the sensor data stored in the storage unit 12-1. In this case, the heartbeat variability (electrocardiogram / RRI) is obtained based on the sensor data from the sensor terminal 11-1, the posture stability is obtained based on the sensor data from the sensor terminal 11-2, and the respiration is the sensor terminal. 11-3 is obtained based on the sensor data.

Takayuki Ogasawara, Kazuyoshi Ono, Nobuaki Matsu, Masumi Yamaguchi, Atsushi Watanabe, Shingo Tsukada: Application development of wearable electrode inner technology, NTT Technology Journal, November 2014 issue Watanabe, K., Iwamoto, Y., Takamatsu, J., Kubo, J., Hashimoto, E., Takai H., Yokozawa S., Mimura S., Araki M .: Aiming ability of top archery players. (Special feature: Science of targeted competition), Biomechanics research, 11 (1): 54-65, 2007. “ECG Implementation on the TMS320C5515 DSP Medical Development Kit (MDK) with the ADS1298 ECG-FE” (http://www.ti.com/lit/an/sprabj1/sprabj1.pdf) Takayuki Ogasawara, Nobuaki Matsuura, Kei Kuwahara, Takuro Tajima, Hiroshi Koizumi, Ryoichi Kasahara: Estimating Respiration by Cardiac Potential Measured by Shirt Type Electrocardiographic Sensor, 2016 IEICE General Conference Proceeding, March 2016 Analog Devices, Inc., “AN-1057 Application Note”, 2010 Tomohisa Hamada: Statistics for Society / Paper Presentation, Shinko Trading Co., Ltd., Medical Book Publishing, 2012 Atsushi Mizumoto, Osamu Takeuchi: For reporting effect sizes in research papers-Basic concepts and points of caution-, English Education Research, 31, 57-66, 2008

  However, when a plurality of different sensors such as a voltage sensor, a floor reaction force meter, a temperature sensor, and a belt are used like the wearable device shown in Non-Patent Document 2, the number of sensor types increases, resulting in high cost. There was a problem that caused it.

  In addition, there are other problems, and since the floor reaction force meter has a corresponding size because it carries a human body, it is inconvenient to carry. Also, since it is installed on the floor and used, it cannot be used when it affects the installation environment or when fixing is not allowed.

  Further, the thermometer installed on the nose interferes with the anchoring operation of bringing the bowstring closer to the face. The belt, which measures the chest movement from expansion and contraction, tightens the chest, which physically and mentally imposes a burden on the competition.

  The present invention has been made to solve such a problem, and an object thereof is to reduce the number of sensors, which enables cost reduction, and facilitates portability. An object of the present invention is to provide an exercise support device and an exercise support method capable of reducing the physical and mental burden on an exerciser.

In order to achieve such an object, the present invention is an exercise support device (100) for supporting movement of an exerciser, comprising: a voltage sensor for measuring a cardiac potential as a bioelectric potential of the exerciser; An acceleration sensor that measures accelerations of three axes orthogonal to each other in the chest, the back, and the arch held by the exerciser, and a child terminal that receives the cardiac potential measured by the voltage sensor and the acceleration measured by the acceleration sensor as inputs. The heartbeat interval / respiratory waveform calculating means for calculating at least the heartbeat interval and the respiratory waveform from the cardiac potential measured by the voltage sensor, the child terminal, and the acceleration measured by the acceleration sensor and the acceleration sensor and attitude calculation means for calculating an attitude of the exerciser from the axis of tilt, the movement from the position calculated by the posture calculation means The event detection means for detecting the release timing when the arrow is shot as an event, the release timing detected by the event detection means and the release timing immediately before the release timing included in the cardiac potential measured by the voltage sensor. And an event execution time feature quantity calculating means for calculating a time difference from the generation timing of the R wave as a feature quantity when the exerciser executes the event .

Incidentally, the calculated posture of the exerciser from the acceleration measured by the acceleration sensor (4-1 to 4-3), the heart rate interval (RRI) and respiratory waveform from biopotentials measured by a voltage sensor (3-1) Is calculated. As a result, according to the present invention, it becomes possible to obtain the stability of the posture as the feature amount of the exerciser without using the floor reaction force meter. Further, it becomes possible to obtain respiration as a feature amount of an exerciser without using a thermometer or a belt.

Note that to calculate the posture of the exerciser from the acceleration measured by the acceleration sensor (4-1 to 4-3), the type of specific operation of the exerciser from the calculated posture detected as an event, is the detection The feature amount at the time of executing the event of the exerciser may be calculated from the event and the biopotential measured by the voltage sensor (3-1). For example, in the case of supporting the movement of the athlete for archery competition, the posture of the athlete is calculated from the acceleration measured by the acceleration sensor (4-1 to 4-3), and the posture of the athlete is calculated from the calculated posture. The timing of the release when the arrow is shot (the timing at which the string moves away from the hand pulling the string) is detected as an event, and the time difference between the detected release timing and the immediately preceding R wave generation timing (the difference between the R wave and the release generation time ) Is calculated as the feature amount of the athlete during the execution of the event. It is possible to infer what kind of influence the generation of the R wave has on the release operation from the characteristic amount (the difference in the generation times of the R wave and the release) during the execution of this event.

  In this way, according to the present invention, only the voltage sensor (3-1) and the acceleration sensor (4-1 to 4-3) are used to detect heart rate variability (electrocardiogram / RRI), posture stability, exercise of breathers and the like. It is possible to obtain the feature amount, reduce the number of sensors, and achieve cost reduction. In addition, it is easy to carry and it is possible to reduce the physical and mental burden on the exerciser.

  In the above description, as an example, the constituent elements in the drawings corresponding to the constituent elements of the invention are indicated by reference numerals in parentheses. Further, in the present invention, a gyro sensor may be provided instead of the acceleration sensor.

  As described above, according to the present invention, it is possible to obtain a feature amount of an exerciser such as heart rate variability (electrocardiogram / RRI), posture stability, and breathing only with a voltage sensor and an acceleration sensor (or a gyro sensor). Therefore, the number of sensors can be reduced and the cost can be reduced. In addition, it is easy to carry and it is possible to reduce the physical and mental burden on the exerciser.

FIG. 1 is a diagram showing a main part of an exercise support device according to a first embodiment of the present invention. FIG. 2 is a diagram showing an installation situation of sensor terminals in the exercise support device according to the first embodiment. FIG. 3 is a diagram showing a cardiac potential and an RRI waveform calculated from the cardiac potential. FIG. 4 is a diagram showing a cardiac potential and a respiratory waveform calculated from the cardiac potential. FIG. 5 is a diagram showing the inclination θ of the Y axis calculated from the measurement value of the acceleration sensor of the sensor terminal installed on the back of the athlete. FIG. 6 is a diagram showing the inclination φ of the X axis calculated from the measured values of the acceleration sensor of the sensor terminal installed on the back of the athlete. FIG. 7 is a diagram showing a drawing operation, an anchoring operation, a releasing operation, and a follow-through operation when performing an archery competition. FIG. 8 is a diagram showing a measured value φ obtained from the acceleration sensor of the sensor terminal installed on the bow. FIG. 9 is a diagram showing the difference value φ ′ of the measurement value φ obtained from the acceleration sensor of the sensor terminal installed on the bow together with “the line I indicating whether or not Condition 1 is satisfied”. FIG. 10 is a diagram showing "a line I indicating whether or not Condition 1 is satisfied" together with the cardiac potential. FIG. 11 is a diagram showing an example in which the generation time difference Δt between the R wave and the release is obtained. FIG. 12: is a figure which shows the principal part of the exercise assistance apparatus which concerns on Embodiment 2 of this invention. FIG. 13 is a diagram showing the numbers determined for the direction (direction) in which the arrow deviates from the center of the target. FIG. 14 is a diagram showing an example of inputting scores. FIG. 15 is a diagram showing an example of inputting a direction. FIG. 16 is a diagram showing an example in which a score and an azimuth are input by tapping a target picture displayed on the screen of the child terminal. FIG. 17 is a diagram showing a main part of the exercise support device according to the third embodiment of the present invention. FIG. 18 is a diagram showing a main part of the exercise support device according to the fourth embodiment of the present invention. FIG. 19 is a diagram showing a main part of the exercise support device according to the fifth embodiment of the present invention. FIG. 20 is a diagram showing a configuration of a main part of the wearable device shown in Patent Document 2.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In addition, in the following embodiment, an archery competition will be described as an object to support the movement of a competitor (athlete) during the archery competition.

[Embodiment 1]
1 is a diagram showing a main part of an exercise support device 100 according to Embodiment 1 of the present invention. In FIG. 1, 1 is a sensor terminal and 2 is a child terminal that receives sensor data from the sensor terminal 1. In this example, three sensor terminals 1-1 to 1-3 are provided as the sensor terminal 1. FIG. 2 shows the installation status of the sensor terminals 1-1 to 1-3.

  In this exercise support device 100, the sensor terminal 1-1 is installed on the chest of the athlete M (see FIG. 2A). The sensor terminal 1-2 is installed on the bow 21 of the athlete M (see FIG. 2A). The sensor terminals 1-3 are installed on the back of the athlete M (see FIG. 2B). A smartphone, a tablet, a notebook computer, or the like is used as the child terminal 2 (see FIG. 2C). Note that the bow 21 held by the athlete M is omitted in FIG.

  The sensor terminal 1-1 includes a voltage sensor 3 (3-1) and an acceleration sensor 4 (4-1). The voltage sensor 3-1 measures an electrocardiographic potential as the bioelectric potential of the athlete M, and the acceleration sensor 4-1 measures the acceleration of the chest generated with the movement of the athlete M, and the measured cardiac potential and The acceleration is sent to the child terminal 2 as sensor data.

  The sensor terminal 1-2 includes an acceleration sensor 4 (4-2). The acceleration sensor 4-2 measures the acceleration of the bow 21, that is, the acceleration of the hand generated with the movement of the player M holding the bow 21, and sends the measured acceleration to the child terminal 2 as sensor data.

  The sensor terminal 1-3 includes the acceleration sensor 4 (4-3). The acceleration sensor 4-3 measures the acceleration of the back generated with the movement of the athlete M, and sends the measured acceleration to the child terminal 2 as sensor data.

  The sensor data from the sensor terminals 1-1 to 1-3 is transmitted to the child terminal 2 by a wireless communication function such as "BlueTooth (registered trademark)", "WiFi (registered trademark)", or "LTE (registered trademark)". To be done. In the child terminal 2, various characteristic amounts of the athlete M from the received sensor data, such as heart rate variability (electrocardiogram / RRI), posture stability, respiration, time difference between R wave and release (described later), etc. Ask.

  The child terminal 2 includes a heartbeat interval / respiratory waveform calculation unit 2-1 that calculates a heartbeat interval (RRI) and a respiratory waveform from the cardiac potential measured by the voltage sensor 3-1, and the acceleration sensors 4-1 to 4-3. A posture calculation unit 2-2 that calculates the posture of the athlete M from the measured acceleration, and an event detection unit that detects a specific motion type of the athlete M as an event from the posture calculated by the posture calculation unit 2-2 2-3, the R-wave generation timing obtained from the cardiac potential measured by the voltage sensor 3-1 and the event detected by the event detection unit 2-3 are used to determine the feature amount of the athlete M during execution of the event. And an event execution time feature amount calculation unit 2-4 for calculating.

  FIG. 3 is a diagram showing a cardiac potential and an RRI waveform calculated from the cardiac potential. The heartbeat interval / respiration waveform calculation unit 2-1 calculates the RRI using the cardiac potential (see 2.8 of Non-Patent Document 3). The procedure is to obtain a differential waveform of the cardiac potential (a waveform showing the difference between the (t + 1) th cardiac potential and the tth cardiac potential), and consider that the R wave is generated when the differential waveform exceeds an arbitrary threshold value. The wave generation interval is defined as RRI.

  FIG. 4 is a diagram showing a cardiac potential and a respiratory waveform calculated from the cardiac potential. The heartbeat interval / respiration waveform calculation unit 2-1 calculates the respiratory waveform using the cardiac potential (see Non-Patent Document 4), and has a temporal change in the voltage difference (RS amplitude) between the R wave and the S wave in the cardiac potential. And make it a respiratory waveform.

  If you want to use the respiration rate instead of the respiration waveform, find the wave period (unit is [s]) from the peak interval at the top or bottom of the respiration waveform, and take the reciprocal of that period to determine the respiration frequency (unit: [Hz]) and multiplying this by 60 gives the respiratory rate per minute. In this case, the heartbeat interval / respiration waveform calculation unit 2-1 obtains the respiration rate from the calculated respiration waveform. Further, the heartbeat interval / respiration waveform calculation unit 2-1 may obtain the heart rate from the calculated RRI.

  The posture calculation unit 2-2 calculates the posture of the athlete M from the acceleration measured by the acceleration sensors 4-1 to 4-3. In this case, the attitude is calculated by the inclination of the axes of the acceleration sensors 4-1 to 4-3. The inclination of each acceleration sensor 4 is modified by referring to the description of Non-Patent Document 5, and is obtained by the following equation (1) and equation (2-1) or equation (2-2).

In the above equations (1), (2-1), and (2-2), θ is the inclination of the Y axis of the acceleration sensor 4 with respect to the vertical direction, and φ is the inclination of the X axis of the acceleration sensor 4 with respect to the vertical direction. Yes, the unit is degree. A _{x, out} , A _{y, out} and A _{z, out} are output values of the acceleration sensor 4, and the unit thereof is gravitational acceleration G (1.0 G≈9.8 m / s ² ).

  In the above equations (1), (2-1), and (2-2), the ratio of the measurement value of the single axis to the size (norm) of the combined vector of the output values of the acceleration sensor 4 is calculated, and the cosine is further calculated. By obtaining the inverse function of (cosine), the inclination θ of the Y-axis and the inclination φ of the X-axis of the acceleration sensor 4 are calculated as values having the dimension of the angle.

  Since the norm included in the equations (1), (2-1), and (2-2) has a constant value under the static operation condition such as archery, regardless of the inclination of the acceleration sensor 4, The norm cannot be used to reveal the posture. However, it is possible to clearly grasp the posture by obtaining the inclination by the equations (1), (2-1), and (2-2).

  FIG. 5 shows the inclination θ of the Y-axis calculated from the measurement value of the acceleration sensor 4-3 of the sensor terminal 1-3 installed on the back of the athlete M. FIG. 6 shows the inclination φ of the X axis calculated from the measurement value of the acceleration sensor 4-3 of the sensor terminal 1-3 installed on the back of the athlete M. 5 and 6, S1 indicates the period of the drawing action (see FIG. 7 (a)) during the archery competition, S2 indicates the period of the anchoring action (see FIG. 7 (b)), and S3 indicates The release operation (see FIG. 7C) is shown, and S4 is the follow-through operation (see FIG. 7D).

  In FIGS. 5 and 6, the large changes in both θ and φ during the drawing operation period S1 indicate that the posture is moving to pull the bow. Further, in the period S2 of the anchoring operation, the changes in θ and φ are reduced as compared with the period S1 of the drawing operation, but the changes themselves have not disappeared. The stability of the posture can be quantitatively grasped from θ and φ in the period S2 of this anchoring operation.

  The same applies to the acceleration sensors 4-1 and 4-2. That is, in the present embodiment, by using the acceleration sensors 4-1 to 4-3, it is possible to quantitatively grasp the stability of the posture without using the floor reaction force meter. The movement of the person M can be supported.

  The event detection unit 2-3 detects a specific motion type of the athlete M as an event from the posture calculated by the posture calculation unit 2-2. In this example, the release timing when the player M shoots an arrow (the timing at which the string moves away from the hand pulling the string) is detected as an event, and the detected release timing is detected by the event execution feature quantity calculation unit 2-4. Send to.

  The event execution time feature amount calculation unit 2-4 generates the R wave generated from the cardiac potential measured by the voltage sensor 3-1 and the release timing (release timing) detected by the event detection unit 2-3. , And the time difference between the release timing detected by the event detection section 2-3 and the immediately preceding R wave generation timing (R wave and release generation time difference) Δt when the athlete M performs the release operation ( It is calculated as a feature amount when the event is executed).

  In this example, since the R wave is detected when the RRI is calculated by the heartbeat interval / respiration waveform calculation unit 2-1, the detection timing of the R wave from the heartbeat interval / respiration waveform calculation unit 2-1 is set at the time of event execution. It is sent to the amount calculation unit 2-4, and the R wave detection timing in the heartbeat interval / respiration waveform calculation unit 2-1 is used as the R wave generation timing.

  The event detector 2-3 determines the release timing. In this case, the difference value φ ′ obtained from φ calculated using the above equation (2) is used to detect the release timing. As an example, the difference value φ ′ is obtained from the measured value of φ obtained from the acceleration sensor 4-2 of the sensor terminal 1-2 installed on the bow 21, and the release timing is obtained using the obtained difference value φ ′.

FIG. 8 shows the measured value of φ, and FIG. 9 shows the difference value φ ′ of φ. The horizontal axis represents time (s) and the vertical axis represents angle (degree). If the t-th φ from the start of measurement is φ _t , the difference value φ ′ _t is obtained as φ ′ _t = φ _{t + 1} −φ _t (t = 1, 2, 3, ...). ..

In this embodiment, the release timing is obtained as follows. Sharp artefacts are measured at the time of release due to the violent recoil of the strings. Using this artifact, the release operation is detected under the following condition 1.
Condition 1: If the difference value of φ at the t-th time from the start of measurement is φ ′ _t , φ ′ _t-1 ≧ −3, φ ′ _t ≦ −3, and φ ′ _{t + 1} ≧ −3 are satisfied.

  When this condition is satisfied, it is set to "1", and when it is not satisfied, it is set to "0". A line I shown together with the difference value φ ′ in FIG. 9 is a line indicating whether or not this condition is satisfied (a line indicating the detection result), and from “0” on the line I indicating the detection result. The place where the value changes to “1” indicates that the release operation is occurring. That is, the release operation can be accurately detected by using the above condition 1.

  The event detection unit 2-3 detects the point (release timing) at which the release operation is occurring as an event, and detects the time difference between the release timing and the immediately preceding R wave generation timing (R wave and Calculate the release time difference) Δt. FIG. 10 shows a line (line indicating whether or not Condition 1 is satisfied) I showing the detection result shown in FIG. 9 together with the cardiac potential. The time Δt indicated by the arrow is the time difference between the R wave and the release, which is obtained as the time difference between the release timing and the latest R wave generation timing in the past and closest to the release timing.

  FIG. 11 shows an example in which the time difference Δt between the R wave and the release is calculated. In this example, at the release timing, the time difference Δt between the R wave and the release is calculated as Δt = 0.47 seconds. If 30% of the RRI is used as a reference for the time difference Δt between the R wave and the release, 30% of the RRI at a heart rate of about 80 is about 0.23 seconds, and in the example of FIG. Since the generation time difference Δt is larger than this, it can be inferred that the generation of the R wave is unlikely to have a great influence on the release operation.

  As can be seen from the above description, according to the exercise support device 100 of the present embodiment, only the voltage sensor 3 (3-1) and the acceleration sensor 4 (4-1 to 4-3) change the heartbeat (the electrocardiogram. RRI), posture stability, breathing, and the feature amount of the athlete M such as the time difference between the R wave and the release can be obtained, and the number of sensors can be reduced and the cost can be reduced. In addition, it is easy to carry and it is possible to reduce the physical and mental burden on the athlete M. In addition, by consolidating the acquired feature amounts in one child terminal 2, it is possible to provide the athlete M with a high-quality measuring, recording, holding, and confirming means, and to support efforts to improve the ability of the athlete. You can

[Embodiment 2]
FIG. 12 shows a main part of the exercise support device 200 according to the second embodiment of the present invention. In the figure, the same reference numerals as those in FIG. 1 indicate the same or similar constituent elements as the constituent elements described with reference to FIG. 1, and the description thereof will be omitted.

  The exercise support apparatus 200 according to the second embodiment is a modification of the exercise support apparatus 100 according to the first embodiment, and receives an input of a shooting score and a direction (direction) in which the arrow deviates from the center of the target. The child terminal 2 is equipped with an input unit 2-5.

  In this exercise support device 200, as shown in FIG. 13, the direction (direction) in which the arrow deviates from the center of the target is represented by a number from 1 to 12 like the dial of a timepiece. If hit, 0 is used. FIG. 14 shows an example of inputting scores, and FIG. 15 shows an example of inputting azimuths. The end in FIG. 14 and FIG. 15 is one unit when performing an archery competition in which a predetermined number of shootings are set as one set. Here, an example is an individual game in which one end consists of six shootings. At the end of each end, the athlete walks to the target, retrieves the arrow from the target, and moves to the next end.

  The 1 to 6 shots in FIGS. 14 and 15 indicate the order of the row shots at each end, the first shot being one shot and the last shot being six shots. The score and direction are manually input from the touch panel of the child terminal 2. In this case, a numerical value may be entered, or as shown in FIG. 16, a target picture is displayed on the screen of the child terminal 2 and the position is entered by tapping the same position on the screen as the position where the real arrow is stuck. You may do it.

  In the exercise support device 200 according to the second embodiment, not only the amount of characteristic of the exerciser but also the score which is an index of the ability of archery and the direction of deviation of the arrows can be collectively stored as data. As a result, it is expected that convenience will be improved, and efforts to improve competitive ability can be further supported.

[Embodiment 3]
FIG. 17 shows a main part of the exercise support device 300 according to the third embodiment of the present invention. In the figure, the same reference numerals as those in FIG. 12 indicate the same or similar components as the components described with reference to FIG. 12, and the description thereof will be omitted.

  The exercise support apparatus 300 according to the third embodiment is a modification of the exercise support apparatus 200 according to the second embodiment, in which the child terminal 2 includes an analysis unit 2-6 that performs multiple regression analysis using each feature amount and score. It is characterized by having.

In the exercise support apparatus 300, the following multiple regression equation (equation (3)) is used for the multiple regression analysis in the analysis unit 2-6.
Y '= α + β ₁ X ₁ + β ₂ X ₂ + β ₃ X ₃ + ... + β _n X _n (3)

Y'in the equation (3) is a vector for storing the estimated value of the objective variable of the bijection. This is automatically determined by the later least squares method. X _{1 to} X _n are vectors that store the explanatory variables, and store each feature quantity of all rays. For example, X ₁ is used to store the inclination (hand posture) of the omnidirectional bow, X ₂ is used to store the RRI, and so on. The constant term α and the partial regression coefficients β ₁ , β ₂ , β ₃ , ..., β _n are determined by the least squares method.

  Since it is not necessary to use all the independent variables, the independent variables are selected by the stepwise method, the variable increasing method, the variable decreasing method, etc., and the selected independent variables are introduced into the multiple regression equation.

In the least squares method, the constant term α and the partial regression coefficients β ₁ , β ₂ , β ₃ , ..., β _n are determined so that the sum of squares of the difference between the objective variable Y and the estimated value Y ′ is minimized. Here, it is assumed that the objective variable Y is a value obtained by subtracting the actual score value from 10 points (full score) and stored for all shootings. For example, the score of 6 shootings is 8, 7, 8, 3, 10, 7. In case of, it becomes 2,3,2,7,0,3.

Next, partial regression coefficients β ₁ , β ₂ , β ₃ , ..., β _n are tested to determine whether they are statistically significant. Various types of test statistics are known, but in the present embodiment, a t value known as a test statistic using a t distribution is used. When the t value at X ₁ is T ₁ , the probability (p value) can be obtained by a two-sided test of the t function with n-2 degrees of freedom. The p-value means the probability that a difference in data will occur by chance, and when the p-value is small, it is considered that there is a significant difference that exceeds chance, that is, a “significant difference” (see Non-Patent Document 6).

In the present embodiment, by using this p-value, the significance between each feature amount and the objective variable can be evaluated. If a value obtained by subtracting the actual score from the full score is used as the objective variable and a significant difference is obtained between this and X ₁ (the inclination of the bow), there is a relationship between the two that exceeds chance. Suggest. This suggests that the inclination of the bow may have lowered the score, and may be one of the ways to determine the factors that limit the competitiveness of athletes. Therefore, exercisers are encouraged to consider practice to correct bow tilt. That is, it is possible to support an exerciser by calculating such a rate-determining characteristic amount. On the other hand, if no significant correlation is obtained, the exerciser may be able to control each feature to a high degree so that it cannot be found at the significance level of 5%, and it can be used as a condition index. Therefore, regardless of whether the result is significant or not, useful information can be presented to the exerciser, and the exerciser can be supported.

  Note that a statistically sufficient number of data (number of shots) is required to perform effective analysis by multiple regression analysis. In the multiple regression analysis taken as an example in the present embodiment, there are five explanatory variables (RRI, respiratory waveform, bow inclination, posture, time difference between R wave and release). With reference to Non-Patent Document 7, if the test power is 0.8, the significance level is 0.05, and the guideline for the effect size is 0.35, the required sample number is 43. In the 70m round in the recurving section of the archery competition, the number of shots is 36, so you can get a sufficient amount of data by doing 2 sets and practicing 72 shots as a practice. Furthermore, even if the conditions are rigorously estimated and the guideline for the effect size is set to 0.15, the required sample number is 91, so adding another set will provide a sufficient amount of data. Therefore, it can be said that such an evaluation by multiple regression analysis is a realistic and realistic support method for practice in normal times.

[Embodiment 4]
FIG. 18 shows a main part of an exercise support device 400 according to Embodiment 4 of the present invention. 17, the same reference numerals as those in FIG. 17 indicate the same or equivalent constituent elements as the constituent elements described with reference to FIG. 17, and the description thereof will be omitted.

  The exercise support device 400 according to the fourth embodiment is a modification of the exercise support device 300 according to the third embodiment. The sensor terminal 1-1 measures a cardiac potential as a biopotential of the athlete M, and the sensor terminal 1- In 2 and 1-3, the myoelectric potential is measured as the bioelectric potential of the athlete M. The sensor terminals 1-2 and 1-3 are equipped with voltage sensors 3-2 and 3-3 as sensors for measuring the myoelectric potential of the athlete M.

  In the exercise support device 400 according to the fourth embodiment, the specifications of the sensor terminals 1-1 to 1-3 can be unified, and the manufacturing / sales can be performed without substantially increasing the substantial mass production cost. In the sensor terminals 1-2, 1-3 other than the sensor terminal 1-1 installed on the chest, the voltage sensors 3-2, 3-3 are used to measure myoelectric potential instead of cardiac potential, which is more abundant. The characteristic amount of the body can be obtained. The sampling rate for measuring the myoelectric potential is 1000 Hz as in the case of the cardiac potential, and noise is removed from the measured value through a low-pass filter with a cutoff frequency of 150 Hz.

  However, the cutoff frequency of the low-pass filter may be variably set depending on whether electrocardiography or myoelectricity is taken. For example, in the case of electrocardiography, noise removal performance is improved by setting the frequency to about 40 Hz as compared with 150 Hz. For the obtained EMG, a threshold value may be set to a voltage value larger than the noise floor level voltage value, and the occurrence time of EMG may be extracted by exceeding the threshold value, or the peak value of the EMG may be set. The envelope may be obtained by extracting. It is also possible to treat the occurrence time of the myoelectric potential and the value of the envelope as a feature amount and perform analysis such as multiple regression analysis. In FIG. 18, the myoelectric potential occurrence time detection unit 2-7 based on the envelope calculation is provided in the child terminal 2.

  As described above, by measuring the myoelectric potential using the voltage sensors 3-2 and 3-3, it is possible to quantitatively and abundantly understand the physical characteristics of the archery competition. In addition, multiple regression analysis can support capacity improvement.

  18 shows a modification of the exercise support device 300 of the third embodiment, the exercise support devices 100 and 200 of the first and second embodiments are similar to the exercise support device 400 of the fourth embodiment. The sensor terminals 1-2 and 1-3 may be provided with voltage sensors 3-2 and 3-3 that measure the myoelectric potential of the athlete M.

[Fifth Embodiment]
FIG. 19 shows a main part of the exercise support device 500 according to the fifth embodiment of the present invention. 18, the same reference numerals as those in FIG. 18 indicate the same or equivalent constituent elements as the constituent elements described with reference to FIG. 18, and description thereof will be omitted.

  The exercise support device 500 according to the fifth embodiment is a modification of the exercise support device 400 according to the fourth embodiment, and is a gyro as a substitute for the acceleration sensors 4-1 to 4-3 in the sensor terminals 1-1 to 1-3. The sensors 5-1 to 5-3 are provided.

  In the exercise support device 500 according to the fifth embodiment, since the rotation information of the sensor terminals 1-1 to 1-3 can be obtained by the gyro sensors 5-1 to 5-3, θ and φ can be obtained, The technique of the present invention can be used. Therefore, even if the sensor terminal does not include the acceleration sensor, the movement of the athlete can be similarly supported if the gyro sensor is included.

  Although FIG. 19 shows a modification of the exercise support device 400 of the fourth embodiment, the exercise support devices 100, 200, and 300 of the first, second, and third embodiments also have the exercise support of the fifth embodiment. Similar to the device 500, the gyro sensors 5-1 to 5-3 may be provided. Further, gyro sensors 5-1 to 5-3 may be provided in addition to the acceleration sensors 4-1 to 4-3.

[Expansion of Embodiment]
Although the present invention has been described with reference to the exemplary embodiments, the present invention is not limited to the above exemplary embodiments. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the technical idea of the present invention. In addition, the respective embodiments can be implemented in any combination within a range that does not contradict.

  1 (1-1 to 1-3) ... Sensor terminal, 2 ... Child terminal, 2-1 ... Heartbeat interval / respiration waveform calculator, 2-2 ... Posture calculator, 2-3 ... Event detector, 2-4 ... Event execution feature quantity calculation unit, 2-5 ... External input unit, 2-6 ... Analysis unit, 2-7 ... Myoelectric potential time detection unit, 3 (3-1 to 3-3) ... Voltage sensor, 4 (4-1 to 4-3) ... Acceleration sensor, 5 (5-1 to 5-3) ... Gyro sensor, 21 ... Bow, 100-500 ... Exercise support device, M ... Competitor (exercise person).

Claims (6)

An exercise support device for supporting movement of an exerciser,
A voltage sensor that measures a cardiac potential as the bioelectric potential of the exerciser,
An acceleration sensor for measuring accelerations of three axes orthogonal to each other in the chest and back of the exerciser and the bow of the exerciser ;
A child terminal that receives as inputs the cardiac potential measured by the voltage sensor and the acceleration measured by the acceleration sensor,
The child terminal is
A heartbeat interval / respiratory waveform calculating means for calculating at least a heartbeat interval and a respiratory waveform from the cardiac potential measured by the voltage sensor,
Posture calculating means for calculating the posture of the exerciser from the acceleration measured by the acceleration sensor and the inclination of the axis of the acceleration sensor ,
Event detection means for detecting, as an event, the release timing when the exerciser shoots an arrow from the posture calculated by the posture calculation means,
The time difference between the release timing detected by the event detection means and the generation timing of the R wave immediately before the release timing included in the cardiac potential measured by the voltage sensor is calculated as the time difference between the exerciser's execution of the event. An exercise support device, comprising : an event execution time feature amount calculation means for calculating a feature amount . In the exercise support device according to claim 1 ,
The child terminal is
The exerciser is provided with an external input means for inputting a score when the arrow is shot and a direction deviating from the aim ,
Along with the feature amount at the release timing when the exerciser shoots an arrow calculated by the event execution time feature amount calculation means, the score and the orientation input to the external input means are the ability of the exerciser. An exercise support device characterized by being held and displayed as an index of . The exercise support apparatus according to claim 2 ,
The child terminal is
The exercising person comprises an analyzing means for analyzing a movement when the arrow is shot,
The heartbeat interval / respiration waveform calculation means,
From the cardiac potential measured by the voltage sensor, calculate the heartbeat interval, respiratory waveform, respiratory rate,
The analysis means is
At least the cardiac potential measured by the voltage sensor, the heartbeat interval calculated by the heartbeat interval / respiratory waveform calculation means, the respiratory waveform, the respiratory rate, and the release occurrence timing calculated by the event execution time feature amount calculation means Based on the time lag between the generation timing of the R wave and the immediately preceding R wave, the score and the azimuth input to the external input means as values input from the outside, the motion of the exerciser when the arrow is shot is analyzed. An exercise support device characterized by the above. In the exercise support device according to any one of claims 1 to 5 ,
A gyro sensor is provided instead of the acceleration sensor ,
The gyro sensor is arranged on the chest of the exerciser, the back, and a bow held by the exerciser, and measures rotation information including angular velocity at each arrangement position,
The exercise assisting device , wherein the posture calculating means calculates the posture of the exerciser from an angle corresponding to the inclination of the axis of the acceleration sensor calculated based on the angular velocity measured by the gyro sensor . In the exercise support device according to any one of claims 1 to 5 ,
In addition to the acceleration sensor, a gyro sensor is provided ,
The exercise support device , wherein the gyro sensor is arranged on a chest, a back of the exerciser, and a bow held by the exerciser, and measures rotation information including angular velocities at respective arrangement positions . An exercise support method for supporting movement of an exerciser,
A first step of measuring a cardiac potential as a biological potential of the exerciser with a voltage sensor;
A second step of measuring accelerations of three axes orthogonal to each other in the chest, the back of the exerciser, and the bow of the exerciser with an acceleration sensor;
A third step in which the heartbeat interval / respiratory waveform calculation means calculates at least a heartbeat interval and a respiratory waveform from the electrocardiographic potential measured in the first step;
A fourth step in which the posture calculation means calculates the posture of the exerciser from the acceleration measured in the second step and the inclination of the axis of the acceleration sensor ;
A fifth step in which the event detecting means detects, as an event, a release timing when the exerciser shoots an arrow from the posture calculated in the fourth step;
The runtime characteristic amount calculation means calculates the time difference between the release timing detected in the fifth step and the R wave generation timing immediately before the release timing included in the cardiac potential measured by the voltage sensor. And a sixth step of calculating a feature amount when the person executes the event .