JP2009268584A - Motion analyzer, motion analysis method, program and recording medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an apparatus in which the average data of a plurality of attempts are easily understandably displayed and the data of motion points under consideration during a series of motions are not changed. <P>SOLUTION: The control part 13 of the motion analyzer 1 specifies parameter data under consideration corresponding to the motion point under consideration from time sequential data in which parameter data are arranged according to the duration, dividing the time sequential data into a plurality of sections with the parameter data under consideration as a break position, sets the average value of the entire attempts of the ratio of the number of the parameter data for each attempt as a reference ratio for each section, and sets the reference number of data on the basis of the reference ratio and the maximum number of data of each section. Then, the control part 13 executes data conversion so that the number of the parameter data of each section is the reference number of data set for the section for the time sequential data of the respective attempts, and obtains the average value. On the basis of the average value, the control part 13 causes a display 12 to display an image indicating the timewise change of the parameter. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a motion analysis apparatus and a motion analysis method for analyzing a motion of a sports player.

  Currently, many of the athletes who are called first-class wear a purposeful and rational exercise process (exercise technique) and use it in the competition. Therefore, by analyzing the movements of first-class athletes during the competition, it is possible to obtain materials that clarify the exercise technique. Conventionally, motion analysis by movie shooting has been performed. In this case, even when a plurality of subjects are used, time series data of all subjects are hardly shown over all aspects of movement, and generally a method of showing some typical examples has been used ( Non-patent document 1).

  However, in recent years, with the advancement of data processing devices and the like, a technique for standardizing and averaging data based on the operating time of each subject is known. For example, the operation time of each subject is normalized to 100%, and the data is averaged at each normalized time, thereby showing the data of a plurality of subjects in a simpler manner.

FIG. 8 shows the ground reaction force during a jumping motion by three subjects. In (A), the horizontal axis is the elapsed time from the jump start point, and the operation time is different for the three trials, so the curves overlap and the overall result is difficult to understand. (B) standardizes the operation time of each trial to 160%, and the change pattern is easy to understand. (C) shows the average and standard deviation of the data normalized in (B), and is a collection of a plurality of time series data. In this way, by standardizing the time from the start of the operation to the end of the operation, the average pattern of a plurality of attempts can be easily understood.
Masahisa Masumura, Michiyoshi Ae, “Body movement to hit the ball strongly in the air -Analysis of volleyball ball movement-", Biomechanics Research, Vol.11, No.3, 2007 Takahiro Hashihara et al., “Analysis of Exercise Technology by Standardization / Averaging Technique: Volleyball Spike Technology”, Physical Education Research Vol. 33, No. 3, December 1988

  However, in the case of FIG. 8C, there are the following problems. That is, a series of operations from the operation start to the operation end may include an operation point to be noted (attention operation point). For example, an attack motion in a volleyball game is from the time of takeoff to the time of landing, and includes an attention motion point at the time of hitting the ball. The timing at which such attention motion points are performed varies depending on each trial. Therefore, when the time from the start to the end of the operation is standardized and an average pattern of multiple attempts is shown, it is impossible to determine the point in time of the target operation point, and various dynamic data of the target operation point will change. .

  Non-Patent Document 2 discloses a drawing in which the time at the crossing in the crossing operation in the volleyball game, the time at the end of the first half, and the time at the takeoff are combined. However, Non-Patent Document 2 does not disclose a specific method for creating such a drawing. In other words, the average value of the time ratio of the first half and the second half of the level crossing over all trials is obtained, the data is normalized by setting a standard for the operation time, and the standardized data is averaged and displayed. The method of determining the number of data to make it possible (constraint conditions for time division) is not considered or mentioned.

  The present invention has been made in view of the above-described problems, and the purpose of the present invention is to display average data of a plurality of trials in an easy-to-understand manner for a series of movements in an athletic competition, and to draw attention movements during the series of movements. The object is to realize a motion analysis apparatus and a motion analysis method in which the data of points does not change and the standardization processing for all trial techniques is simple.

  In order to solve the above problems, the motion analysis device according to the present invention is a motion analysis device including a control unit that analyzes the motion of a sports player, and a series of predetermined motions including a target motion point is a specific motion, When the data indicating the value of the parameter that changes with the specific operation is used as the parameter data, the control unit (a) for a plurality of trials, the parameter data for each predetermined time in the specific operation are arranged according to the elapsed time (B) specifying parameter data corresponding to the target action point as target parameter data from among the time series data, and (c) using the target parameter data as a delimiter position, the time series data. (D) For each trial, for each division, the number of parameter data included in the division Calculate the ratio to the number of all parameter data, (e) For each category, calculate the average value over all trials of the calculated ratio, set the average value as the reference ratio, (f) For each category, Specify the maximum number of maximum data among the number of parameter data of each trial, (g) For each division, set the reference data number that satisfies the following condition A, (h) For the time series data of each trial, The parameter data is converted by linear interpolation so that the number of parameter data in each section becomes the number of reference data set for the section, the converted parameter data is arranged in order according to the elapsed time, and each parameter data is Create converted time-series data associated with the number indicating the order, and (i) for the converted time-series data in all trials, A value is obtained, average time series data in which the average values are arranged according to numbers is created, and a screen showing temporal changes of the parameters is displayed on the display unit based on the average time series data. .

  Condition A: For each category, the number of reference data for the category is greater than or equal to the maximum number of data specified for the category, and the ratio of the number of reference data for the category to the total number of reference data for all categories is It matches the reference ratio set for.

  Further, the motion analysis method of the present invention is a motion analysis method in a motion analysis device provided with a control unit for analyzing the motion of a sports player, wherein a series of predetermined motions including a target motion point is defined as a specific motion, and the specific motion When the data indicating the parameter value that changes with the parameter data is used as parameter data, (a) the control unit sets time-series data in which the parameter data for each predetermined time in the specific operation is arranged according to the elapsed time for a plurality of trials. (B) the control unit specifies parameter data corresponding to the target action point from the time series data as target parameter data, and (c) the control unit Dividing the time-series data into a plurality of sections using the parameter data as a delimiter position; and (d) the control unit For each trial, for each category, a step of calculating a ratio of the number of parameter data included in the category to the total number of parameter data, and (e) the ratio calculated by the control unit for each category A step of obtaining an average value over all attempts and setting the average value as a reference ratio; and (f) the maximum number of data among the number of parameter data of each attempt by the control unit for each division. And (g) the control unit sets a reference data number satisfying the following condition A for each section, and (h) the control unit sets each of the time series data of each trial for each time series data. The parameter data is converted by linear interpolation so that the number of parameter data in the division becomes the number of reference data set for the division. A step of creating converted time series data in which each parameter data is associated with a number indicating the order, and (i) the control unit has the same number for the converted time series data in all trials The average value of the parameter data is obtained for each time, average time series data in which the average values are arranged according to the number is created, and a screen showing the temporal change of the parameters is displayed on the display unit based on the average time series data And a step.

  Condition A: For each category, the number of reference data for the category is greater than or equal to the maximum number of data specified for the category, and the ratio of the number of reference data for the category to the total number of reference data for all categories is It matches the reference ratio set for.

  According to said structure, the average value of parameter data, such as various dynamic data in a some test subject, can be shown with time. Further, since the position data of the target motion point does not change, the position data of the target motion point can be displayed accurately. In the converted time-series data in all trials, the number of parameter data in each section is the same as the number of reference data, so that the process for obtaining the average value can be easily executed.

  Further, as described above, in the technique described in Non-Patent Document 2, the number of data serving as a reference for standardizing data of all trials is obtained by averaging the time ratios of the respective phases with respect to the entire operation time. With this method alone, data cannot be standardized by synchronous adjustment for trials in which the number of raw data of trials is greater than the number of reference data. However, according to the above configuration, it is possible to standardize all attempts by setting the number of reference data satisfying the condition A for each section. That is, the condition A has one requirement that, for each category, the number of reference data for the category is equal to or greater than the maximum number of data specified for the category. Therefore, the number of raw parameter data in each section in all trials is equal to or greater than the number of reference data set for the section. As a result, by using linear interpolation for the time series data of each trial, the parameter data can be easily converted so that the number of parameter data in each section becomes the number of reference data. That is, it is possible to easily standardize the number of data of all attempts. Such an effect is an unprecedented effect.

  Furthermore, the condition A has one requirement that the ratio of the number of reference data of the section to the total number of reference data of all sections matches the reference ratio set for the section. Here, “matching” includes not only the case of complete matching but also the case of slight deviation from the reference ratio. For example, when the reference ratio is obtained up to one digit after the decimal point, it may be “matched” even if it is within ± 0.5% of the reference ratio. Thereby, in the converted time series data, the ratio of the number of parameter data of each section matches the reference ratio. Since the reference ratio corresponds to the time ratio of each section, the time ratio of each section can be grasped by checking the number of parameter data of each section.

  Furthermore, it is preferable that the control unit displays on the display unit a screen representing the average value at a constant interval in the order of the numbers.

  Thereby, the time ratio of each division can be grasped by looking at a screen showing the above average values at regular intervals in the order of the numbers.

  An example of the sports player is a volleyball player, and an example of the parameter data is position data indicating position coordinates of a specific body part of the volleyball player with respect to a predetermined reference axis.

  The motion analysis device may be realized by a computer. In this case, a program for causing the computer to operate the motion analysis device by operating the computer as the control unit, and a computer readable recording thereof Various recording media are also within the scope of the present invention.

  As described above, the motion analysis apparatus according to the present invention can easily display the average data of a plurality of trials for a series of motions in a sports competition, and does not change the data of attention motion points during the series of motions. A simple screen can be displayed.

  One embodiment of the motion analysis system of the present invention is described below with reference to FIGS.

(Configuration of motion analysis system)
The motion analysis system according to the present embodiment is realized by a motion analysis program that analyzes data (analysis target data: parameter data) indicating values of various parameters that change in accordance with the motion of a player in a sporting event such as a volleyball game. . Here, the analysis target data includes, for example, a relative position of a sports equipment such as a body part or a bat relative to a reference point, a force such as a ground reaction force, a speed of the body part or a sports equipment, a reference when centering on a reference axis. There is data indicating the body part from the line, the angle of the sports equipment, and the like. In the following, the relative position data with respect to the reference point (hereinafter simply referred to as position data) will be described as an example of the analysis target data, but the present invention is not limited to this. Although a volleyball competition will be described as an example of a sports competition, the present invention is not limited to a volleyball competition.

  As illustrated in FIG. 1, the motion analysis system 10 according to the present embodiment includes two cameras 2 for measuring analysis target data (here, position data) and moving image data captured by the camera 2. And an operation analysis apparatus 1 for analyzing position data.

  The motion analysis apparatus 1 is a personal computer in which the motion analysis program of this embodiment is installed. The motion analysis apparatus 1 includes an input unit 11, a display (display unit) 12, a control unit 13, and a storage unit 14.

  The input unit 11 includes a keyboard and a mouse. The keyboard is for inputting various processing commands and the like to the control unit 13. The mouse is a pointing device that allows an operator to specify any point in the image displayed on the display 12 and cause the control unit 13 to recognize the specified point.

  The display 12 is a device for displaying information processed by the control unit 13 as an image, and a liquid crystal display is used. However, the present invention is not limited to the liquid crystal display, and may be, for example, a plasma display, a CRT, an organic EL (Electro Luminescence) display, or an inorganic EL display.

  The control unit 13 comprehensively controls the operations of the various configurations described above in the motion analysis apparatus 1. The control unit 13 includes a CPU (Central Processing Unit), a RAM (Random Access Memory), and a random write / read memory. The operation control of various configurations is performed by causing the CPU to execute various control programs including an operation analysis program. For example, the control program may be in a form in which a program recorded on a removable medium such as a CD-ROM (Compact Disc Read Only Memory) is read and expanded in the RAM, and the CPU accesses the RAM and uses it. Alternatively, a configuration may be adopted in which what is installed in the storage unit 14 or the like is read out and expanded in a RAM, and the CPU accesses and uses the RAM. Further, when the control unit 13 is connected to a communication network such as the Internet, a mode in which the program is downloaded via the communication network, installed in the storage unit 14, and executed is also conceivable.

  The storage unit 14 is configured by a nonvolatile storage device such as a hard disk or a flash memory. The contents stored in the storage unit 14 include the control program, OS (Operating System) program, and other various programs, information input from the input unit 11, information processed by the control unit 13, and the like. .

(Operation analysis procedure)
Next, a specific method of motion analysis by the motion analysis device 1 in the present embodiment will be described. In the following, an explanation will be given by taking as an example a case where an analysis is performed on a crossing operation when a player performs an attack in a volleyball game. As shown in Fig. 2, the attack is a run-up operation from the time when it starts to attack until one foot reaches the level crossing position, a level crossing operation from when one foot reaches the level crossing position to the time of takeoff, It can be divided into three phases of hitting action from the ground to the landing. The level crossing operation can be performed in the first half from the time when one foot reaches the level crossing position (at the start of the level crossing) to the position where the body center of gravity reaches the lowest position (at the end of the first half), and from the time of the first half to the time of takeoff ( It is divided into the latter half until the end of the level crossing. Here, the end of the first half is the time when the force for jumping is accumulated, and is the attention operation point in the crossing operation. In FIG. 2, the position of the center of gravity of the body at the start of the crossing is indicated by a circle, the position of the center of gravity of the body at the end of the first half (attention motion point) is indicated by the mark of ◎, and the position of the center of gravity of the body at the end of the crossing is indicated by a mark.

(Procedure 1: Acquisition of position data)
An outline of a procedure based on the well-known DLT method (Direct Linear Transformation Parameters) will be described as a method for obtaining three-dimensional position data from a two-dimensional image photographed by a camera.

  The DLT method is a method for obtaining three-dimensional position data from two-dimensional image data by comparison with calibration points photographed so as to be distributed over the entire photographing range. For details on the principle and procedure of the method, for example, Walton , Js: “Science in Biomechanics Cinematography”, Academic Publishers, Del Mar, 1979, 69-97.

  In order to acquire three-dimensional position data by the DLT method, first, a calibrator (a plurality of markers whose relative positional relations are known as calibration points are installed on a calibrator at a photographing place (here, a valley court). And coordinate with the origin of the intersection of the center line and the left side line. In the control unit 13, a DLT coefficient for obtaining three-dimensional position data from an actual two-dimensional captured image is calculated for each photographing camera and stored in the storage unit 14.

  For example, the analysis of actual 3D position data is as follows: (1) From the start of the serve until the player finishes the attack and lands at the same time with the above two cameras (shooting speed is 100 frames per second, for example) (2) The operator finishes the crossing from the frame image at the start of the crossing for each of a plurality of crossing motion trials from the captured moving images. (3) The operator uses the mouse of the input unit to select a specific body part (for example, waist) of the player performing the crossing operation in each selected frame image, and (4) ) The control unit 13 can perform the procedure of calculating the three-dimensional position data of the specific body part designated from the already calculated DLT coefficient.

  In this way, the control unit 13 obtains the three-dimensional coordinates (position data) of the specific body part corresponding to each frame image from the start of the crossing to the end of the crossing for a plurality of crossing operations. And the control part 13 produces the time series data which arranged the calculated position data in the order of a frame image about each level crossing operation | movement. Thereby, the control part 13 can acquire time series data. At this time, the control unit 13 specifies position data corresponding to the frame images at the start of the crossing, at the end of the first half, and at the end of the crossing operation based on information input by the operator to the input unit, and which position data starts the crossing Information indicating whether the frame image corresponds to the frame image at the end of the hour, at the end of the first half or at the end of the crossing operation is stored in the storage unit 14. The creation of time series data may be executed by another computer apparatus, and the control unit 13 may acquire time series data from the computer apparatus.

  The position data may be calculated by attaching a transmitter to a specific body part (such as the waist) of the player and receiving a signal emitted from the transmitter.

(Procedure 2: Coordinate conversion processing of position data)
Time series data such as force, angle, speed, etc. can be subjected to normalization / average processing as described later. However, the position data as described above, particularly the position data indicated by the three-dimensional coordinates cannot be normalized and averaged as described later.

  FIG. 3 shows the movement of the attacking player during the volleyball game in terms of the position of the center of gravity of the body. The top view of FIG. 3 is seen from the side of the coat, and the bottom view of FIG. 3 is seen from the top of the coat. The origin is the intersection of the left side line and the center line. A circle on each line indicates the position of the center of gravity of the body at the start of the crossing, and a square mark indicates the position of the center of gravity of the body at the end of the crossing.

  As is clear from FIG. 3, each player has a different point and direction of attack. Therefore, the position data of the specific body part obtained by the three-dimensional movie shooting method cannot be standardized and averaged as it is. In order to standardize and average the position data of each trial, it is necessary to unify the movement surface.

  Therefore, the control unit 13 performs a coordinate conversion process on the position data of each attempt. FIG. 4 is a diagram illustrating a coordinate conversion procedure in a crossing operation that is a part of an attack operation of a volleyball game. The intersection of the left side line and the center line is the origin (0, 0, 0), and shows the trajectory of a specific body part during the crossing operation from above the court. The trajectory is indicated by time-series data acquired in (Procedure 1: Acquisition of position data). In the figure, the ◯ mark on the solid line indicates the position at the start of the crossing, the ◎ mark indicates the position at the end of the first half, and the □ mark indicates the position at the end of the crossing.

  The control unit 13 performs coordinate conversion according to the following procedures (1) to (3). However, the Z coordinate is not converted.

  (1) First, the control unit 13 obtains an angle θ between the horizontal vector from the position at the start of the crossing operation to the position at the end of the crossing operation and the center line.

  (2) Next, the origin is moved to the position on the court at the end of the first half.

  (3) Finally, each position data is coordinate-transformed by the following formulas A and B. Here, the converted Y′-axis is the longitudinal direction of the player, and the converted X′-axis is the lateral direction of the player.

X ′ = cos (θ) · X + sin (θ) · Y Formula A
Y ′ = − sin (θ) · X + cos (θ) · Y Formula B
By performing the coordinate conversion in this way, it is possible to unify the exercise surface of each trial with the front and rear direction and the left and right direction of the player as axes.

(Procedure 3: Data normalization process)
Next, normalization of time series data is performed. The operating time of each trial is different. Therefore, it is necessary to standardize the operation time of each trial technique. At this time, simply by standardizing the series of operations from the start to the end of the operation so that the start and end of the operation are combined, as described above, the target operation point (at the end of the first half in the case of a crossing operation) ) Cannot be discriminated at any time, and various data of the target action point are transformed.

  Therefore, in the present embodiment, the operation time normalization processing is performed on the coordinate-converted position data as follows.

(Standardization procedure 1)
First, for each trial, the control unit 13 counts the number of frame images from the start of operation to the end of the first half, that is, position data (hereinafter referred to as the first half part) from the start of the operation to the end of the first half (hereinafter referred to as the first half position). The number (M) of data). Further, for each trial, the control unit 13 counts the number of frame images from the end of the first half to the end of the operation (hereinafter referred to as the second half), that is, position data from the end of the first half to the end of the operation (hereinafter referred to as the second half position). The number (N) of data) is counted. The control unit 13 then, for each trial, the ratio Sm = M / (M + N) of the total number of first half position data (M + N) and the ratio Sn = N / (of the total number of second half position data (M + N). M + N).

  And the control part 13 calculates | requires the average value Sm_ave of Sm calculated | required about each trial, and calculates | requires the average value Sn_ave of Sn calculated | required about each trial. The control unit 13 determines the obtained average value Sm_ave as the data number ratio of the first half part, and determines the obtained average value Sn_ave as the data number ratio of the second half part. In addition, the control part 13 may obtain | require an integer value as data ratio (%), and may obtain | require it to 1 decimal place.

  A specific calculation method will be described with reference to FIG.

  FIG. 5 shows each frame image of a crossing operation of a certain trial technique. The first half is 5 frames (that is, the number M of the first half position data is 5), and the second half is 7 frames (that is, the second half position data). N is 7).

  Table 1 shows an example of calculation when the number of attempts is 3, and the data of attempt 1 is the value shown in FIG. From Table 1, the data number ratio of the first half position data is (5/12 + 6/13 + 6/12) /3≈0.46, and the second half position data ratio is (7/12 + 7/13 + 6/12) /3≈0.54. Become.

(Standardization procedure 2)
Next, with respect to the time series data of each trial, the synchronization adjustment is performed so that the ratio of the number of the first half position data and the number of the second half position data is the same as the data number ratio obtained in the procedure 1. .

  Specifically, the control unit 13 specifies the largest number of data (hereinafter referred to as the maximum number of first half data) among the number of first half position data of each trial. Further, the control unit 13 specifies the largest number of data (hereinafter referred to as the maximum number of second half data) among the number of second half position data of each trial. Then, the control unit 13 sets a reference first half data number and a reference second half data number that satisfy the following condition A.

  Condition A: The ratio of the number of first half data and the number of second half data to the total of the number of first half data and the number of second half data matches the ratio of the number of data in the first half and the second half obtained in step 1, and The reference first half data number and the reference second half data number are integers greater than or equal to the maximum first half data number and the maximum second half data number, respectively.

  Specifically, with respect to Table 1, the maximum number of first half data is 6, the maximum number of second half data is 7, and the ratio of the number of first half data and the number of second half data is 0.46: 0.54 = 23: 27. Thus, 23 (> 6) is obtained as the reference first half data number, and 27 (> 7) is obtained as the reference second half data number.

  That is, the control unit 13 is equal to or greater than the maximum number of first half data, and the ratio of the reference first half data number to the sum of the reference first half data number and the reference second half data number is the first half portion data number ratio obtained in step 1. The number of matches is calculated, and the smallest integer is set as the reference first half data number. Similarly, the control unit 13 also sets the reference second half data number. Here, “matching” includes not only the case where they completely match, but also the case where they slightly deviate from the data number ratio obtained in the procedure 1. For example, when the data number ratio is calculated up to one digit after the decimal point, it may be “matched” even when it is within ± 0.5% of the reference ratio.

  The control unit 13 may set the reference first half data number and the reference second half data number based on the information input to the input unit 11. In this case, the operator sets the number of reference data that is equal to or greater than the maximum number of data for the input unit 11 as close to the number of trial data as possible in relation to the time ratio of each aspect. Judgment should be made so as to be a numerical value.

  For the time series data of each trial, the number of position data from the start of the crossing to the end of the first half becomes the reference first half data number, and the number of position data from the end of the first half to the end of the crossing becomes the reference second half data number. As described above, the synchronization adjustment is performed by the primary interpolation formula.

  Specifically, the elapsed time from the start of the crossing is obtained for each of the first half position data of the time series data of each trial. The elapsed time can be easily obtained from the measurement interval of the position data and the order of the frame images corresponding to the position data. For example, when an image of 100 frames per second is taken, the position data measurement interval is 0.01 seconds, and when it is the fifth position data from the start of the crossing, from the start of the crossing corresponding to the position data. The elapsed time is 0.01 × (5-1) = 0.04 seconds. Next, when the elapsed time from the start of the crossing to the end of the first half is divided by (number of reference first half data −1) as the reference sampling interval, the time when the reference sampling interval × n has elapsed from the start of the crossing Is the synchronization timing. However, n is an integer from 0 to (reference first half data number −1). Then, with respect to the first half position data of each trial, the position data at the synchronization timing is obtained by the primary interpolation formula, and the position data after the synchronization adjustment is generated.

  FIG. 6 is a diagram schematically illustrating a synchronization adjustment method. In FIG. 6, (a) shows the synchronization timing obtained from the reference first half data number. (C) has shown the measurement timing about the first half position data of each trial. And (b) has shown the first half position data after carrying out synchronous adjustment.

  When the elapsed time from the start of the crossing of the first half position data for each trial is different from the synchronization timing, synchronization adjustment is performed using this temporal difference. For each synchronization timing TM, the first half position data Y (A) of the elapsed time A immediately before the TM and the first half position data Y (B) of the elapsed time B immediately after the TM are specified. Then, the first half position data Y (TM) at the synchronization timing is obtained according to the following equation.

  When there is no first half position data having the same elapsed time as the synchronization timing, the first half position data at the synchronization timing is obtained as described above. Similarly, the synchronization timing of the latter half position data is determined (in this case, when the time of the reference sampling interval × n has elapsed since the end of the first half: n is an integer from 0 to (reference latter half data number−1)). Then, the latter half position data at the synchronization timing is obtained.

  Then, the first half position data of the synchronization timing obtained in this way is arranged in order of the elapsed time of the synchronization timing. Thereafter, the second half position data of the synchronization timing is arranged in the order of the elapsed time of the synchronization timing. At this time, the data number of the position data at the start of the crossing is the first, and a data number is assigned to each position data in the order in which they are arranged. The data including the position data arranged in this way and the corresponding data number is defined as synchronized adjusted time series data (converted time series data).

  The above synchronous adjustment processing is executed for the position data of each trial. As a result, in the synchronized and adjusted time series data of each trial, the number of position data in the first half part becomes the reference first half data number, and the number of position data in the second half part becomes the reference second half data number. In the synchronously adjusted time series data for all trials, the position data whose data number is the number of reference first half data is the position data at the end of the first half.

  In this manner, the control unit 13 sets integers that satisfy the condition A as the reference first half data number and the reference second half data number. As described above, in the technique described in Non-Patent Document 2, the number of data serving as a reference for standardizing the data of all trials is obtained by averaging the time ratio of each aspect with respect to the entire operation time. With the method alone, the number of raw data of trials may be larger than the number of reference data. In such a case, the theoretical formula cannot be solved and the data cannot be standardized by synchronous adjustment. However, according to the present embodiment, as described above, since the integer satisfying the condition A is set as the reference first half data number and the reference second half data number, the raw data of each aspect of the first half portion and the second half portion is set in all trials. The number of data is greater than the maximum number of first half data and the maximum number of second half data, respectively. As a result, for the synchronized and adjusted time-series data of each trial, data conversion can be easily performed so that the number of data in the first half and the latter half becomes the reference data number by using primary interpolation. That is, it is possible to easily standardize the number of data of all attempts. Such an effect is an unprecedented effect.

(Procedure 4: Data averaging process)
The synchronized and adjusted time-series data of each trial obtained by the standardization process all include the same number of position data. And the control part 13 calculates | requires the average value of the positional data corresponding to the said data number for every data number about all the trial techniques, and produces the average time series data which arranged the said average value according to the data number. And the control part 13 is a screen which shows the time change of the position of the specific body part which represented the average value corresponding to the said data number at a fixed interval according to the order of the data number based on the created average time series data. Is displayed on the display 12. Thereby, the control part 13 can display the change of a position, ie, an average locus | trajectory, on the display 12 based on the produced average time series data. Thereby, the position data of all attempts can be shown together.

  At this time, the control part 13 should just show a horizontal axis as a data number, and a vertical axis | shaft as an average value of position data.

  Further, the interval between adjacent data numbers on the horizontal axis may be constant. Thereby, the ratio of the length in the horizontal axis direction of each aspect (the first half part and the second half part in the above example) is the ratio of the number of data obtained in the procedure 1. This data ratio corresponds to the time ratio of each situation. Therefore, the time ratio of each aspect can be grasped by looking at the length of each aspect in the horizontal axis direction.

  Further, in the synchronously adjusted time series data for all trials, the position data of the data number of the reference first half data number is the position data at the end of the first half. For this reason, the average value of the position data corresponding to the data number accurately indicates the sum of the position data at the end of the first half of all trials. That is, the position data at the end of the first half, which is the attention motion point, can be shown without changing.

  In the above description, the waist has been described as a specific body part. However, the present invention is not limited to this, and a plurality of body parts (fingertip, wrist, head, both elbows, both shoulders, chest, both knees, both ankles, toes, Etc.), normalization averaging processing may be performed. In this case, the control unit 13 may create and display a stick picture by connecting the positions of the body parts averaged for each data number with line segments. This makes it possible to represent an average action form for the whole body.

  FIG. 7 is a diagram illustrating the attacking action of a first-class volleyball player. The hitting action is divided into three phases: backswing time from the time of takeoff to the end of the backswing, fore swing time from the end of the backswing to the time of impact with the ball, and follow-through time from the time of impact to the time of landing. It is done. In this case, the end of backswing and the time of impact are set as the attention motion points. In the upper bar graph in FIG. 7, the black portion indicates the back swing time, the vertical line portion indicates the fore swing time, and the white portion indicates the follow-through time. The stick picture in the lower part of FIG. 7 obtains the ratio of the number of data in the three aspects of backswing time, fore swing time, and follow-through time by the method described in (Procedure 1 of normalization processing), and The trajectory of the position of 21 body parts points normalized by the method described in the procedure 2) and averaged by the method described in the above (procedure 4: data averaging process) is shown.

  As described above, the motion analysis apparatus 1 according to the present embodiment includes the control unit 13 that analyzes the motion of the athlete. Here, a series of predetermined motions including the target motion point is defined as a specific motion (for example, a crossing motion), and data indicating parameter values that change with the specific motion is analyzed data (parameter data, for example, predetermined reference coordinates). Position data of a specific body part with respect to).

Then, the control unit 13
(A) For a plurality of trials, obtain time-series data in which position data for every predetermined time in a crossing operation is arranged according to elapsed time;
(B) identifying position data corresponding to the attention motion point from the time series data;
(C) Using the identified position data as a delimiter position, the time series data is divided into a plurality of sections (here, the first half and the second half),
(D) For each trial, for each category (first half and second half), calculate the ratio of the number of position data included in the category to the total number of position data,
(E) For each category (first half and second half), calculate the average value over all attempts of the calculated ratio, set the average value as the data number ratio (reference ratio),
(F) For each category (first half and second half), specify the largest number of maximum data (maximum first half data, maximum second half data) among the number of position data of each trial,
(G) For each category (first half and second half), set the reference data number (reference first half data number, reference second half data number) that satisfies the following condition A,
Condition A: For each category (first half and second half), the number of standard data for the category is greater than or equal to the maximum number of data specified for the category, and the standard data for the category with respect to the total number of standard data for all categories The number ratio matches the data number ratio set for the category.
(H) For the time series data of each trial, the position data is converted by primary interpolation so that the number of position data of each section (first half and second half) is the number of reference data set for the section, The converted position data is arranged in order according to the elapsed time, and the synchronized adjusted time series data (converted time series data) in which each position data is associated with the data number indicating the order is created.
(I) For synchronized adjusted time series data in all trials, an average value of position data is obtained for each identical data number, average time series data in which the average value is arranged in accordance with the data number is created, and the time variation of the above parameters Is displayed on the display 12.

  As described above, the standardization / averaging method of the present embodiment can indicate the average value of various mechanical data such as position data for a plurality of subjects over time. For this reason, if you standardize and average exercise techniques or exercise techniques where most of the exercise techniques are demonstrated, the resulting average value of the exercise process is common to the movements of all subjects. It should match or approximate the movement process (movement technique). Therefore, the standardization / averaging method of this embodiment is one excellent method for investigating the exercise technique. In addition, since the standardization / averaging method of the present embodiment can organize a plurality of trials as a single exercise trial, each group between expert groups versus unskilled groups of groups. It becomes easy to compare and examine the operation.

  Further, since the position data of the target motion point does not change, the position data of the target motion point can be displayed accurately.

  Further, the number of data of each phase with the attention motion point as a boundary is set as an average value of the data number ratio of each phase in each trial. And the number of data of each situation is adjusted so that it may become the set number-of-data ratio, and the analysis object data of all the aspects are arranged in order. By displaying the data to be analyzed at regular intervals according to the order, the time ratio of each aspect can be grasped.

  The present invention is not limited to the above-described embodiments, and various modifications can be made within the scope shown in the claims. That is, embodiments obtained by combining technical means appropriately modified within the scope of the claims are also included in the technical scope of the present invention.

  Finally, each block of the motion analysis apparatus 1, in particular, the control unit 13 may be configured by hardware logic, or may be realized by software using a CPU as follows.

  That is, the motion analysis apparatus 1 includes a central processing unit (CPU) that executes instructions of a control program that implements each function, a read only memory (ROM) that stores the program, and a random access memory (RAM) that expands the program. And a storage device (recording medium) such as a memory for storing the program and various data. An object of the present invention is to provide a recording medium on which a program code (execution format program, intermediate code program, source program) of a control program of the motion analysis apparatus 1 which is software that realizes the functions described above is recorded so as to be readable by a computer. This can also be achieved by supplying the operation analysis apparatus 1 and reading and executing the program code recorded on the recording medium by the computer (or CPU or MPU).

  Examples of the recording medium include a tape system such as a magnetic tape and a cassette tape, a magnetic disk such as a floppy (registered trademark) disk / hard disk, and an optical disk such as a CD-ROM / MO / MD / DVD / CD-R. Card system such as IC card, IC card (including memory card) / optical card, or semiconductor memory system such as mask ROM / EPROM / EEPROM / flash ROM.

  The motion analysis apparatus 1 may be configured to be connectable to a communication network, and the program code may be supplied via the communication network. The communication network is not particularly limited. For example, the Internet, intranet, extranet, LAN, ISDN, VAN, CATV communication network, virtual private network, telephone line network, mobile communication network, satellite communication. A net or the like is available. Also, the transmission medium constituting the communication network is not particularly limited. For example, even in the case of wired such as IEEE 1394, USB, power line carrier, cable TV line, telephone line, ADSL line, etc., infrared rays such as IrDA and remote control, Bluetooth ( (Registered trademark), 802.11 wireless, HDR, mobile phone network, satellite line, terrestrial digital network, and the like can also be used. The present invention can also be realized in the form of a computer data signal embedded in a carrier wave in which the program code is embodied by electronic transmission.

  The motion analysis device of the present invention can be applied as a device for analyzing the motion of a player in sports such as volleyball competition.

It is a block diagram which shows the structure of the motion analysis apparatus which concerns on this invention. It is a figure which shows each operation | movement aspect of the attack in a volleyball game. The movement of the attacking player during volleyball competition is shown by the position of the center of gravity of the body. It is a figure which shows the procedure of the coordinate transformation in a crossing operation | movement which is a part of attack operation | movement of a volleyball game. It is a figure which shows each frame image of the level crossing operation of Trial Technique 1. It is a figure which illustrates the method of synchronous adjustment typically. It is a figure which shows the hit | damage operation | movement of an attack of a volleyball player. It is the graph which showed the ground half force during jumping operation by three subjects.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Motion analysis apparatus 2 Camera 11 Input part 12 Display (display part)
13 Control unit 14 Storage unit

Claims (6)

A motion analysis device including a control unit for analyzing the motion of a sports player,
A series of predetermined actions including the target action point is designated as a specific action,
When data indicating the value of a parameter that changes with the specific operation is used as parameter data,
The control unit
(A) For a plurality of attempts, obtain time-series data in which parameter data for each predetermined time in the specific operation is arranged according to elapsed time;
(B) From the time series data, parameter data corresponding to the target action point is specified as target parameter data;
(C) Using the parameter data of interest as a delimiter position, the time series data is divided into a plurality of sections;
(D) For each trial, for each category, calculate the ratio of the number of parameter data included in the category to the total number of parameter data,
(E) For each category, calculate the average value over all attempts of the calculated ratio, set the average value as the reference ratio,
(F) For each category, specify the largest number of data among the number of parameter data for each trial,
(G) For each category, set the number of reference data satisfying the following condition A,
Condition A: For each category, the number of reference data for the category is greater than or equal to the maximum number of data specified for the category, and the ratio of the number of reference data for the category to the total number of reference data for all categories is Matches the reference percentage set for
(H) For the time series data of each trial, the parameter data is converted by primary interpolation so that the number of parameter data of each section becomes the reference data number set for the section, and the converted parameter data passes. Arrange in order according to time, create converted time-series data in which each parameter data is associated with a number indicating the order,
(I) For the converted time series data in all trials, obtain the average value of the parameter data for each identical number, create the average time series data in which the average value is arranged according to the number, and based on the average time series data, Display a screen showing the temporal change of the parameter on the display unit;
A motion analysis apparatus characterized by that.   The motion analysis apparatus according to claim 1, wherein the control unit displays, as the screen, a screen that represents the average value at a predetermined interval in the order of the numbers. The above athlete is a volleyball player,
The motion analysis apparatus according to claim 1, wherein the parameter data is position data indicating position coordinates of a specific body part of the volleyball player with respect to a predetermined reference axis. A motion analysis method in a motion analysis device including a control unit for analyzing a motion of a sports player,
A series of predetermined actions including the target action point is designated as a specific action,
When data indicating the value of a parameter that changes with the specific operation is used as parameter data,
(A) For the plurality of attempts, the control unit obtains time series data in which parameter data for each predetermined time in the specific operation is arranged according to elapsed time;
(B) the control unit specifying parameter data corresponding to the target action point as target parameter data from the time series data;
(C) The control unit divides the time-series data into a plurality of sections using the parameter data of interest as a delimiter position;
(D) For each trial, the control unit calculates a ratio of the number of parameter data included in the section to the number of all parameter data for each section;
(E) The control unit obtains an average value over all attempts of the calculated ratio for each category, and sets the average value as a reference ratio;
(F) The control unit specifies the largest number of maximum data among the number of parameter data of each trial for each category;
(G) The control unit sets a reference data number satisfying the following condition A for each section;
Condition A: For each category, the number of reference data for the category is greater than or equal to the maximum number of data specified for the category, and the ratio of the number of reference data for the category to the total number of reference data for all categories is Matches the reference percentage set for
(H) For the time series data of each trial, the control unit converts the parameter data by primary interpolation so that the number of parameter data of each section becomes the reference data number set for the section, and after the conversion Arranging the parameter data in order according to the elapsed time, creating converted time series data in which each parameter data is associated with a number indicating the order;
(I) For the converted time series data in all trials, the control unit obtains an average value of the parameter data for each identical number, creates average time series data in which the average values are arranged according to the number, and the average time series Based on the data, displaying a screen showing a temporal change of the parameter on the display unit;
A motion analysis method comprising:   An operation analysis program for causing a computer to function as the control unit of the operation analysis apparatus according to any one of claims 1 to 3.   A computer-readable recording medium on which the operation analysis program according to claim 5 is recorded.

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