JP6554158B2 - Swing analysis device - Google Patents

Description

  The present invention relates to a swing analysis apparatus, method, and program for analyzing a swing of a hitting tool such as a golf swing.

  Conventionally, various methods for measuring a swing of a hitting tool such as a golf swing with a measuring device and analyzing the same have been proposed. For example, Non-Patent Document 1 shows a stick diagram in which coordinates of various observation points of a golfer's body during a golf swing are measured and these observation points are connected at a specific time. From the stick diagram, the posture of the golfer can be read, and the difference in swing among the golfers is evaluated by comparing the stick diagrams of a plurality of golfers. Further, Non-Patent Document 1 includes the difference between the x and y coordinates of various observation points of the golfer's body at a specific time and the same coordinates at the time when the head speed is the fastest during a golf swing. It is also disclosed to create a matrix that performs the singular value decomposition. Then, such singular value decomposition is performed for various times, and the characteristics of the golfer are determined from the maximum singular values at the respective times.

Kishi Shibata, et al., "Dynamics and Motion Control of Golf Swing (1st Report)-Construction of Evaluation Model Representing Golf Swing", Journal of Precision Engineering, 2002, Vol. 68, no. 3, pp. 397-402

  By the way, the swing of the hitting tool by the player is a complex operation including various behaviors. For example, a golf swing is an operation that combines various behaviors such as swinging and swinging of an arm, rotation of the waist, and parallel movement of the body. The stick diagram in Non-Patent Document 1 represents a combined action in which various behaviors are combined. However, simply observing the entire combined action in this way cannot always accurately capture the swing characteristics. .

  An object of the present invention is to make it possible to more accurately capture swing characteristics by individually evaluating behaviors included in the swing.

  The swing analysis device according to the first aspect includes a data acquisition unit that acquires time-series behavior data representing a time-series behavior when the player swings the hitting tool, and mode-expanding the time-series behavior data, A mode expansion unit that decomposes the behavior into characteristic behaviors.

  A swing analysis apparatus according to a second aspect is the swing analysis apparatus according to the first aspect, wherein the mode expansion unit uses the time series behavior data so that a time average of the time series behavior data approaches a reference behavior. Pseudo extension data that is pseudo-expanded is created, and the pseudo extension data is mode-expanded to decompose the behavior into the characteristic behavior.

  The swing analysis device according to a third aspect is the swing analysis device according to the second aspect, wherein the mode expansion unit creates additional data based on the time series behavior data, and adds the additional data to the time series behavior data. The pseudo extended data is created by combining the data.

  The swing analysis device according to a fourth aspect is the swing analysis device according to the third aspect, wherein the mode expansion unit reverses the at least part of data included in the time-series behavior data to obtain the additional data. Create

  The swing analysis device according to a fifth aspect is the swing analysis device according to the third aspect or the fourth aspect, wherein the mode expansion unit combines the additional data with the time-series behavior data such that both are continuous. .

  A swing analyzing apparatus according to a sixth aspect is the swing analyzing apparatus according to any one of the second to fifth aspects, wherein the hitting tool is a golf club. The reference behavior is one of address, impact, and top behavior.

  The swing analysis device according to a seventh aspect is the swing analysis device according to any one of the second to sixth aspects, wherein the mode expansion unit is a difference between the pseudo expanded data and the time average of the pseudo expanded data. Singular value decomposition.

  The swing analysis device according to an eighth aspect is the swing analysis device according to any one of the first aspect to the sixth aspect, wherein the mode expanding unit performs mode expansion by singular value decomposition or Fourier analysis of the time series behavior data. Do.

  The swing analysis device according to a ninth aspect is the swing analysis device according to any one of the first to eighth aspects, and further includes an analysis unit that analyzes the swing based on the result of the mode expansion.

  The swing analysis device according to a tenth aspect is the swing analysis device according to any one of the first to ninth aspects, wherein the time series behavior data is at least one observation of at least one of the player and the hitting tool. This is any data of point position, velocity, acceleration, angular velocity, angular acceleration, force and torque.

  A swing analysis apparatus according to an eleventh aspect is the swing analysis apparatus according to any one of the first to tenth aspects, and further includes a screen creation unit that creates a screen that displays the characteristic behavior.

The swing analysis method according to the twelfth aspect includes the following steps.
(1) A step of acquiring time-series behavior data representing the behavior when the player swings the hitting tool in time series.
(2) A step of decomposing the behavior into a characteristic behavior by mode-expanding the time-series behavior data.
(3) A step of analyzing a swing based on the result of the mode expansion.

The swing analysis program according to the thirteenth aspect causes the computer to execute the following steps.
(1) A step of acquiring time-series behavior data representing the behavior when the player swings the hitting tool in time series.
(2) A step of decomposing the behavior into a characteristic behavior by mode-expanding the time-series behavior data.

  According to the above viewpoint, the behavior when the player swings the hitting tool is decomposed into characteristic behaviors by mode-expanding time-series behavior data representing this in time series. Therefore, the behavior included in the swing can be individually evaluated, and as a result, the characteristic of the swing can be grasped more accurately.

1 is a functional block diagram showing the overall configuration of a swing analysis system including a swing analysis device according to an embodiment of the present invention. The figure which shows the position of the marker attached to the body of a golfer. The flowchart which shows the flow of the swing analysis method which concerns on one Embodiment of this invention. (A) Stick diagram showing time average of time-series behavior data. (B) A stick diagram representing the time average of pseudo-extended data. The conceptual diagram showing the relationship between the time-sequential behavior data and pseudo extended data when the average behavior is brought close to the behavior at the time of addressing. The graph of the contribution rate from the 1st mode to the 5th mode based on measurement data of actual golf swing, and a cumulative contribution rate. The comparison figure of the stick diagram before mode decomposition and the stick diagram of the 1st mode. FIG. 4 is a comparison diagram between a stick diagram before mode decomposition and a stick diagram in first and second modes. The comparison figure of the stick diagram before mode decomposition and the stick diagram of the 1st-the 3rd mode. The comparison figure of the stick diagram before mode decomposition and the stick diagram of the 1st-the 4th mode. FIG. 6 is a comparison diagram of a stick diagram before mode decomposition and a stick diagram of first to fifth modes. The comparison figure of the stick diagram of the 1st mode when swinging the golf club from which weight differs. The comparison figure of the stick diagram of the 1st and 2nd mode when swinging the golf club from which weight differs. The comparison figure of the stick diagram of the 1st-3rd mode when swinging the golf club from which weight differs. The comparison figure of the stick diagram of the 1st-4th mode when swinging the golf club from which weight differs. The comparison figure of the stick diagram of the 1st-5th mode when swinging the golf club from which weight differs. The conceptual diagram showing the relationship between the time-sequential behavior data and pseudo expansion data when the average behavior is close to the behavior at the top. The conceptual diagram showing the relationship between the time-sequential behavior data and pseudo expansion data when an average behavior is brought close to the behavior at the time of impact.

  Hereinafter, a swing analysis apparatus, method, and program according to an embodiment of the present invention will be described with reference to the drawings.

<1. Outline of Swing Analysis System>
FIG. 1 shows an overall configuration diagram of a swing analysis system 100 including a swing analysis apparatus 1 according to the present embodiment. The swing analysis system 100 is a system for analyzing a golf swing. A golf swing is a complex motion that includes various behaviors, and is configured by combining various behaviors such as, for example, swinging up and swinging down of an arm, rotation of a waist, and translation of a body. The swing analysis system 100 individually evaluates such characteristic behaviors included in the golf swing so that the characteristics of the golf swing can be captured more accurately. More specifically, the golf swing is decomposed into characteristic behaviors by mode-expanding time-series behavior data representing the behavior of various observation points when the golfer swings the golf club in time series. The user can understand the characteristic behavior included in the golf swing based on the results of the above mode development, and in turn can understand the characteristics of the golfer, the characteristics of the golf club, and the like. In addition, a user here is a general term for a golfer himself or his instructor, a fitter for fitting a golf club suitable for the golfer, a golf club developer, or the like who needs a result of golf swing analysis. .

  The time-series behavior data that is the target of mode expansion is acquired based on the measurement data measured by the measuring device 2. The measuring device 2 constitutes a swing analysis system 100 together with the swing analysis device 1. Hereinafter, after describing the configuration of each part of the swing analysis system 100, a swing analysis method by the swing analysis system 100 will be described.

<2. Details of each part>
<2-1. Measuring equipment>
The measuring device 2 according to the present embodiment is a motion capture system including a plurality of cameras 21, 21,. As the motion capture system, for example, a three-dimensional motion analysis system manufactured by VICON can be preferably used. The multiple cameras 21, 21,... Are arranged at positions that allow the golfer to take a picture of the golf club swinging from various directions so that three-dimensional measurement of the golfer's body movement is possible. Is done.

  In this embodiment, a marker is attached to the position of the observation point so that the behavior of the observation point in the golfer's body can be easily captured by the cameras 21, 21,. More specifically, as shown in FIG. 2, light is reflected at the positions of 53 observation points such as the golfer's 7 head, wrist, fingertip, elbow, shoulder, waist, knee, heel, and legtip. Sex sphere markers 20, 20,... Are attached. In this example, the markers 20, 20,... Are attached to the body suit worn by the golfer 7.

  While the golfer 7 performs a golf swing using the golf club, the cameras 21, 21,... Continuously photograph the state at a predetermined sampling frequency. The sampling frequency can be 500 Hz, for example. In the present embodiment, the golf swing is measured in a period from at least the address, back 9 o'clock, top, down 9 o'clock, impact, and follow 3 o'clock. Note that the back 9 o'clock is the timing when the golf club points to the 9 o'clock direction of the watch during the back swing when the golfer 7 is viewed from the front, and the down 9 o'clock is during the down swing when viewed from the same direction. The timing at which the golf club points to the 9 o'clock direction of the watch is the timing at which the follow 3 o'clock refers to the timing at which the golf club points to the 3 o'clock direction of the watch during the follow swing after impact as seen from the same direction. In other words, in this embodiment, time-series image data from at least the address to the follow-up 3 o'clock is taken as measurement data by the measuring device 2. The shooting by the cameras 21, 21, ... is synchronized, and a golf swing seen from various directions at the same time is shot.

  Although not shown in particular, the measuring instrument 2 analyzes image data captured by the cameras 21, 21,... As well as the cameras 21, 21,. A communication device for transmitting to the device 1 is also mounted. The communication device can be wireless so as not to hinder the swing operation, or can be connected to the swing analysis device 1 in a wired manner via a cable. In the present embodiment, image data captured by the cameras 21, 21,... Is transmitted to the swing analysis device 1 in real time via the communication device. However, for example, image data is stored in a storage device in the camera 21, 21,..., And the image data is taken out from the storage device after the end of the golf swing and delivered to the swing analysis device 1. It is also good.

2-2. Swing analysis device>
The swing analysis device 1 is a general-purpose computer as hardware, and is realized as, for example, a desktop computer, a notebook computer, a tablet computer, or a smartphone. As shown in FIG. 1, the swing analysis device 1 installs the swing analysis program 6 in a general-purpose computer from a recording medium 30 such as a computer readable CD-ROM or via a communication line such as the Internet. Manufactured. The swing analysis program 6 is software for analyzing a golf swing based on measurement data sent from the measuring device 2 and causes the swing analysis device 1 to execute an operation to be described later.

  The swing analysis apparatus 1 includes a display unit 11, an input unit 12, a storage unit 13, a control unit 14, and a communication unit 15. These units 11 to 15 are connected to each other via the bus line 16 and can communicate with each other. The display part 11 can be comprised with a liquid crystal display etc., and displays the analysis result etc. of a golf swing with respect to a user. The input unit 12 can be configured with a mouse, a keyboard, a touch panel, and the like, and accepts an operation from the user for the swing analysis apparatus 1.

  The storage unit 13 can be configured with a hard disk or the like. In the storage unit 13, the swing analysis program 6 is stored, and measurement data sent from the measuring device 2 is stored. The control part 14 can be comprised from CPU, ROM, RAM, etc. The control unit 14 virtually operates as the data acquisition unit 14a, the mode development unit 14b, the screen creation unit 14c, and the analysis unit 14d by reading and executing the swing analysis program 6 in the storage unit 13. Details of the operations of the units 14a to 14d will be described later. The communication unit 15 functions as a communication interface that transmits and receives data to and from an external device such as the measuring device 2.

<3. Swing analysis method>
Hereinafter, a swing analysis method by the swing analysis system 100 will be described. In this method, a golf swing by the golfer 7 is measured, and this mode is developed and decomposed into various characteristic behaviors. The method is used to understand the characteristics of a golf swing in the context of golf lessons, fitting a golf club to a golfer, developing a golf club, and the like. The details will be described below.

  FIG. 3 is a flowchart showing the flow of the swing analysis method according to the present embodiment. As shown in the figure, in the first step S1, a golf club is prepared and the golf club 7 swings the golf club. At this time, measurement by the measuring device 2 is performed, and measurement data representing a state in which the golfer 7 swings the golf club is collected. The measurement data according to the present embodiment is time-series image data captured by the cameras 21, 21,... During the period from the address to the follow-up 3 o'clock as described above. Note that the measurement data here includes time series image data of a plurality of series respectively corresponding to the shooting directions of the plurality of cameras 21, 21,. Measurement data measured by the measuring device 2 is transmitted from the communication device to the swing analysis device 1. On the swing analysis device 1 side, the data acquisition unit 14 a acquires the measurement data via the communication unit 15 and stores it in the storage unit 13.

  In the following step S2, the data acquisition unit 14a derives time-series behavior data representing behavior when the golfer 7 swings a golf club based on measurement data from the measurement device 2 in time series. More specifically, the data acquisition unit 14a performs image processing on the image data included in the measurement data, thereby detecting the images of the markers 20, 20,. The images of the markers 20, 20,... Are detected from a plurality of shooting directions, and their positions are specified as three-dimensional coordinates. The three-dimensional coordinates of the markers 20, 20, ..., that is, the three-dimensional coordinates of 53 observation points of the body of the golfer 7, are each in the time interval corresponding to the sampling frequency in the period from the address to the follow 3 o'clock It is derived for time.

In other words, in step S2, for n = 1, 2,..., N (N is an integer of 2 or more) and i = 1, 2,. Three-dimensional coordinates r _i (n) of the observation point are derived. The first time is the address, and the Nth time is the follow 3 o'clock.

In the above equation, x _i (n), y _i (n), and z _i (n) are X, Y, and Z direction components of r _i (n), respectively. The X, Y and Z directions are defined as shown in FIG. That is, the X direction is a direction from the back to the belly of the golf player 7, the Y direction is a flying line direction, and the Z axis is a direction from the bottom to the top. r _i (n) is a position vector of the ith observation point at the nth time.

Now, for the ith observation point, the following matrix [r _i ] is defined. Matrix [r _i] is a matrix of N rows and three columns, the first N rows from the first row, in order along the time series, the three-dimensional coordinate _{r i (1), r i} (2), ··· , R _i (N).

Furthermore, a matrix [R] is defined in which 53 matrices [r ₁ ], [r ₂ ],..., [R ₅₃ ] for all observation points are arranged in this order in the column direction (horizontal direction). The matrix [R] is a matrix of N rows and 159 (= 3 × 53) columns.

  The matrix [R] is time-series behavior data representing the behavior (positions) of 53 observation points from the first time to the N-th time in time series. In step S2, a matrix [R] that is such time-series behavior data is derived. Since the n th row of [R] includes the three-dimensional coordinates of 53 observation points in the golfer 7's body at the n th time, the n th row of [R] is the golfer of the n th time 7 postures.

In the subsequent steps S3 and S4, the golf swing represented by the time-series behavior data [R] is decomposed into the characteristic behavior by performing mode expansion of the time-series behavior data [R] of step S2. More precisely, pseudo-expansion data [R _a ] that is pseudo-expansion of time-series behavior data [R] is created, and this is mode expanded. A golf swing is an aperiodic movement. Therefore, in the present embodiment, the analysis is executed by regarding the golf swing as a pseudo periodic motion by mode-expanding the pseudo extended data [R _a ] obtained by duplicating and synthesizing the golf swing. As a method of mode expansion, singular value decomposition is used in this embodiment.

In step S3, the mode expansion unit 14b creates pseudo-expanded data [R _a ] based on the time-series behavior data [R] such that the time average approaches the reference behavior. The pseudo extended data [R _a ] is created to bring the reference point of singular value decomposition closer to the reference behavior. The reference behavior is the behavior at the time of addressing in the present embodiment. FIG. 4A shows a stick line formed by connecting time averages of the positions of 53 observation points included in the time-series behavior data [R] when a golfer actually performs a golf swing. FIG. 4B is a stick diagram obtained by connecting time averages of the positions of 53 observation points included in the pseudo-expanded data [R _a ] based on the same golf swing. As can be seen from the figure, the former time average is not in the attitude of the address but in the attitude of taking back some arms. Therefore, when the time series behavior data [R] is mode-developed as it is, there is a possibility that the meaning of each mode including the first mode can not be understood with reference to the address. Therefore, in the present embodiment, pseudo extended data [R _a ] is created.

More specifically, the mode expansion unit 14b creates the following additional data [R (1)] and [R _t ] based on the time-series behavior data [R]. Now, define the one row 3-column matrix representing the three-dimensional coordinates of the i observation point at the address matrix of 2N rows and three columns arranged 2N number in the row direction (vertical direction) [r _i (1)] . At this time, [R (1)] is a matrix of 53 matrices [r ₁ (1)], [r ₂ (1)], ..., [r ₅₃ (1)] for all observation points. It is derived as a matrix of 2N rows 159 (= 3 × 53) columns arranged in the column direction (lateral direction) in order.

On the other hand, the additional data [R _t ] is derived as follows. That is, the additional data [R _t ] is a matrix obtained by inverting the time series behavior data [R] in the time series direction.

Subsequently, the mode expansion unit 14b combines the additional data [R (1)] and [R _t ] with the time-series behavior data [R] according to the following equation to create the pseudo extended data [R _a ]. .

FIG. 5 is a conceptual diagram showing the relationship between the time-series behavior data [R] and the pseudo extended data [R _a ] according to the present embodiment. That is, the additional data [R (1)] in which the behavior at the time of address is repeatedly replicated by the time length 2N is combined before time n = 1 of the address of the time-series behavior data [R]. Furthermore, additional data [R _t ] of time length N obtained by inverting time series behavior data [R] in the time series direction is combined after time n = N at 3 o'clock of time series behavior data [R], and further Thereafter, additional data [R (1)] is added. Thus, the additional data [R (1)] and [R _t ] are combined so as to be continuous with the time-series behavior data [R], and the pseudo-extended data [R _a ] thus created is continuously It becomes data whose value changes. The pseudo extended data [R _a ] is a matrix of 6N rows and 159 (= 3 × 53) columns.

In subsequent step S4, the mode expansion unit 14b performs singular value decomposition on the pseudo extended data [R _a ] according to the following expression.

[R ₀ ] in the above formula is a time average of [R _a ]. [R ₀ ] is a matrix of 6N rows and 159 (= 3 × 53) columns in which an average matrix is generated by averaging [R _a ] in the time direction (row direction), and the average matrix is arranged in 6N rows. is there. That is, the 1st column of [R ₀ ] is a value sequence in which 6N pieces of the average value of the 6N components of the 1st column of [R _a ] are arranged in the row direction. By the way, as described above, data representing the behavior at the time of addressing for a time length 4N (in the present embodiment, the posture of the golfer 7) is added to the pseudo expanded data [R _a ]. Therefore, the behavior represented by the time average [R ₀ ] of the pseudo-extended data [R _a ] is closer to the behavior at the time of addressing than the behavior represented by the similar time average of time series behavior data [R] Yes.

As described above, in this embodiment, [R _a ] − [R ₀ ], which is the difference between the pseudo expanded data [R _a ] and its time average [R ₀ ], is singular value decomposed, and j = 1, 2, ..., J (where J is an integer equal to or less than 159), λ _j , z _j and v _j are derived. λ _j is a singular value of the j-th mode and represents a ratio of the j-th mode to [R _a ] − [R ₀ ]. v _j is a left singular vector of [R _a ]-[R ₀ ] and is N-dimensional. z _j is a right singular vector of [R _a ]-[R ₀ ] and has 159 dimensions. z _j represents the excitation pattern of each observation point in the golfer's 7 body, and v _j represents the excitation pattern with respect to time of z _j .

Further, the mode expansion unit 14b reduces the contribution rate C _j which is the contribution of the j-th mode to [R _a ] based on the singular value λ _j with respect to j = 1, 2,. Derived according to

By the above singular value decomposition, the pseudo-expansion data [R _a ] representing the behavior of the golf swing as well as the time-series behavior data [R], the features corresponding to the respective modes from the first mode to the J mode included in the golf swing. Behavior is extracted. [R _j ] representing the behavior of the j-th mode is expressed by the following equation.

  In addition, although J is 159 at the maximum, it can be suitably selected according to the purpose etc. of analysis to which behavior up to what order mode is derived. FIG. 6 is a graph of contribution rates and accumulated contribution rates from the first mode to the fifth mode derived by singular value decomposition as in the above-described step based on measurement data of a golfer's golf swing. As shown in the figure, the contribution ratio of the first mode alone reaches approximately 90%, and the cumulative contribution ratio from the first mode to the fifth mode reaches 99.8%. Therefore, it can be seen that the golf swing can be generally evaluated by deriving the behavior up to the fifth mode.

Moreover, the mode expansion | deployment part 14b derives | leads-out the behavior comprised from 1st mode to kth mode with respect to k = 1,2, ..., J according to the following Formula.

In addition, the mode developing unit 14 b expresses the behavior of a single mode according to the following equation for j = 1, 2,..., J and n = 1, 2 _,. n) is derived. Note that v _j (n) indicates a time excitation pattern at each representative point in the j-th mode at the n-th time.

In the present embodiment, the steps described above are repeatedly executed for a golf swing when at least one golfer tries a different golf club a plurality of times, and pseudo extended data [R _a ] is obtained for each trial. Derived. Modal expansion unit 14b, based on the pseudo extension data [R _a] in this case, j = 1, 2, · · ·, J and,, n = 1, 2, · · ·, to the N, R _j (N) is derived, and further, postures (three-dimensional coordinates of 53 observation points) at each timing in each mode are derived from R _j (n). Then, a three-way analysis of variance is performed on the data of these postures to derive a P value indicating whether a significant difference in posture can be seen between trials due to differences in golf clubs.

In subsequent step S5, the screen creation unit 14c creates a screen (hereinafter referred to as a result screen) that displays the result of the mode development described above, and displays the screen on the display unit 11. For example, stick diagrams (side view and front view) as shown in FIGS. 7 to 11 are displayed on the result screen. These figures are a stick diagram formed by connecting 53 observation points included in [R _a ] before mode decomposition when swinging a golf club with an actual golfer, and first to kth is a diagram overlapping 53 amino a stick diagram comprised of this connecting an observation point included in the constructed [R ₁ ~ _k] mode. 7 to 11 correspond to the case of k = 1 to 5, respectively.

  When the behavior of the first mode is observed from FIG. 7, the posture at the time of address matches the posture before the mode decomposition. However, in the behavior of the first mode, the swing width of the arm is smaller than the posture before mode decomposition from 9 o'clock to 9 o'clock down, and it converges to the posture at the address from impact to 3 o'clock. . Therefore, the behavior of the first mode is considered to indicate the arm swinging and swinging motions from the address to the impact, and the leg and waist constant rotating motions.

  When observing the combined behavior of the first mode and the second mode from FIG. 8, by adding the behavior of the second mode to the behavior of the first mode, the posture of the arm from the back 9 o'clock and the arm at the follow 3 o'clock It can be seen that the posture of is close to the posture before mode decomposition. On the other hand, the posture of the arm has not changed much from 9 o'clock down to the impact. Therefore, it is considered that the behavior of the second mode does not indicate the behavior of the arm, but the rotation of the shoulder excites the behavior of the arm.

  When observing the synthetic behavior from the first mode to the third mode from FIG. 9, this synthetic behavior is partially different from the posture before mode decomposition at the timing of follow 3, but from the back swing to the down swing. It can be seen that it constitutes a golf swing. In addition, the posture of the arm from 9 o'clock down to the impact is close to the posture before the mode decomposition, and these are the ones in which the behavior of the arm is excited by pushing out (parallel movement) in the flying ball direction and rotating operation. it is conceivable that. From the above results, it is considered that the behavior in the third mode indicates the parallel movement and the rotation motion of the behavior of the hips and legs from the down swing to the follow swing.

  When observing the combined behavior of the first mode to the fourth mode from FIG. 10, the posture from the left shoulder to the arm in the impact approaches the posture before the mode decomposition by adding the behaviors of the first mode to the fourth mode. As you can see, there are no major changes in other areas. Therefore, the behavior of the fourth mode is unlikely to be excitation due to the operation of other parts. Therefore, the behavior of the fourth mode is considered to indicate the rotational movement of the shoulder and the arm near the impact.

  When observing the combined behavior from the first mode to the fifth mode from FIG. 11, it can be seen that the posture of the arm at the time of follow 3 approaches the posture before mode decomposition by adding the behaviors of the first mode to the fifth mode. However, there is no significant change in posture at other timings except at 3 o'clock. For this reason, the fifth mode is unlikely to be excited by the operation of other parts as in the fourth mode. Therefore, the behavior in the fifth mode is considered to be an arm extension movement in the follow swing.

Summarizing the above results, the behaviors of the first to fifth modes are as follows. 7 to 11 show only an example. Even if the golfers change at least between golfers of the same level, the golf clubs change at least between similar clubs. Even if it changed, the same tendency was confirmed in the behavior of each mode.

  The result screen can also display a comparison diagram of stick diagrams (side view and front view) when the same or different golfers swing different golf clubs. FIGS. 12 to 16 are stick diagrams representing the behavior of the first to kth modes when the same golfer swings golf clubs of different weights. 12 to 16 correspond to the cases where k = 1 to 5, respectively. By displaying such a diagram, the user can understand the difference in the characteristics of the golf club. For example, from FIG. 12 to FIG. 16, the position of the arm at the top for the behavior of the first mode, the position of the hand at the impact for the behavior of the second mode, and the position of the elbow at the top and impact for the behavior of the third mode As for the behavior in the fourth mode, it can be seen that there is a difference in the position of the left hand in the impact, and in the behavior in the fifth mode, there is a difference in the position of the right elbow in the impact. That is, it is possible to know at what timing in the golf swing the movement of what part changes due to the difference in the golf club. In addition, in conjunction with the knowledge shown in Table 1, these understandings can be further deepened. Such information can be preferably used in, for example, a golf club fitting scene or a golf club development scene.

  Although not particularly illustrated, a comparison diagram of stick diagrams when different golfers swing the same or different golf clubs can be displayed on the result screen. In this case as well, as in the above example, for k = 1, 2,..., J, sticks representing behaviors constituted by the first to kth modes when different golfers perform a golf swing. A diagram in which line diagrams are superimposed can be displayed. From such a stick diagram, it is possible to know the difference in golf swing between golfers. That is, it is possible to know what characteristic motion a particular golfer performs at what timing in the golf swing. In addition, in conjunction with the knowledge shown in Table 1, these understandings can be further deepened. Such information can be preferably used in, for example, a golf lesson scene or a golf club development scene. In particular, if one of the golf swings to be compared is that of an advanced player, the problem of the golf swing of the other golfer can be known.

In addition to the stick diagram, the result screen can also display the singular value λ _j and the contribution rate C _j for j = 1, 2,. Further, the cumulative contribution ratio C ₁ + C ₂ +... + C _k can be displayed for k = 1, 2,.

The result screen also displays the result of the three-way analysis of variance described above. Tables 2 and 3 below show the measurements when two golf clubs (total weights 337.1g and 314.9g) with two golfers A and B that are different only in shaft weight were tested by 7 balls each. It is a result of P value based on data. Each golfer was allowed to wear a bodysuit with 53 markers as shown in FIG. 2, and measurement data was collected by a motion capture system similar to that of the measurement device 2. The average score of the two golfers A and B was about 80. In addition, each golfer was informed of the weight of the golf club in advance, and instructed to swing similarly regardless of which golf club, and was allowed to take a break every 3 to 4 balls. In this experiment, sponge balls were used so as not to feel the sense of impact. Table 2 shows the result of the golfer A, and Table 3 shows the result of the golfer B.

  Looking at the results of Golfer A in Table 2, the results of analysis of variance in the first mode have P values of <0.05 at the address and top, and it is possible to confirm the difference in posture for each golf club. On the other hand, at back 9 o'clock, down 9 o'clock, impact and follow 3 o'clock, P value> 0.05, and no difference in posture can be seen. When considered together with the results in Table 1, it is considered that there are differences in the position of the arms and the rotation of the hips and legs at the time of address and top due to the difference in weight of the golf club.

  In the second mode, the P value <0.05 throughout, and a difference in posture for each golf club can be confirmed. When considered together with the results in Table 1, it is considered that differences in the weight of the golf club cause differences in shoulder rotation throughout the swing.

  In the third mode, the P value <0.05 at the back 9 o'clock, top, impact, and follow 3 o'clock, and the difference in posture for each golf club can be confirmed. On the other hand, at the address and down 9 o'clock, the P value> 0.05, and there is no difference in posture. From these, it is considered that there is a difference in posture between the back swing near the top and the follow swing near the impact. According to the results in Table 1, the behavior of the third mode indicates the parallel movement and rotation of the hips and legs from the down swing to the follow swing. In this respect, it can be seen from the results in Table 2 that there is a difference in the backswing near the top, but from the results in Table 1, the behavior in the backswing cannot be confirmed. This is considered to be because a difference in behavior cannot be confirmed by visual observation although a difference is statistically observed. In summary, it is considered that there is a difference in the parallel movement and rotation of the waist and legs from the down swing to the follow swing due to the difference in weight of the golf club.

  In the fourth mode, the P value <0.05 at the address, back 9 o'clock, down 9 o'clock, impact and follow 3 o'clock, and the difference in posture for each golf club can be confirmed. On the other hand, at the top, P value> 0.05, and no difference is seen in the posture. From these, it is considered that there is a difference in posture between the back swing near the address and the follow swing from near the impact. According to the results in Table 1, the behavior in the fourth mode indicates the rotational behavior of the shoulder and arm near the impact. In this respect, from the results of Table 2, although there is a statistical difference in the behavior of the address, back 9 o'clock and down 9 o'clock, the difference may not be visually confirmed as in the case of the third mode. . In summary, it is considered that differences in the rotational behavior of the shoulders and arms near the impact can be seen due to differences in the weight of the golf club.

  In the fifth mode, the P value is less than 0.05 at 9 o'clock down and 3 o'clock down, and the difference in posture between golf clubs can be confirmed. On the other hand, at the address, back 9 o'clock, top and impact, the P value> 0.05, and no difference is seen in the posture. From these, it is considered that there is a difference in posture between the downswing near the impact and the follow swing after the impact. According to the results in Table 1, the behavior in the fifth mode indicates the arm extension behavior in the follow swing. As to the behavior at 9 o'clock down, as in the third and fourth modes, although there is a statistical difference, there is a possibility that the difference can not be confirmed visually. In summary, it is considered that there is a difference in the arm extension behavior in the follow swing due to the difference in the weight of the golf club.

  Next, looking at the results of golfer B in Table 3, the results of analysis of variance in the first mode are P values <0.05 throughout, and it is possible to confirm the difference in posture for each golf club. According to the results in Table 1, the behavior of the first mode shows the swinging up and down of the arm and the rotation of the hips and legs from the address to the impact. After the impact, the behavior converges to the posture at the time of the address. . Therefore, it is considered that the P value <0.05 for the entire swing. From this result, it is considered that there is a difference in the position of the arm from the address to the impact and the rotational behavior of the waist and legs due to the difference in weight of the golf club.

  In the second mode, the P value is less than 0.05 throughout the whole, and it is possible to confirm the difference in posture between golf clubs. According to the results of Table 1, the behavior of the second mode indicates the rotational movement of the shoulder. From this result, it is considered that there is a difference in the rotation of the shoulder in the entire swing due to the difference in the weight of the golf club.

  In the third mode, the P value is less than 0.05 at the address, 9 o'clock down, impact, and 3 o'clock follow-up, and it is possible to confirm the difference in attitude between golf clubs. On the other hand, at 9 o'clock on the back and at the top, the P value is> 0.05, and there is no difference in posture. From these, it is considered that there is a difference in posture from the down swing to the follow swing. In combination with the results in Table 1, it is considered that differences in the weight of the golf club lead to differences in translational and rotational motions of the waist and legs from the downswing to the follow swing.

  In the fourth mode, the P value is less than 0.05 at the address, top, impact and three o'clock, and it is possible to confirm the difference in posture between golf clubs. On the other hand, at 9 o'clock back and 9 o'clock down, the P value is> 0.05, and there is no difference in posture. From these, it is thought that a difference will arise in attitude from top and impact to follow swing. According to the results in Table 1, the behavior of the fourth mode indicates the rotational movement of the shoulders and arms near the impact. Therefore, although there is a statistical difference in the behavior of the vicinity of the top and the follow swing, it is considered that the difference in the behavior can not be visually confirmed. In summary, it is believed that differences in the weight of the golf club lead to differences in the rotational movement of the shoulders and arms near the impact.

  In the fifth mode, P value <0.05 at the top and impact, and a difference in posture for each golf club can be confirmed. On the other hand, the P value> 0.05 at the address, back 9 o'clock, down 9 o'clock, and follow 3 o'clock, and there is no difference in posture. According to the results in Table 1, the behavior in the fifth mode is an arm extension operation in the follow swing. Therefore, with regard to the behavior of the top and the impact, although there is a statistical difference as in the fourth mode, it is considered that the difference can not be visually confirmed. In summary, it is considered that the behavior exhibited by the fifth mode does not change even when the weight of the golf club changes.

  To summarize the results of golfers A and B, both golfers change the rotational motion of the shoulder corresponding to the second mode throughout the swing, and the shoulder and leg translation and rotational motion corresponding to the third mode follow from the impact. It turns out that it is changing with the swing.

  As described above, the influence of the golf club on the golf swing of each golfer can be known from the result of the above-described three-way ANOVA. Further, by comparing the results of a plurality of golfers, it is possible to know the characteristics of the golf club itself more accurately. Therefore, according to the above method, golf clubs having different specifications such as shaft hardness, head weight and center of gravity, and length of the golf club are made to be tested by the same or different golfers. You can know the characteristics. Such information can be used preferably in scenes of golf club development, golf club fitting, and the like.

  As described above, part or all of the analysis of the swing based on the result of the mode expansion can be performed by the user or can be automated. For example, by implementing an algorithm in accordance with the above determination criteria by software, the control unit 14 can be virtually operated as an analysis unit 14d that performs a swing analysis based on the result of mode expansion.

<4. Modified example>
As mentioned above, although one Embodiment of this invention was described, this invention is not limited to the said embodiment, A various change is possible unless it deviates from the meaning. For example, the following modifications are possible. Moreover, the gist of the following modifications can be combined as appropriate.

<4-1>
The configuration of the measuring device 2 described above is an example, and the measuring device 2 may be, for example, an inertial sensor, a distance image sensor, or the like, and is selected from the group consisting of an inertial sensor, a distance image sensor, and a motion capture system Two or more devices may be arbitrarily combined.

<4-2>
In the above embodiment, the golf swing is analyzed. However, swinging tools other than the golf club, for example, a swing of a tennis racket or a baseball pad may be an analysis target.

<4-3>
In the above embodiment, the pseudo-extended data is singular value decomposed, but mode expansion may be performed by Fourier analysis to extract characteristic behavior corresponding to each mode.

<4-4>
In the above embodiment, the reference behavior is the behavior at the time of addressing. However, the reference behavior can also be other time behavior, for example impact or top behavior. For example, when the behavior at the top is used as a reference behavior, pseudo-expanded data can be created as shown in FIG. 17, and when the behavior at impact is used as a reference behavior, as shown in FIG. Pseudo extension data can be created.

<4-5>
In the above embodiment, the time-series behavior data to be subjected to the mode expansion is the data of the position of the observation point, but even the data of the observation point speed, acceleration, angular velocity, angular acceleration, force, torque, etc. It may be a combination of two or more data selected from the group consisting of these and position.

1 Swing analysis system (computer)
100 swing analysis system 14a data acquisition unit 14b mode development unit 14c screen creation unit 14d analysis unit 2 measuring device 6 swing analysis program 7 golfer

Claims (11)

A data acquisition unit for acquiring time-series behavior data representing the behavior of the player's body in time series when the player swings the hitting tool;
Included in the behavior by creating pseudo-extended data that pseudo-expands the time-series behavior data so that the time average of the time- series behavior data approaches the reference behavior, and singular value decomposition of the pseudo-extended data And a mode expansion unit for extracting characteristic behavior corresponding to each of the
Swing analysis device. The mode expansion unit creates additional data based on the time-series behavior data, and combines the additional data with the time-series behavior data to create the pseudo-extended data.
The swing analysis device according to claim 1 . The mode expansion unit creates the additional data by inverting at least a part of the data included in the time series behavior data.
The swing analysis apparatus according to claim 2 . The mode expansion unit combines the additional data with the time-series behavior data so that both are continuous.
The swing analysis apparatus according to claim 2 or 3 . The hitting tool is a golf club,
The reference behavior is any one of an address, an impact and a top behavior.
The swing analysis apparatus according to any one of claims 1 to 4 . The mode expansion unit decomposes the difference between the pseudo extended data and the time average of the pseudo extended data by singular value decomposition,
The swing analysis apparatus according to any one of claims 1 to 5 . The system further includes an analysis unit that analyzes a swing based on the result of the mode expansion.
The swing analysis apparatus according to any one of claims 1 to 6 . The time series behavior data includes at least the position of one observation point, speed, acceleration, angular velocity, angular acceleration, one of the data of the force and torque in the body of the player,
The swing analysis apparatus according to any one of claims 1 to 7 . It further comprises a screen creation unit that creates a screen that displays the characteristic behavior.
The swing analysis apparatus according to any one of claims 1 to 8 . Obtaining time-series behavior data representing a time-series behavior of the player's body when the player swings the hitting tool;
Included in the behavior by creating pseudo-extended data that pseudo-expands the time-series behavior data so that the time average of the time- series behavior data approaches the reference behavior, and singular value decomposition of the pseudo-extended data extracting a characteristic behavior for each mode
Including,
Swing analysis method. Obtaining time-series behavior data representing a time-series behavior of the player's body when the player swings the hitting tool;
Included in the behavior by creating pseudo-extended data that pseudo-expands the time-series behavior data so that the time average of the time- series behavior data approaches the reference behavior, and singular value decomposition of the pseudo-extended data Causing the computer to execute a step of extracting characteristic behavior corresponding to each of the
Swing analysis program.