Swing motion data analysis methods

Abstract

A method for analyzing golf swing data is implemented via a computing device that is communicatively connected to a sensing unit for sensing a golf swing. The computing device obtains multiple data points from the sensing unit corresponding to multiple time points to be analyzed. It then filters these data points to determine if a normal swing event exists. When a normal swing event is determined to exist, it obtains multiple processed swing data points to further obtain multiple time points. Based on these time points, the processed swing data points, and the multiple parameters, the computing device obtains multiple swing analysis data points and multiple swing suggestion data points related to the swing.

Claims

1. A method for analyzing golf swing data, implemented by a computing device communicatively connected to a sensing unit, the sensing unit being disposed on a golf club and used to sense the swing motion to generate motion data related to the swing motion, the computing device storing multiple ball parameters related to a ball, multiple swing parameters related to the swing, and multiple field parameters related to a sports field, the method comprising the following steps: (A) obtaining multiple sets of motion data to be analyzed from the sensing unit corresponding to multiple time points, wherein, Each piece of motion data to be analyzed includes a first acceleration value along a first direction, a second acceleration value along a second direction, a third acceleration value along a third direction, a first angular velocity value, and a second angular velocity value; (B) Select multiple swing motion data from the motion data to be analyzed, wherein step (B) includes the following sub-steps: (B-1) Obtain multiple first acceleration differences based on the first acceleration values; (B-2) Determine whether there is at least one candidate first acceleration difference greater than a difference threshold value among the first acceleration differences; (B-3) When it is determined that there is at least one candidate first acceleration difference, obtain a target first acceleration difference value from the at least one candidate first acceleration difference value, wherein the time points corresponding to the two first acceleration values ​​used to calculate the target first acceleration difference value are not later than the time points corresponding to the two first acceleration values ​​used to calculate other candidate first acceleration differences; (B-4) Obtain the target first acceleration value with the largest corresponding acceleration value from the two first acceleration values ​​used to calculate the target first acceleration difference; (B-5) Determine whether there are n pre-impact acceleration values ​​with a time point earlier than the target first acceleration value and m post-impact acceleration values ​​with a time point later than the target first acceleration value in the first acceleration values ​​in the motion data to be analyzed, where n and m are both positive integers; and (B-6) When it is determined that there are n pre-impact acceleration values ​​and m post-impact acceleration values, arrange the motion data to be analyzed corresponding to the n pre-impact acceleration values, the m post-impact acceleration values ​​and the target first acceleration value in chronological order to obtain the swing motion data; (C) Determine whether there is a normal swing event based on the swing motion data, wherein step (C) includes the following sub-steps: (C-1) Take the time point corresponding to the target first acceleration value as a hitting time point; (C-2) Determine whether the first angular velocity value corresponding to the point of impact is greater than zero; and (C-3) When it is determined that the first angular velocity value corresponding to the point of impact is greater than zero, determine whether there is at least one normal swing motion data among p swing motion data corresponding to time points earlier than the point of impact where both the first angular velocity value and the second angular velocity value are less than zero, where p is a positive integer not greater than n; wherein, when it is determined that the normal swing motion data exists, it is determined that the normal swing event exists; (D) When it is determined that the normal swing event exists, perform data processing on the swing motion data to obtain multiple processed swing motion data;(E) Based on the processed swing motion data, obtain multiple phase points related to the phases of the swing, wherein step (E) includes the following sub-steps: (E-1) Obtain at least one candidate starting swing motion data corresponding to an absolute value of the first acceleration value greater than a first acceleration threshold value from the processed swing motion data corresponding to a time earlier than the time of impact; (E-2) Obtain the time point corresponding to the earliest one of the at least one candidate starting swing motion data, and use that time point as a swing starting time point in the phase points; (E-3) Obtain two candidate return time points corresponding to return swing motion data corresponding to a change in the first angular velocity value from negative to positive from the processed swing motion data corresponding to a time earlier than the time of impact; (E-4) Select the one corresponding to a positive value of the first angular velocity value from the two candidate return time points, and use it as a swing return time point in the phase points; (E-5) Obtain at least one candidate end-of-swing data point corresponding to the first acceleration value being less than a second acceleration threshold value from the processed swing data, wherein the time point of the processed swing data corresponding to the maximum first acceleration value is a reference time point, and the at least one candidate end-of-swing data point is a processed swing data point corresponding to a time point later than the reference time point; and (E-6) Obtain the time point corresponding to the earliest one of the at least one candidate end-of-swing data points, and use that time point as a swing end point in the phased time points; wherein the phased time points are composed of the impact time point, the swing start time point, the swing return time point, and the swing end point; (F) Based on the time points of the periodization, the processed swing motion data, the ball parameters, the swing parameters, and the field parameters, obtain multiple swing analysis data related to the swing motion; and (G) Based on the ball parameters, the swing parameters, and the field parameters, obtain multiple swing suggestion data.

2. The swing motion data analysis method as described in claim 1, wherein, The computing device is also communicatively connected to a user display device, and after step (G), it further includes the following steps: (H) transmitting the swing analysis data and the swing suggestion data to the user display device.

3. The swing motion data analysis method as described in claim 1, wherein, Step (D) includes the following sub-steps: (D-1) When the existence of the normal swing event is determined, the swing motion data is de-noise processed to obtain multiple de-noise swing motion data; and (D-2) The de-noise swing motion data is coordinate corrected to obtain multiple corrected swing motion data as the processed swing motion data.

4. The swing motion data analysis method as described in claim 1, wherein, In step (F), the swing analysis data includes swing trajectory analysis data related to the movement trajectory of the swing, hitting force analysis data related to the force applied when the swing hits the ball, hitting speed analysis data related to the speed of the swing when it hits the ball, swing rhythm analysis data related to the time interval traversed by the swing during the swing movement, swing angle analysis data related to the angle of the swing when it hits the ball, and hitting distance analysis data related to the distance the ball travels.

5. The swing motion data analysis method as described in claim 1, wherein, In step (G), the swing recommendations include a strike force recommendation related to the recommended force applied when the swing contacts the ball and a strike velocity recommendation related to the recommended velocity applied when the swing contacts the ball.

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