Method, system, and apparatus for analyzing a sporting apparatus

• US 10,080,941 B2
• Filed: 09/08/2015
• Issued: 09/25/2018
• Est. Priority Date: 07/02/2015
• Status: Active Grant

• Current Assignee: Sumitomo Rubber Industries Limited
• Original Assignee: Sumitomo Rubber Industries Limited
• Inventors: Brekke, Dustin J., Vogler, Jay, Ripp, Patrick, Samson, Mitchell, Brunski, Jeff D., Schielke, Brian D., Carlyle, Scott A., Seagram, Phillip C., Beck, Christopher J., Miller, Eli, Bacon, Kirk D.
• Primary Examiner(s): LEGESSE, NINI F
• Application Number:
  US14/848,083
• Publication Number:
  US 20170001072A1
• Time in Patent Office: 1,113 Days
• Field of Search: 473219, 473221-224, 473409
• CPC Class Codes: A63B 2071/0647 Visualisation of executed movements
• CPC Class Codes: A63B 2071/0658 Position or arrangement of display
• CPC Class Codes: A63B 2102/02 Tennis
• CPC Class Codes: A63B 2102/06 Squash
• CPC Class Codes: A63B 2102/065 Racketball
• CPC Class Codes: A63B 2102/14 Lacrosse
• CPC Class Codes: A63B 2102/16 Table tennis
• CPC Class Codes: A63B 2102/32 Golf
• CPC Class Codes: A63B 2220/13 Relative positions
• CPC Class Codes: A63B 2220/16 Angular positions
• CPC Class Codes: A63B 2220/34 Angular speed
• CPC Class Codes: A63B 2220/44 Angular acceleration
• CPC Class Codes: A63B 2225/20 with means for remote communication, e.g. internet or the like
• CPC Class Codes: A63B 2225/50 Wireless data transmission, e.g. by radio transmitters or telemetry
• CPC Class Codes: A63B 2225/54 Transponders, e.g. RFID
• CPC Class Codes: A63B 60/46 Measurement devices associated with golf clubs, bats, rackets or the like for measuring physical parameters relating to sporting activity, e.g. baseball bats with impact indicators or bracelets for measuring the golf swing
• CPC Class Codes: A63B 71/0622 Visual, audio or audio-visual systems for entertaining, instructing or motivating the user
• CPC Class Codes: G01S 19/19 Sporting applications
• CPC Class Codes: G06F 2218/08 Feature extraction
• CPC Class Codes: G06F 2218/12 Classification; Matching
• CPC Class Codes: G06V 40/23 : Recognition of whole body movements, e.g. for sport training
• CPC Class Codes: G16H 20/30 : relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising

Abstract

The present application is direction to a computing device having a memory and a processor. The processor is configured to receive data generated in response to a motion of a sporting apparatus, where the data includes a first data relating to a first characteristic of the motion of the sporting apparatus. The first data is based on a comparison between at least two different directional segments of a path created by a first location on the sporting apparatus during the motion of the sporting apparatus. The processor is further configured to analyze the data to determine a skill value, determine a recommended sporting apparatus from a group of at least two sporting apparatuses based on the skill value; and transmit information relating to the recommended sporting apparatus.

Claims

1. A method comprising:

(a) detecting, using an electronic position sensor, user-specific swing data comprising three-dimensional position data of a location on a reference golf club detected at points of time throughout a test swing of a specific user;

(b) receiving the swing data using a processor;

(c) obtaining rules that identify user skill values based on comparisons between first values of a first spatial attribute of a first swing segment and second values of a second spatial attribute of a second swing segment that is different from the first segment, the comparisons identified as correlative of skill value with an acceptable degree of predictiveness;

(d) identifying, based on at least the user-specific swing data, a first user-specific value corresponding to the first spatial attribute and a second user-specific value corresponding to the second spatial attribute;

(e) determining a user skill value based on the user-specific first and second values and on the rules obtained in step (c);

(f) retrieving recommended skill values associated with each of a plurality of golf clubs from a database;

(g) based on the user skill value and the recommended skill values retrieved in step (f), transmitting a recommendation of at least one of the plurality of golf clubs.

2. The method of claim 1, wherein step (e) further comprises determining the user skill value by applying the second user-specific value to an algorithm generated based on correlations between empirical skill value data and empirical motion characteristic data.

3. A method for analyzing a reference golf club, the method comprising the steps of:

(a) generating an algorithm based on correlations between empirical skill value data and empirical spatial characteristic data, the algorithm being configured to receive at least one user-specific value and calculate a user skill value;

(b) receiving, from a sensor device, swing data of a specific user'"'"'s swing of the reference golf club, the swing data including three-dimensional position data of a location on the reference golf club detected throughout the swing;

(c) calculating based on at least the three-dimensional position data, a user-specific value representative of a relationship between a first value of a spatial characteristic attributable to a first golf swing portion and second value of the spatial characteristic attributable to a second golf swing portion;

(d) determining the user skill value from the user-specific value by applying the user-specific value to the algorithm;

(e) determining that the user skill value corresponds to at least one recommended skill value associated with a recommended golf club from a group of at least two golf clubs; and

(f) transmitting information relating to the recommended golf club.

4. The method recited in claim 3, wherein:

step (a) further comprises generating the algorithm based on correlations between the empirical skill value data and empirical motion characteristic data;

step (b) further comprises calculating a second user specific value representative of a motion characteristic of the second golf swing portion; and

step (c) further comprises determining the user skill value from the second user-specific value by applying the second user-specific value to the algorithm.

5. The method recited in claim 3, wherein the algorithm is generated using a least squares regression analysis.

6. The method recited in claim 3, wherein step (e) comprises:

comparing the user skill value to the recommended skill value associated with the at least two golf clubs from the group; and

outputting, as the recommended golf club, the golf club from the group that has the recommended skill value that most closely matches the user skill value.

7. The method recited in claim 3, wherein step (e) comprises:

determining at least one of a recommended loft of a club head and a recommended shaft flex of a shaft of the recommended golf club; and

transmitting the at least one of the recommended loft and the recommended shaft flex along with the information relating to the recommended golf club.

8. A method comprising:

(a) receiving swing data of a specific user'"'"'s swing of a reference golf club generated by a sensor device associated with the reference golf club, the swing data including three-dimensional position data of a location on the referenced golf club detected throughout the swing;

(b) calculating, based on at least the three-dimensional position data, a user-specific value representative of a relationship between a first value of a spatial characteristic attributable to a backswing portion of the swing a second value of the spatial characteristic attributable to the downswing portion of the swing;

(c) determining a user skill value from the user-specific value by applying the user-specific value to an algorithm, the algorithm generated based on correlations between empirical skill value data and empirical spatial characteristic data;

(d) retrieving recommended skill values associated with each of a plurality of golf clubs from a database;

(e) determining at least one of the recommended skill values from the database is similar to the user skill value; and

(f) transmitting information relating to the at least one of the golf clubs having the recommended skill value similar to the user skill value.

9. The method of claim 8, wherein the spatial characteristic includes a length.

10. The method of claim 8, wherein the algorithm is generated using a least squares regression analysis.

11. The method of claim 8, wherein step (g) further comprises:

determining at least one of a recommended loft of a club head and a recommended shaft flex of a shaft of the at least one of the golf clubs; and

transmitting the at least one of the recommended loft and the recommended shaft flex along with the information relating to the at least one of the golf clubs.

12. In a system implementing a reference golf club comprising a shaft, a grip, and a club head, a sensor device attached to at least one of the shaft, the grip, and the club head, and a computing device, a method comprising:

(a) receiving swing data of a specific user'"'"'s swing of the reference golf club, the swing data including three-dimensional position data of a location on the reference golf club detected throughout the swing;

(b) calculating, based on at least the three-dimensional position data, a user-specific value for a length ratio, the length ratio comprising a relationship between a first value for a length of a backswing segment of the swing and a second value for a length of a downswing segment of the swing;

(c) determining a user skill value from the user-specific value by applying the user-specific value to an algorithm, the algorithm generated based on correlations between empirical skill value data and empirical length ratio data;

(e) determining a recommended golf club from a group of at least two golf clubs based on the user skill value; and

(f) transmitting, by the computing device, information relating to the recommended golf club.

13. The method recited in claim 12, wherein the position data is captured by:

projecting a three-dimensional vector onto the location on the reference golf club; and

recording at least one of orientation, velocity, and location data of the three-dimensional vector through the swing of the reference golf club.