Method and system for training athletes based on athletic signatures and a classification thereof
View Patent ↗A method for training athletes is disclosed. The method comprises: maintaining a classification for signatures generated based on movement data associated with athletes; wherein the movement data is stored in a database; associating guidance with each signature in the classification; and assigning a signature from the database to at least some athletes in the database.
1. A computer-implemented method for training athletes, comprising:
maintaining by a computer a classification for signatures generated based on movement data associated with athletes; wherein the movement data is stored in a database, and comprises kinematic data including normalized values for concentric net vertical impulse (CON-IMP), average eccentric rate of force development (ECC-RFD), and average vertical concentric force (CON-VF) for each athlete;
associating by said computer guidance with each signature in the classification; and
assigning by said computer a signature from the database to at least some athletes in the database.
2. The method of claim 1 , wherein the classification comprises a linear signature to characterize athletes who excel at movement in a straight line.
3. The method of claim 1 , wherein the classification comprises a rotational signature to characterize athletes who excel at movement that involves an element of rotation.
4. The method of claim 1 , wherein the classification comprises a lateral signature to characterize athletes who excel at lateral movement.
5. The method of claim 1 , wherein the classification comprises archetypical signatures associated with performance excellence.
6. The method of claim 5 , wherein the performance excellence is characterized by one of a particular sport and a position within a particular sport.
7. The method of claim 1 , further comprising generating the kinematic data by having an athlete perform a vertical jump from a force place from a standing position.
8. The method of claim 1 , wherein the guidance comprises an indication of a propensity for a particular injury.
9. The method of claim 1 , wherein the guidance comprises at least one exercise protocol for at least one of transforming an athlete's signature to a desired signature and preventing injury to the athlete.
10. The method of claim 8 , wherein the exercise protocol comprises an exercise definition, a number of repetitions associated with the exercise, a number of sets associated with the exercise, and a schedule for performing the exercise.
11. A non-transitory computer-readable medium comprising instructions which when executed by a processing system causes said system to perform a method for training athletes, comprising:
maintaining a classification for signatures generated based on movement data associated with athletes; wherein the movement data is stored in a database, and comprises kinematic data including normalized values for concentric net vertical impulse (CON-IMP), average eccentric rate of force development (ECC-RFD), and average vertical concentric force (CON-VF) for each athlete;
associating guidance with each signature in the classification; and
assigning a signature from the database to at least some athletes in the database.
12. The computer-readable medium of claim 11 , wherein the classification comprises a linear signature to characterize athletes who excel at movement in a straight line.
13. The computer-readable medium of claim 12 , wherein the classification comprises a rotational signature to characterize athletes who excel at movement that involves an element of rotation.
14. The computer-readable medium of claim 11 , wherein the classification comprises a lateral signature to characterize athletes who excel at lateral movement.
15. The computer-readable medium of claim 11 , wherein the classification comprises archetypical signatures associated with performance excellence.
16. A system, comprising:
a processor; and
a memory coupled to the processor, the memory storing instructions which when executed by the processor, causes the system to perform for training athletes, comprising:
maintaining a classification for signatures generated based on movement data associated with athletes; wherein the movement data is stored in a database, and comprises kinematic data including normalized values for concentric net vertical impulse (CON-IMP), average eccentric rate of force development (ECC-RFD), and average vertical concentric force (CON-VF) for each athlete;
associating guidance with each signature in the classification; and
assigning a signature from the database to at least some athletes in the database.
17. The system of claim 16 , wherein the classification comprises a linear signature to characterize athletes who excel at movement in a straight line.
18. The system of claim 16 , wherein the classification comprises a rotational signature to characterize athletes who excel at movement that involves an element of rotation.