SYSTEMS AND METHODS FOR AUTOMATED ANALYSIS OF FITNESS DATA

• US 20150032235A1
• Filed: 07/15/2014
• Published: 01/29/2015
• Est. Priority Date: 07/23/2013
• Status: Abandoned Application

• Current Assignee: Badpopcorn Incorporated
• Original Assignee: Badpopcorn Incorporated
• Inventors: Yu, Benjamin Lon Hing, Naqvi, Mohammad Ali, Kinnick, Jonathan Michael, Tripp, Corey Robert
• Application Number:
  US14/332,260
• Publication Number:
  US 20150032235A1
• Time in Patent Office: Days
• US Class Current: 700/91
• CPC Class Codes: A63B 71/0686 Timers, rhythm indicators or pacing apparatus using electric or electronic means
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising

Abstract

Systems and methods are provided for processing and analyzing workout or other fitness data associated with a user. For example, a fitness analysis system may electronically receive workout data indicating performance of a user with respect to each of a number of different workouts completed by the user, where a given workout may include multiple movements. The workout data may be processed and analyzed to determine features or aspects of fitness or health that are relatively strong or weak for the given user by applying one or more rule sets and/or based on comparisons among a variety of the processed data. One or more user interfaces may then be generated providing graphical or other indications of fitness strengths or weaknesses determined by the fitness analysis system.

Claims

1. A system comprising:

an electronic data store configured to store workout data indicating performance of each of a plurality of users with respect to each of a plurality of workouts; and

a computing system comprising one or more hardware computing devices executing specific computer-executable instructions, said computing system in communication with the electronic data store, and configured to at least;

retrieve, from the electronic data store, workout information associated with a user of the plurality of users, wherein the retrieved workout information indicates performance of the user with respect to each of a first plurality of workouts;

generate a plurality of scores for the user, wherein each of the plurality of scores indicates a performance level of the user with respect to at least one of an exercise or a fitness trait;

determine an overall fitness level for the user based at least in part on the plurality of scores;

identify at least one outlying score among the plurality of scores based at least in part on a comparison of the outlying score to at least one of the overall fitness level or at least one other score of the plurality of scores for the user;

automatically determine a potential cause of the at least one outlying score based at least in part on a score type associated with the outlying score; and

generate a user interface for presentation to the user based at least in part on the automatic determination, wherein the user interface identifies the determined potential cause of the at least one outlying score as a fitness strength or fitness weakness associated with the user.

2. The system of claim 1, wherein the potential cause is one of physical strength, flexibility or technique.

3. The system of claim 2, wherein the computing system is further configured to determine the potential cause of the at least one outlying score based at least in part on a rule set associated with at least one of a fitness category, a fitness trait or an exercise.

4. The system of claim 1, wherein the computing system is further configured to identify the at least one outlying score by determining that a difference between the at least one outlying score and the overall fitness level is greater than a predetermined threshold.

5. The system of claim 4, wherein the predetermined threshold is associated with at least one of a fitness category, a fitness trait or an exercise.

6. The system of claim 4, wherein the plurality of scores and the overall fitness score are each based at least in part on a percentile of workout performance of the user relative to a population of users.

7. The system of claim 1, wherein the at least one other score comprises a score that more closely matches the overall fitness level than the at least one outlying score.

8. A computer-implemented method comprising:

as implemented by one or more computing devices configured with specific executable instructions,

electronically receiving workout data indicating performance of a user with respect to each of a plurality of workouts completed by the user;

generating a plurality of fitness sub-scores for the user, wherein each of the plurality of fitness sub-scores indicates a performance level of the user with respect to at least one of a movement, a fitness category or a fitness trait;

determining an overall fitness level for the user based at least in part on the plurality of fitness sub-scores;

identifying at least one outlying sub-score among the plurality of fitness sub-scores based at least in part on a comparison of the outlying sub-score to the overall fitness level;

automatically determining a potential cause of the at least one outlying sub-score based at least in part on a score type associated with the outlying sub-score; and

generating a user interface for presentation to the user based at least in part on the automatic determination, wherein the user interface identifies the determined potential cause of the at least one outlying sub-score.

9. The computer-implemented method of claim 8, wherein the at least one outlying sub-score is further identified based at least in part by comparing the at least one outlying sub-score to at least one other sub-score of the plurality of sub-scores.

10. The computer-implemented method of claim 8, wherein the user interface identifies the outlying sub-score as being indicative of a specific determined fitness strength or fitness weakness associated with the user.

11. The computer-implemented method of claim 8, wherein a first sub-score of the plurality of fitness sub-scores is based on performance of the user with respect to a plurality of different movement types.

12. The computer-implemented method of claim 8, wherein the potential cause is determined based at least in part by applying a first electronically retrieved rule set that identifies a cause based on a defined score relationship between at least two types of exercises.

13. The computer-implemented method of claim 8, wherein computer application of a first rule set identifies a first potential cause when a first sub-score is lower than a second sub-score and identifies a different potential cause when the second sub-score is lower than the first sub-score.

14. The computer-implemented method of claim 13, wherein the first rule set is applied based on a fitness category assigned to at least one of the first sub-score and the second sub-score.

15. The computer-implemented method of claim 8, wherein identifying the at least one outlying sub-score comprises identifying that a given sub-score is more than a predefined threshold number of percentile points different than one or more specific sub-scores other than the given sub-score.

16. A computer-readable, non-transitory storage medium storing computer executable instructions that, when executed by one or more computing devices, configure the one or more computing devices to perform operations comprising:

electronically receiving workout data indicating performance of a user with respect to each of a plurality of workouts completed by the user;

generating a plurality of fitness sub-scores for the user, wherein each of the plurality of fitness sub-scores indicates a performance level of the user with respect to at least one of a movement, a fitness category or a fitness trait;

determining an overall fitness level for the user based at least in part on the plurality of fitness sub-scores;

identifying at least one outlying sub-score among the plurality of fitness sub-scores based at least in part on a comparison of the outlying sub-score to the overall fitness level;

automatically determining a potential cause of the at least one outlying sub-score based at least in part on a score type associated with the outlying sub-score; and

generating a user interface for presentation to the user based at least in part on the automatic determination, wherein the user interface identifies the determined potential cause of the at least one outlying sub-score.

17. The computer-readable, non-transitory storage medium of claim 16, wherein the user interface comprises a graphical representation of the plurality of fitness sub-scores and the overall fitness level.

18. The computer-readable, non-transitory storage medium of claim 16, wherein determining the overall fitness level comprising averaging the plurality of fitness sub-scores.