Fuzzy logic-based evaluation and feedback of exercise performance

• US 9,364,714 B2
• Filed: 12/31/2014
• Issued: 06/14/2016
• Est. Priority Date: 01/14/2014
• Status: Active Grant

• Current Assignee: Zsolutionz LLC
• Original Assignee: Zsolutionz LLC
• Inventors: Koduri, Sunil, Hand, John Michael, Bhatia, Surendra P. S., Adams, Bobby Joe, Ransone, John W., Koduri, Shalini
• Primary Examiner(s): GINSBERG, OREN ISAAC
• Application Number:
  US14/588,346
• Publication Number:
  US 20150196805A1
• Time in Patent Office: 531 Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/4833 Assessment of subject's compliance to treatment
• CPC Class Codes: A63B 2024/0068 Comparison to target or threshold, previous performance or not real time comparison to other individuals
• CPC Class Codes: A63B 2069/0037 safety devices, e.g. warning bells, rear-view mirrors
• CPC Class Codes: A63B 2071/0625 Emitting sound, noise or music
• CPC Class Codes: A63B 2071/065 Visualisation of specific exercise parameters
• CPC Class Codes: A63B 22/0076 Rowing machines for conditioning the cardio-vascular system seats moving during exercise A63B22/0087; training appliances for rowing or sculling on boats A63B69/06
• CPC Class Codes: A63B 22/02 with movable endless bands , e.g. treadmills other training appliances for running on the spot A63B69/0028
• CPC Class Codes: A63B 22/04 with movable multiple steps , i.e. more than one step per limb, e.g. steps mounted on endless loops, endless ladders steppers with cantilevered support elements pivoting about an axis A63B22/0048
• CPC Class Codes: A63B 22/0605 performing a circular movement, e.g. ergometers
• CPC Class Codes: A63B 22/0664 performing an elliptic movement
• CPC Class Codes: A63B 2209/10 with adhesive type surfaces, i.e. hook and loop-type fastener
• CPC Class Codes: A63B 2214/00 Training methods
• CPC Class Codes: A63B 2220/806 Video cameras
• 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 2230/06 heartbeat rate only
• CPC Class Codes: A63B 2230/08 other bio-electrical signals
• CPC Class Codes: A63B 2230/202 glucose
• CPC Class Codes: A63B 2230/30 blood pressure A63B2230/04 takes precedence
• CPC Class Codes: A63B 2230/42 rate
• CPC Class Codes: A63B 2230/436 : partial O2 value
• CPC Class Codes: A63B 2230/50 : temperature
• CPC Class Codes: A63B 24/0062 : Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
• CPC Class Codes: A63B 24/0087 : Electric or electronic controls for exercising apparatus of groups A63B21/00 - A63B23/00, e.g. controlling load
• CPC Class Codes: A63B 71/0622 : Visual, audio or audio-visual systems for entertaining, instructing or motivating the user
• CPC Class Codes: G06Q 10/0639 : Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 50/01 : Social networking
• CPC Class Codes: G06T 7/00 : Image analysis
• CPC Class Codes: G06V 40/20 : Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: G16H 20/30 : relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 30/40 : for processing medical images, e.g. editing
• CPC Class Codes: G16H 40/67 : for remote operation

Abstract

Disclosed herein are techniques and systems for evaluating exercise performance of a user of a fitness system by utilizing one or more intelligent sensors, including at least one camera-based sensor configured to detect image data of the user. The fitness system may include a stationary exercise device, a memory to store personal information about a user, and a processor to generate a set of exercise rules based, at least in part, on the personal information about the user. The fitness system may also include one or more sensors to monitor a physical state of the user, and a fuzzy system to generate an evaluation for the user based, at least in part, on i) the set of rules and ii) output from the one or more sensors. The fitness system may thereby provide real-time, constructive feedback regarding the user'"'"'s exercise performance based on the sensed data.

Claims

1. A method of evaluating an exercise performance condition of a user of a fitness system, the method comprising:

generating a set of exercise rules based, at least in part, on personal information about the user;

detecting, by a camera-based sensor, image data of the user;

analyzing the image data to produce one or more measurements representative of a muscle tension of the user;

mapping the one or more measurements representative of the muscle tension to a set of fuzzy variables by a membership function; and

generating an evaluation for the user based, at least in part, on i) the set of fuzzy variables and ii) the set of exercise rules.

2. The method of claim 1, further comprising obtaining, based on one or more additional sensors, one or more additional measurements representative of a physical state of the user, the one or more additional measurements including one or more of body weight, heart rate, blood pressure, oxygen level, hydration level, body temperature, blood glucose level, or respiratory rate.

3. The method of claim 1, further comprising analyzing the image data to produce one or more additional measurements relating to a stance of the user.

4. The method of claim 1, further comprising identifying, by the camera-based sensor, the user based at least in part on facial recognition.

5. The method of claim 1, further comprising:

identifying the user; and

downloading from a remote network server the personal information about the user.

6. The method of claim 1, wherein the personal information about the user includes one or more of name, gender, age, race, height, weight, health conditions, or fitness goals.

7. The method of claim 1, wherein the evaluation includes one or more of i) an evaluation of exercise performance by the user or ii) an instruction for the user to take corrective action.

8. The method of claim 7, further comprising causing display of:

an image of a reference user having an ideal exercise form, and

an avatar of the user that indicates the exercise performance of the user.

9. The method of claim 8, wherein the causing the display of the avatar of the user comprises overlaying the avatar of the user on top of the image of the reference user.

10. The method of claim 1, wherein the fitness system includes a treadmill, and wherein the evaluation includes one or more of instructions to correct a stance of the user, to correct running stride, or to correct running pace.

11. The method of claim 1, further comprising providing the evaluation on a display in the form of a text-based message of the evaluation.

12. The method of claim 1, further comprising:

detecting, by an electronic textile (e-textile) sensor, pressure forces on at least one foot of the user, wherein the generating the evaluation for the user is further based, at least in part, on the pressure forces.

13. The method of claim 1, further comprising displaying a text-based message of the evaluation for the user.

14. A fitness system comprising:

a camera-based sensor to detect image data of a user;

one or more processors; and

memory, storing instructions that, when executed by the one or more processors, perform operations comprising;

generating a set of exercise rules based, at least in part, on personal information about the user;

analyzing the image data detected by the camera-based sensor to produce one or more measurements representative of a muscle tension of the user;

mapping the one or more measurements representative of the muscle tension to a set of fuzzy variables by a membership function; and

generating an evaluation for the user based, at least in part, on i) the set of fuzzy variables and ii) the set of exercise rules.

15. The fitness system of claim 14, further comprising one or more additional sensors, the operations further comprising obtaining, based on the one or more additional sensors, one or more additional measurements representative of a physical state of the user, the one or more additional measurements including one or more of body weight, heart rate, blood pressure, oxygen level, hydration level, body temperature, blood glucose level, or respiratory rate.

16. The fitness system of claim 14, the operations further comprising analyzing the image data to produce one or more additional measurements relating to a stance of the user.

17. The fitness system of claim 14, the operations further comprising identifying the user based at least in part on facial recognition using the image data detected by the camera-based sensor.

18. The fitness system of claim 14, the operations further comprising:

identifying the user; and

downloading from a remote network server the personal information about the user.

19. The fitness system of claim 14, wherein the personal information about the user includes one or more of name, gender, age, race, height, weight, health conditions, or fitness goals.

20. The fitness system of claim 14, wherein the evaluation includes one or more of i) an evaluation of exercise performance by the user or ii) an instruction for the user to take corrective action.

21. The fitness system of claim 20, further comprising a display, the operations further comprising presenting on the display:

an image of a reference user having an ideal exercise form, and

an avatar of the user that indicates the exercise performance of the user.

22. The fitness system of claim 21, wherein the presenting on the display the avatar of the user comprises overlaying the avatar of the user on top of the image of the reference user.

23. The fitness system of claim 14, wherein the fitness system includes a treadmill, and wherein the evaluation includes one or more of instructions to correct a stance of the user, to correct running stride, or to correct running pace.

24. The fitness system of claim 14, further comprising a display, the operations further comprising providing the evaluation on the display in the form of a text-based message of the evaluation.

25. The fitness system of claim 14, further comprising an electronic textile (e-textile) sensor, the operations further comprising:

detecting, by the e-textile sensor, pressure forces on at least one foot of the user, wherein the generating the evaluation for the user is further based, at least in part, on the pressure forces.

26. The fitness system of claim 14, further comprising a display, the operations further comprising presenting, on the display, a text-based message of the evaluation for the user.

27. A computer-implemented method comprising:

generating a set of exercise rules based, at least in part, on personal information about a user;

detecting, by a camera-based sensor, image data of the user;

analyzing the image data to produce one or more measurements representative of a muscle tension of the user;

mapping the one or more measurements representative of the muscle tension to a set of fuzzy variables by a membership function; and

presenting, on a display, an evaluation for the user based, at least in part, on i) the set of fuzzy variables and ii) the set of exercise rules.

28. The computer-implemented method of claim 27, further comprising obtaining, based on one or more additional sensors, one or more additional measurements representative of a physical state of the user, the one or more additional measurements including one or more of body weight, heart rate, blood pressure, oxygen level, hydration level, body temperature, blood glucose level, or respiratory rate.

29. The computer-implemented method of claim 27, further comprising analyzing the image data to produce one or more additional measurements relating to a stance of the user.

30. The computer-implemented method of claim 27, further comprising:

identifying the user; and

downloading from a remote network server the personal information about the user.

31. The computer-implemented method of claim 27, wherein the personal information about the user includes one or more of name, gender, age, race, height, weight, health conditions, or fitness goals.

32. The computer-implemented method of claim 27, wherein the evaluation includes one or more of i) an evaluation of exercise performance by the user or ii) an instruction for the user to take corrective action.

33. The computer-implemented method of claim 32, further comprising presenting on the display:

an image of a reference user having an ideal exercise form, and

an avatar of the user that indicates the exercise performance of the user.

34. The computer-implemented method of claim 33, wherein the presenting on the display the avatar of the user comprises overlaying the avatar of the user on top of the image of the reference user.