Muscular energy state analysis system and method for swing motion and computer program product thereof

• US 8,348,862 B2
• Filed: 12/09/2009
• Issued: 01/08/2013
• Est. Priority Date: 11/13/2009
• Status: Expired due to Fees

• Current Assignee: Institute For Information Industry
• Original Assignee: Institute For Information Industry
• Inventors: Chu, Tun-Hsiao
• Primary Examiner(s): Hoekstra, Jeffrey G
• Assistant Examiner(s): HENSON, DEVIN B
• Application Number:
  US12/634,190
• Publication Number:
  US 20110118621A1
• Time in Patent Office: 1,126 Days
• Field of Search: 600/546, 600/587, 600/595, 463/2, 463/3, 463/47.2, 473/131, 473/207, 473/219, 473/282, 473/453, 473/457, 473/461, 473/463, 473/524, 473/564, 73/650.1, 73/650.3, 73/650.7, 73/650.8, 733/790.1, 733/790.2
• US Class Current: 600/587
• CPC Class Codes: A61B 2503/10 Athletes
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/224 Measuring muscular strength
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/6824 Arm or wrist
• CPC Class Codes: A61B 5/6887 mounted on external non-worn devices, e.g. non-medical devices
• CPC Class Codes: A61B 5/6895 Sport equipment
• CPC Class Codes: A63B 2024/0012 Comparing movements or motion sequences with a registered reference
• CPC Class Codes: A63B 2024/0065 Evaluating the fitness, e.g. fitness level or fitness index
• CPC Class Codes: A63B 2220/30 Speed
• CPC Class Codes: A63B 2220/803 Motion sensors
• CPC Class Codes: A63B 2220/833 Sensors arranged on the exercise apparatus or sports implement
• CPC Class Codes: A63B 2225/50 Wireless data transmission, e.g. by radio transmitters or telemetry
• CPC Class Codes: A63B 2230/08 other bio-electrical signals
• CPC Class Codes: A63B 2230/62 posture
• CPC Class Codes: A63B 24/0006 Computerised comparison for qualitative assessment of motion sequences or the course of a movement
• CPC Class Codes: A63B 69/0002 for baseball

Abstract

A muscular energy state analysis system and method for a swing motion and a computer program product thereof are provided. The system includes: a swing implement, for a user to perform the swing motion, and including an acceleration sensor for sensing acceleration of the swing implement when the swing implement is swung, so as to generate a swing speed data; a plurality of signal detection modules, for detecting electromyographic (EMG) signals generated by a muscles of the user; a database, for storing a muscular energy sample value,; a muscular energy analysis module, for analyzing the EMG signals and the swing speed data so as to obtain a plurality of muscular performance values; and a comparison module, for comparing the swing speed data and the muscular performance values with the at least one muscular energy sample value in the database, so as to generate a comparison result data.

Claims

1. A muscular energy state analysis system for a swing motion, comprising:

a swing implement, for a user to perform the swing motion, and comprising an acceleration sensor for sensing acceleration of the swing implement when the swing implement is swung, so as to generate a swing speed data;

a plurality of signal detection modules, for detecting a plurality of electromyographic (EMG) signals generated by a plurality of muscles of the user;

a database, for storing a muscular energy sample value, wherein the muscular energy sample value comprises a swing speed sample value and a plurality of corresponding muscular performance sample values;

a muscular energy analysis module, for analyzing the EMG signals and the swing speed data so as to obtain a plurality of muscular performance values, wherein the muscular energy analysis module comprises a signal analysis module and a muscular energy determination module, the signal analysis module performs a time-domain analysis on the EMG signals so as to obtain a plurality of muscle exertion intensity values, and the muscular energy determination module calculates the muscular performance values by using the muscle exertion intensity values, wherein the signal analysis module further performs a frequency-domain analysis on the EMG signals so as to obtain a fatigue index value and forms a two-dimensional coordinate system by using one of the muscle exertion intensity values and the fatigue index value; and

a comparison module, for comparing the swing speed data and the plurality of muscular performance values with the muscular energy sample value in the database, so as to generate a comparison result data, wherein the comparison module analyzes a target quadrant where a point defined by the muscle exertion intensity value and the fatigue index value is, the comparison module determines whether the user is in the a fatigue state according to the quadrant where the point is, and when the comparison module determines that the user is in the fatigue state, the comparison module generates a rest suggestion information.

2. The muscular energy state analysis system for a swing motion according to claim 1, wherein the comparison module compares the swing speed data and the plurality of muscular performance values with the swing speed sample value and the plurality of corresponding muscular performance sample values of each of the muscular energy sample values in the database respectively, so as to generate the comparison result data.

3. The muscular energy state analysis system for a swing motion according to claim 1, wherein the muscular performance values and the muscular performance sample values are respectively corresponding to one of a plurality of muscular properties;

and the muscular energy analysis module compares the muscular performance value and the muscular performance sample value of the same muscular property, so as to generate the comparison result data.

4. The muscular energy state analysis system for a swing motion according to claim 1, wherein the muscular energy analysis module further determines whether the muscular performance values comprise an abnormal muscular performance value by comparing the muscular performance values with the muscular performance sample values.

5. The muscular energy state analysis system for a swing motion according to claim 4, wherein the comparison module further generates a force-exertion suggestion data according to the comparison result data.

6. The muscular energy state analysis system for a swing motion according to claim 1, wherein when comparing the swing speed data and the plurality of muscular performance values with the muscular energy sample value in the database, the comparison module compares the swing speed data and the plurality of muscular performance values with each of the muscular energy sample values in the database, selects a target muscular energy sample value from the muscular energy sample value, and compares the swing speed data and the plurality of muscular performance values with the target muscular energy sample value, so as to generate the comparison result data.

7. The muscular energy state analysis system for a swing motion according to claim 1, further comprising a display for displaying the comparison result data.

8. The muscular energy state analysis system for a swing motion according to claim 1, wherein the comparison result data is a difference between the swing speed data and the swing speed sample value, and a difference between the plurality of muscular performance values and the plurality of muscular performance sample values.

9. A muscular energy state analysis method for a swing motion, comprising:

providing a database storing a muscular energy sample value, wherein each of the muscular energy sample values comprises a swing speed sample value and a plurality of corresponding muscular performance sample values;

sensing acceleration of a swing implement by an acceleration sensor when a user uses the swing implement to perform the swing motion, so as to generate a swing speed data;

obtaining a plurality of electromyographic (EMG) signals generated by a plurality of muscles of the user;

analyzing the EMG signals and the swing speed data so as to obtain a plurality of muscular performance values;

comparing the swing speed data and the plurality of muscular performance values with the muscular energy sample value in the database, so as to generate a comparison result data;

performing a frequency-domain analysis on the EMG signals so as to obtain a fatigue index value;

forming a two-dimensional coordinate system by using a muscle exertion intensity value and the fatigue index value;

analyzing a target quadrant where a point defined by the muscle exertion intensity value and the fatigue index value is located by a comparison module;

determining whether the user is in a fatigue state according to the quadrant where the point is by the comparison module; and

when the comparison module determines that the user is in the fatigue state, generating a rest suggestion information by the comparison module.

10. The method according to claim 9, wherein the comparing comprises:

comparing the swing speed data and the muscular performance values with the swing speed sample value and the plurality of corresponding muscular performance sample values of the muscular energy sample value in the database, so as to generate the comparison result data.

11. The method according to claim 9, wherein the muscular performance values and the muscular performance sample values are respectively corresponding to one of a plurality of muscular properties, and the method further comprises:

comparing the muscular performance value and the muscular performance sample value of the same muscular property, so as to generate the comparison result data.

12. The method according to claim 9, further comprising:

determining whether the muscular performance values comprise an abnormal muscular performance value by comparing the muscular performance values with the muscular performance sample values.

13. The method according to claim 12, further comprising:

generating a force-exertion suggestion data according to the comparison result data.

14. The method according to claim 9, wherein the comparing comprises:

comparing the swing speed data and the plurality of muscular performance values with each of the muscular energy sample values in the database, selecting a target muscular energy sample value from the muscular energy sample value, and comparing the swing speed data and the plurality of muscular performance values with the target muscular energy sample value, so as to generate the comparison result data.

15. The method according to claim 9, further comprising:

providing a display for displaying the comparison result data.

16. The method according to claim 9, wherein the comparison result data is a difference between the swing speed data and the swing speed sample value, and a difference between the plurality of muscular performance values and the plurality of muscular performance sample values.

17. A computer program product, for performing a muscular energy state analysis method for a swing motion when an electronic device reads the computer program product, wherein an acceleration sensor senses an acceleration of a swing implement when a user uses the swing implement to perform the swing motion, so as to generate a swing speed data, and a plurality of signal detection modules obtains a plurality of electromyographic (EMG) signals generated by a plurality of muscles of the user;

and the method comprises;

providing a database for storing a muscular energy sample value, wherein each of the muscular energy sample values comprises a swing speed sample value and a plurality of corresponding muscular performance sample values;

analyzing the EMG signals and the swing speed data so as to obtain a plurality of muscular performance values;

comparing the swing speed data and the plurality of muscular performance values with the muscular energy sample value in the database, so as to generate a comparison result data;

performing a frequency-domain analysis on the EMG signals so as to obtain a fatigue index value;

forming a two-dimensional coordinate system by using a muscle exertion intensity value and the fatigue index value;

analyzing a target quadrant where a point defined by the muscle exertion intensity value and the fatigue index value is located by a comparison module;

determining whether the user is in a fatigue state according to the quadrant where the point is by the comparison module; and

when the comparison module determines that the user is in the fatigue state, generating a rest suggestion information by the comparison module.