Sensing applications for exercise machines

• US 8,574,131 B2
• Filed: 02/19/2013
• Issued: 11/05/2013
• Est. Priority Date: 07/18/2007
• Status: Active Grant

• Current Assignee: Life Fitness LLC
• Original Assignee: Brunswick Corporation
• Inventors: Daly, Juliette C., Cate, Casparus, DeYoung, Glenn Allen
• Primary Examiner(s): RICHMAN, GLENN E
• Application Number:
  US13/770,729
• Publication Number:
  US 20130165297A1
• Time in Patent Office: 259 Days
• Field of Search: 482 1- 9, 482/51, 482/54, 482900-902, 434/247, 119/700
• US Class Current: 482/9
• 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 2024/0078 Exercise efforts programmed as a function of time
• CPC Class Codes: A63B 2071/065 Visualisation of specific exercise parameters
• CPC Class Codes: A63B 22/0228 with variable resilience
• CPC Class Codes: A63B 22/0235 driven by a motor
• CPC Class Codes: A63B 22/025 electrically, e.g. D.C. motors with variable speed control
• CPC Class Codes: A63B 2220/17 Counting, e.g. counting periodical movements, revolutions or cycles, or including further data processing to determine distances or speed
• CPC Class Codes: A63B 2220/22 Stride length
• CPC Class Codes: A63B 2220/34 Angular speed
• CPC Class Codes: A63B 2220/53 Force of an impact, e.g. blow or punch
• CPC Class Codes: A63B 2220/833 Sensors arranged on the exercise apparatus or sports implement
• CPC Class Codes: A63B 2230/06 heartbeat rate only
• 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 24/0075 Means for generating exercise programs or schemes, e.g. computerized virtual trainer, e.g. using expert databases
• CPC Class Codes: Y10S 482/901 having computer circuitry

Abstract

Methods for profiling exercise sessions are described. An example method of determining cadence of a user disclosed herein includes receiving output signals from a sensor generated in response to consecutive footfalls of the user impacting a deck of a treadmill during an exercise session and processing the output signals from the sensor to determine respective magnitude values of a peak or a trough value of each of the output signals. The method includes detecting whether a first output signal has a first peak or trough value and detecting whether a second output signal has a second peak or trough value, determining a time interval between the first peak or trough value detected and the second peak or trough value detected, and calculating a cadence value of the user based on the time intervals.

Claims

1. A method of determining cadence of a user exercising on a treadmill, the method comprising:

receiving output signals from a sensor generated in response to consecutive footfalls of the user impacting a deck of the treadmill during an exercise session;

processing the output signals from the sensor to determine respective magnitude values of a peak or a trough value of each of the output signals;

detecting whether a first output signal has a first peak or trough value and detecting whether a second output signal has a second peak or trough value;

determining a time interval between the first peak or trough value detected and the second peak or trough value detected; and

calculating a cadence value of the user based on the time intervals.

2. A method as described in claim 1, further comprising providing a cadence training program to the user, the method comprising:

receiving a target cadence value;

comparing the calculated cadence value with the target cadence value;

in response to the calculated cadence value being less than the target cadence value, prompting the user to increase a speed of the treadmill or prompting the user to shorten a stride length if the calculated cadence value is less than the target cadence; and

in response to the calculated cadence value being greater than the target cadence value, prompting the user to decrease the speed of the treadmill or prompting a user to lengthen a stride length if the calculated cadence value is greater than the target cadence.

3. A method as described in claim 2, wherein receiving the target cadence value comprises receiving the target cadence value from a user interface or a data structure having recommended cadence values based on a user'"'"'s physical characteristics and workout parameters selected via the user interface.

4. A method as described in claim 2, further comprising directing a device controller to cause a speed adjustor to automatically increase or decrease the speed value of a drive member driving a belt of the treadmill.

5. A method as described in claim 2, further comprising determining a stride length of a user exercising on a treadmill, the method comprising:

receiving a speed value of a belt moving over a deck of the treadmill from a user interface or a speed sensor; and

calculating a stride length value of a user by multiplying the time interval between the first and second peak or trough values of the first and second output signals by the speed value of the belt.

6. A method as defined in claim 5, further comprising comparing the calculated stride length value with a nominal stride length value, wherein the nominal stride length value is retrieved from a data structure having look-up tables that define average stride lengths based on a user'"'"'s physical characteristics and workout parameters selected via a user interface.

7. A method as described in claim 2, further comprising adjusting a metabolic cost equation when the calculated cadence value is either less than or greater than the target cadence value.

8. A method as described in claim 7, wherein adjusting the metabolic cost equation comprises selecting a coefficient value from a data storage and multiplying the metabolic cost equation by the coefficient value.

9. A method as described in claim 8, wherein selecting the coefficient value comprises determining a delta value, wherein the delta value is based on a difference between a nominal stride length of the user retrieved from a storage interface and an average stride length retrieved from a data structure, and wherein the delta value and the speed are used to select the coefficient value from the data structure.

10. A method as described in claim 9, wherein the nominal stride length of the user is obtained by storing the calculated cadence value or the calculated stride length in a memory prior to prompting the user to either shorten or lengthen the stride and averaging the stored calculated cadence values or the calculated stride length.

11. A machine accessible medium having instructions stored thereon that, when executed, cause a machine to:

receive output signals from a sensor generated in response to consecutive footfalls of a user impacting a deck of a treadmill during an exercise session;

process the output signals from the sensor to determine respective magnitude values of a peak or a trough value of each of the output signals;

detect whether a first output signal has a first peak or trough value and detecting whether a second output signal has a second peak or trough value;

determine a time interval between the first peak or trough value detected and the second peak or trough value detected; and

calculate a cadence value of the user based on the time interval.

12. A machine accessible medium as defined in claim 11 having instructions stored thereon that, when executed, cause the machine to store the calculated cadence value in memory.

13. A machine accessible medium as defined in claim 11 having instructions stored thereon that, when executed, cause the machine to receive a target cadence value, compare the calculated cadence value with the target cadence value, and in response to the calculated cadence value being less than the target cadence value, prompt the user to increase a speed of the treadmill or prompting the user to shorten a stride length, or in response to the calculated cadence value being greater than the target cadence value, prompt the user to decrease the speed of the treadmill or prompting the user to lengthen a stride length if the calculated cadence value is greater than the target cadence value.

14. A machine accessible medium as defined in claim 13 having instructions stored thereon that, when executed, cause the machine to receive the target cadence value from a user interface or a data structure having recommended cadence values based on a user'"'"'s physical characteristics and workout parameters selected via the user interface.

15. A machine accessible medium as defined in claim 13 having instructions stored thereon that, when executed, cause the machine to direct a device controller to automatically increase or decrease the speed value of a drive member driving a belt.

16. A machine accessible medium as defined in claim 13 having instructions stored thereon that, when executed, cause the machine to prompt the user to shorten or lengthen the stride length of the user via a display.

17. A machine accessible medium as defined in claim 13 having instructions stored thereon that, when executed, cause the machine to receive a speed value of a belt moving over a deck of the treadmill from a user interface or a speed sensor, and multiply the time interval between the first and second peak or trough values of the first and second output signals by the speed value of the belt to determine a calculated stride length value of the user exercising on a treadmill.

18. A machine accessible medium as defined in claim 17, having instructions stored thereon that, when executed, cause the machine to store the calculated stride length value in a memory medium.

19. A machine accessible medium as defined in claim 17 having instructions stored thereon that, when executed, cause the machine to compare the calculated stride length with a nominal stride length, wherein the nominal stride length is retrieved from a data structure having look-up tables that define average stride lengths based on a user'"'"'s physical characteristics and workout parameters selected via the user interface.

20. A machine accessible medium as defined in claim 13, having instructions stored thereon that, when executed, cause the machine to adjust a metabolic cost equation when the calculated cadence value is either less than or greater than the target cadence value.

21. A machine accessible medium as defined in claim 20, having instructions stored thereon that, when executed, cause the machine to select a coefficient value from a data storage and multiplying the metabolic cost equation by the coefficient value to adjust the metabolic cost equation.

22. A machine accessible medium as defined in claim 21, having instructions stored thereon that, when executed, cause the machine to determine a delta value based on a difference between the nominal stride length of the user retrieved from a storage interface and an average stride length retrieved from a data structure, and wherein the delta value and the speed are used to select the coefficient value from the data structure.

23. A machine accessible medium as defined in claim 22, having instructions stored thereon that, when executed, cause the machine to determine the nominal stride length of the user by storing the calculated cadence value or the calculated stride length in a memory prior to prompting the user to either shorten or lengthen the stride and averaging the stored calculated cadence value or the calculated stride length to determine the nominal stride length.

24. A system for profiling an exercise session of an exercise machine, comprising:

a user interface to enable a user to input physical characteristics or workout parameters;

sensors operatively coupled to the exercise machine to generate output signals in response to a user impacting the exercise machine during the exercise session, the sensors to produce output signals that are proportional to magnitudes of forces imparted on the exercise machine by the user during the exercise session; and

a control system to process the output signals to determine peak or trough values of the output signals, the control system to detect whether a first output signal has a first peak or trough value and detect whether a second output signal has a second peak or trough value, the control system to determine a time interval between the first peak or trough value detected and the second peak or trough value detected and calculate a cadence value of the user based on the time interval.

25. A system as described in claim 24 wherein the sensors comprise piezoelectric sensors.