System And Apparatus For Correlating Heart Rate To Exercise Parameters

• US 20110288381A1
• Filed: 05/23/2011
• Published: 11/24/2011
• Est. Priority Date: 05/24/2010
• Status: Abandoned Application

• Current Assignee: Saris Cycling Group Incorporated
• Original Assignee: Saris Cycling Group Incorporated
• Inventors: Ivereson, Jeffrey T., Lim, Allen C., Bartholomew, Jesse
• Application Number:
  US13/113,767
• Publication Number:
  US 20110288381A1
• Time in Patent Office: Days
• US Class Current: 600/301
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/222 combined with detection or measurement of physiological parameters, e.g. heart rate

Abstract

A computer-implemented method is used for estimating an exercise parameter for a user. The method includes the steps of receiving a measured physiologic value such as heart rate, determining an estimated exercise parameter value based on the physiologic value based on a stored correlation between a measured physiologic value and a measured exercise parameter value, and providing the estimated exercise parameter value.

Claims

1. A computer-implemented method for estimating an exercise parameter for a user, comprising the steps of:

receiving a measured physiologic value;

determining an estimated exercise parameter value based on the physiologic value using a stored correlation between a measured physiologic value and a measured exercise parameter value; and

providing the estimated exercise parameter value.

2. The method of claim 1, wherein the physiologic value is a heart rate value and wherein the exercise parameter value is at least one of power output, oxygen consumption, and carbon dioxide exhalation.

3. The method of claim 1, wherein providing the exercise parameter value includes transmitting a signal including the measured physiologic value and the estimated exercise parameter value.

4. The method of claim 1, wherein receiving a measured physiologic value includes receiving a wireless signal including the measured physiologic value.

5. The method of claim 1, further including receiving a user specific data entry wherein determining an estimated exercise parameter value based on the physiologic value includes customizing the estimated exercise parameter based on the user specific data.

6. The method of claim 5, wherein the user specific data is at least one of a gender, age, height, weight, fitness level, and fatigue level.

7. The method of claim 1, wherein the stored correlation between a measured physiologic value and a measured exercise parameter value is generated based on a regression analysis of received measured physiologic values and measured exercise parameter values.

8. A computer system for providing an estimated exercise parameter value, comprising:

a heart rate sensor input device;

a processor configured to receive heart rate information from the heart rate input device and execute a program to determine a correlation between the received heart rate information and estimated values for one or more exercise parameters; and

an estimated exercise parameter output device.

9. The system of claim 8, wherein the estimated exercise parameter output device is further configured to transmit the received heart rate information.

10. The system of claim 8, further including memory for receiving and storing a measured correlation between the received heart rate information and exercise parameter values for a specific user.

11. A computer implemented method for generating a correlation between a measured heart rate and measured power output for a user during exercise:

receiving a measured heart rate value;

receiving a measured power output value;

determining a user-specific correlation between heart rate and power output using the measured heart rate value and the measured power output value; and

storing the user-specific correlation in computer memory.

12. The method of claim 11, wherein the step of determining a user-specific correlation between heart rate and power output is carried out using a regression analysis that includes determining a linear correlation between heart rate and power output.

13. The method of claim 11, wherein the step of determining a user-specific correlation between heart rate and power output is carried out using a regression analysis and includes determining a first order correlation between the heart rate and power output.

14. The method of claim 11, wherein the step of determining a user-specific correlation between heart rate and power output is carried out using a regression analysis and includes determining a linear correlation, a first order correlation, and a second order correlation between the heart rate and power output.

15. The method of claim 14, further comprising applying a differential correlation between the measured heart rate and power output.

16. The method of claim 11, wherein storing the user-specific correlation in computer memory including associating the user-specific correlation with one or more user input values.

17. The method of claim 16, wherein user input values include at least one of is at least one of a gender, age, height, weight, fitness level, and fatigue level.

18. A computer-implemented method for estimating power output by a user, comprising the steps of:

receiving a measured heart rate value;

determining an estimated power output based on the heart rate value using a stored correlation between a measured heart rate value and a power output value; and

providing the power output value.

19. The method of claim 18, further including receiving a user specific data entry wherein determining an estimated power output value based on the heart rate value includes customizing the estimated power output value based on the user specific data, wherein the user specific data is at least one of a gender, age, height, weight, fitness level, and fatigue level.

20. The method of claim 18, wherein the stored correlation between a measured heart rate value and a power output value is generated based on a regression analysis of received measured heart rate values and power output exercise parameter values.