Algorithms for computing heart rate and movement speed of a user from sensor data

• US 20070118043A1
• Filed: 04/20/2006
• Published: 05/24/2007
• Est. Priority Date: 11/23/2005
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Oliver, Nuria, Flores-Mangas, Fernando
• Application Number:
  US11/407,645
• Publication Number:
  US 20070118043A1
• Time in Patent Office: Days
• US Class Current: 600/519
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A63B 2024/0009 Computerised real time comparison with previous movements or motion sequences of the user
• 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 2071/0644 with display speed of moving landscape controlled by the user's performance
• CPC Class Codes: A63B 2071/0663 worn on the wrist, e.g. wrist bands
• CPC Class Codes: A63B 2220/34 Angular speed
• CPC Class Codes: A63B 2220/40 Acceleration
• 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 2230/04 heartbeat characteristics, e.g. ECG, blood pressure modulations
• CPC Class Codes: A63B 2230/202 glucose
• CPC Class Codes: A63B 2230/207 P-O2, i.e. partial O2 value
• CPC Class Codes: A63B 2230/30 blood pressure A63B2230/04 takes precedence
• CPC Class Codes: A63B 2230/42 rate
• CPC Class Codes: A63B 2230/50 temperature
• CPC Class Codes: A63B 2230/65 skin conductivity
• CPC Class Codes: A63B 24/0006 Computerised comparison for qualitative assessment of motion sequences or the course of a movement
• 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 69/0028 for running, jogging or speed-walking movable endless bands A63B22/02
• CPC Class Codes: A63B 71/0622 Visual, audio or audio-visual systems for entertaining, instructing or motivating the user
• CPC Class Codes: A63B 71/0686 : Timers, rhythm indicators or pacing apparatus using electric or electronic means
• CPC Class Codes: G16H 20/30 : relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/67 : for remote operation

Abstract

Aspects of the invention use music to influence a person'"'"'s performance in a physical workout. A computing device receives and analyzes data indicating current physiology and movement of the user in order to provide a music piece that will influence the user to speed up, slow down, or maintain current pace so to achieve a desired exercise performance level. Information specific to the user may be considered in providing the music piece.

Claims

1. A computer-implemented method for computing a heart rate of a user using an electrocardiogram (“

ECG”

) signal, the method comprising;

(a) receiving an ECG signal concerning a user;

(b) obtaining an ECG low pass signal;

(c) obtaining an ECG high frequency signal;

(d) obtaining an ECG high frequency envelope;

(e) obtaining an adaptive threshold for heart beat detection; and

(f) obtaining a heart rate of the user.

2. The method of claim 1, wherein obtaining the ECG low pass signal includes:

low pass filtering the ECG signal.

3. The method of claim 1, wherein obtaining the ECG high frequency signal includes:

subtracting the ECG low pass signal from the ECG signal.

4. The method of claim 1, wherein obtaining the ECG high frequency envelope includes:

low pass filtering the ECG high frequency signal.

5. The method of claim 1, wherein obtaining the adaptive threshold for heart beat detection includes:

low pass filtering the ECG high frequency envelope.

6. The method of claim 1, wherein obtaining the heart rate of the user includes:

(a) obtaining result of (the ECG high frequency envelope−

K*the adaptive threshold), wherein K is a positive integer; and

(b) if the result is positive and no heart beat has been detected in past N numbers of ECG signals of the user, wherein N is a positive integer, computing the heart rate of the user.

7. The method of claim 6, wherein computing the heart rate of the user includes:

(a) computing an instantaneous heart rate of the user; and

(b) obtaining the heart rate of the user using the instantaneous heart rate of the user.

8. The method of claim 7, wherein the instantaneous heart rate of the user is calculated through a formula:

$\left(\mathrm{int}\right)<br><br>\frac{60.0*\mathrm{SamplingRate}}{\#<br><br>\mathrm{SamplesBetweenBeats}}.$

9. The method of claim 7, wherein obtaining the heart rate of the user using the instantaneous heart rate of the user includes:

median filtering the instantaneous heart rate of the user.

10. A computer-implemented method for computing a movement speed of a user using an acceleration signal on the Y-axis (“

Y-acceleration signal”

), the method comprising;

(a) receiving a Y-acceleration signal concerning a user;

(b) obtaining an acceleration low pass signal;

(c) obtaining an adaptive threshold for step detection; and

(d) obtaining a movement speed of the user.

11. The method of claim 10, wherein obtaining the acceleration low pass signal includes:

low pass filtering the Y-acceleration signal.

12. The method of claim 11, wherein obtaining the adaptive threshold for step detection includes:

low pass filtering the Y-acceleration signal with a different low pass frequency from that is used for obtaining the acceleration low pass signal.

13. The method of claim 10, wherein obtaining a movement speed of the user includes:

(a) obtaining result of (the acceleration low pass signal−

the adaptive threshold for step detection); and

(b) if the result is negative and no valley has been detected in the Y-acceleration signal, computing the movement speed of the user.

14. The method of claim 13, wherein computing the movement speed of the user includes:

(a) computing instantaneous steps per minute of the user; and

(b) obtaining the movement speed of the user using the instantaneous steps per minute of the user.

15. The method of claim 14, wherein the instantaneous steps per minute of the user is calculated through a formula:

$\left(\mathrm{int}\right)<br><br>\frac{60.0*\mathrm{SamplingRate}}{\#<br><br>\mathrm{SamplesSinceLastStep}}.$

16. The method of claim 14, wherein obtaining the movement speed of the user using the instantaneous steps per minute of the user includes:

median filtering the instantaneous steps per minute of the user.

17. A computer-readable medium including computer-executable instructions for:

computing a heart rate of a user using an electrocardiogram (“

ECG”

) signal.

18. The medium of claim 17, wherein computing a heart rate of a user using an electrocardiogram (“

ECG”

) signal includes;

(a) receiving an ECG signal concerning a user;

(b) obtaining an ECG low pass signal using the ECG signal;

(c) obtaining an ECG high frequency signal using the ECG signal and the ECG low pass signal;

(d) obtaining an ECG high frequency envelope using the ECG high frequency signal;

(e) obtaining an adaptive threshold for heart beat detection using the ECG high frequency envelope; and

(f) obtaining a heart rate of the user using the adaptive threshold and the ECG high frequency envelope.

19. The medium of claim 17, further comprising:

computing movement speed of the user using an acceleration signal on the Y-axis (“

Y-acceleration signal”

).

20. The medium of claim 19, wherein computing movement speed of the user using an acceleration signal on the Y-axis (“

Y-acceleration signal”

) includes;

(a) receiving a Y-acceleration signal concerning a user;

(b) obtaining an acceleration low pass signal using the Y-acceleration signal;

(c) obtaining an adaptive threshold for step detection using the Y-acceleration signal; and

(d) obtaining a movement speed of the user using the adaptive threshold for step detection and the acceleration low pass signal.