Wearable sports monitoring equipment for measuring heart rate or muscular activity and relating method

• US 20160143592A1
• Filed: 11/17/2015
• Published: 05/26/2016
• Est. Priority Date: 11/19/2014
• Status: Active Grant

• Current Assignee: Suunto Oy (Anta International Group Holdings Ltd.)
• Original Assignee: Suunto Oy (Anta International Group Holdings Ltd.)
• Inventors: Ojanen, Olli-Pekka, Martikka, Mikko, Nieminen, Heikki, Pernu, Kimmo, Lindman, Erik
• Granted Patent: US 11,457,865 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• 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 5/25 Bioelectric electrodes therefor
• CPC Class Codes: A61B 5/296 for electromyography [EMG]
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/6801 specially adapted to be attached to or worn on the body surface
• CPC Class Codes: A61B 5/6804 Garments; Clothes
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses
• CPC Class Codes: A61B 5/721 using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/7285 for synchronising or triggering a physiological measurement or image acquisition with a physiological event or waveform, e.g. an ECG signal A61B6/5205, A61B6/541, A61B8/5207, A61B8/543 take precedence

Abstract

The invention relates to wearable electronic equipment and method for measuring heart rate or muscular activity of a person. The equipment comprises one or more heartbeat or muscular activity sensors for providing a heartbeat or muscular activity signal, respectively, and a motion sensor for providing a motion signal corresponding to movement of the person. In addition, there are provided processing means for detecting from the heartbeat or muscular activity signal first events corresponding to individual heartbeats or muscle activations, respectively, and from the motion signal second events corresponding to movement changes stronger than a predefined threshold. The processing means are further programmed to form a first time series of said first events, and to determine the heartbeat or muscular activity parameter using the first time series. According to the invention, the processing means are programmed to omit from said first time series those first events that coincide with and/or take place at the same frequency as the second events. The invention helps to remove motion-induced artifacts from ECG and EMG signals for more accurate sports performance monitoring and characterization.

Claims

1. Wearable electronic equipment for determining a heartbeat or muscular activity parameter of a person, comprising:

a heartbeat or muscular activity sensor for providing a heartbeat or muscular activity signal, respectively,

a motion sensor for providing a motion signal corresponding to movement of the person, and

a processing means adapted to;

detect from the heartbeat or muscular activity signal first events corresponding to individual heartbeats or muscle activations, respectively,

detect from the motion signal second events corresponding to movement changes which are stronger than a predefined threshold,

form a first time series of said first events from only such first events that are asynchronous with and/or take place at a different frequency than the second events, and

determine said heartbeat or muscular activity parameter using the first time series.

2. The wearable electronic equipment according to claim 1, wherein the processing means is further adapted to disregard periods of the heartbeat or muscular activity signal that coincide with the second events when forming said first time series.

3. The wearable electronic equipment according to claim 2, wherein the processing means is further adapted to perform a Discrete Fourier Transform (DFT) of the first time series and to determine said heartbeat or muscular activity parameter using the output of the DFT.

4. The wearable electronic equipment according to claim 1, wherein the processing means is further adapted to:

form a temporary time series of all first events detected,

form a second time series of all second events detected, and

remove frequency components of the temporary time series that are common with at least one frequency component of the second time series in order to form said first time series.

5. The wearable electronic equipment according to claim 4, wherein the processing means is further adapted to carry out said removing frequency components by:

performing a Discrete Fourier Transform (DFT) of the first time series,

performing a Discrete Fourier Transform (DFT) of the second time series, and

reducing common frequency components of the first and second time series from the first time series.

6. The wearable electronic equipment according to claim 4, wherein at least the first and/or second time series is/are formed as binary series where one bit value represents detected events and the other bit value non-existence of such events.

7. The wearable electronic equipment according to claim 1, wherein the motion sensor is an acceleration sensor.

8. The wearable electronic equipment according to claim 1, wherein the heartbeat or muscular activity sensor includes a heartbeat sensor and the heartbeat or muscular activity parameter includes at least average heart rate, average heartbeat interval, one or more parameters derived therefrom or a combination thereof.

9. The wearable electronic equipment according to claim 1, wherein the heartbeat or muscular activity sensor includes a muscular activity sensor and the heartbeat or muscular activity parameter includes cadence and/or one or more parameters derived therefrom.

10. The wearable electronic equipment according to claim 1, wherein the one or more heartbeat or muscular activity sensors and the motion sensor are located in a single device unit.

11. The wearable electronic equipment according to claim 10, wherein the single device unit further comprises at least part of said processing means.

12. The wearable electronic equipment according to claim 1, wherein the processing means is located in a different device unit than the heartbeat or muscular activity sensor and/or the motion sensor.

13. The wearable electronic equipment according to claim 1, wherein the heartbeat or muscular activity sensor comprises electric ECG or EMG electrodes, respectively.

14. The wearable electronic equipment according to claim 13, wherein the ECG or EMG electrodes are connected to a measurement circuit with input impedance of less than 50 kOhm.

15. The wearable electronic equipment according to claim 13, wherein the ECG or EMG electrodes are laminated onto a fabric structure.

16. The wearable electronic equipment according to claim 1, wherein the heartbeat or muscular activity sensor includes an optical sensor, pressure sensor or acceleration sensor.

18. The wearable electronic equipment according to claim 1, further comprising a wireless communication unit in a first device unit comprising said heartbeat or muscular activity sensor and a first part of the processing means and being adapted to communicate said first events to a second device unit containing a second part of the processing means through said wireless communication unit.

17. (canceled)

19. A method of monitoring a physical performance of a person comprising:

measuring a heartbeat or muscular activity signal using a measurement device at least partly positionable against the skin of the person,

measuring movement of at least one part of the measurement device using a motion sensor for providing a motion signal, and

detecting from the heartbeat or muscular activity signal first events corresponding to individual heartbeats or muscle activations, respectively,

detecting from the motion signal second events corresponding to movement changes which are stronger than a predefined threshold,

forming a first time series of such first events that are asynchronous with and/or take place at a different frequency as the second events, and

determining said heartbeat or muscular activity parameter using the first time series.

20. The method according to claim 19, further comprising disregarding periods of the heartbeat or muscular activity signal that coincide with the second events when forming said first time series.

21. The method according to claim 20, further comprising performing a Discrete Fourier Transform (DFT) of the first time series and determining said heartbeat or muscular activity parameter using the output of the DFT.

22. The method according to claim 19, further comprising:

forming a temporary time series of all first events detected,

forming a second time series of all second events detected, and

removing frequency components of the temporary time series that are common with at least one frequency component of the second time series in order to form said first time series.

23. The method according to claim 22, further comprising:

performing a Discrete Fourier Transform (DFT) of the first time series,

performing a Discrete Fourier Transform (DFT) of the second time series, and

reducing common frequency components of the first and second time series from the first time series.

24. The method according to claim 22, wherein the first and/or second time series is/are formed as binary series where one bit value represents detected events and the other bit value non-existence of such events.

25. The method according to claim 19, wherein the heartbeat or muscular activity signal contains a contribution by changing contact impedance between said measurement electrodes and the skin of the person due to the movement of the measurement device.

26. The method according to claim 19, wherein the heart or muscular activity signal contains a contribution by potential changes in the vicinity of the measurement device due to accumulation of static electricity.

27. (canceled)