Methods for detecting heart rate, respiration, and oxygen saturation and uses thereof
This invention generally relates to methods useful for measuring heart rate, respiration conditions, and oxygen saturation and a wearable device that incorporate those methods with a computerized system supporting data collection, analysis, readout and sharing. Particularly this present invention relates to a wearable device, such as a wristwatch or ring, for real time measuring heart rate, respiration conditions, and oxygen saturation.
1. A method for measuring and monitoring heart rate, respiration rate, and oxygen saturation of a subject with a single device comprising the step of
a) measuring reflectance of red and infrared lights off skin tissue using a biometric sensor board controlling one or more light emitting diodes (LEDs), wherein brightness of the LEDs are automatically adjusted to account for skin tone, thereby generating photoplethysmographic data;
(b) measuring movement of the subject;
(c) processing and analyzing data collected in steps a) and b), wherein the processing for each of the measured data includes (i) applying a Fourier Transform; (ii) applying a peak detector; (iii) calculating a spectral centroid; (iv) and segmenting to thereby generate heart rate, respiration rate, and oxygen saturation of the subject; and
(d) displaying or sharing results of the processed data remotely on a display.
2. The method of claim 1 , wherein the subject is a human patient or a healthy subject in need of monitoring for safety purpose.
3. The method of claim 1 , wherein said device is a wrist-worn device.
4. The method of claim 1 , wherein said biometric sensor board extracts and collects photoplethysmographic data from said subject.
5. The method of claim 1 , wherein said biometric sensor board comprises a light sensor, a dual wavelength light source (red and infrared) with an auto-gain feedback loop for calibrating skin tones and pulse strength, and a plurality of active filters for an enhanced signal to noise ratio with an auto-gain feedback loop to maintain a signal strength for signal processing.
6. The method of claim 1 , wherein said data processing and analyzing carried out by a microcontroller equipped with a central processing unit comprises noises elimination from extracted photoplethysmographic data using a motion tracking sensor for an enhanced signal to noise ratio.
7. The method of claim 6 , wherein said motion tracking sensor is an accelerometer or a gyroscope.
8. The method of claim 1 , wherein said data processing and analyzing comprises a frequency analysis using a Fourier Transform on data collected over several seconds of time, wherein said frequency is related to a specific biometric measurement of heart rate and respiration.
9. The method of claim 8 , wherein said frequency for heart rate measurement ranges from about 0.4 Hertz (Hz) to about 4 Hz; said frequency for respiration measurement ranges from about 0.05 Hz to about 0.5 Hz; and said heart rate and respiration are determined by comparing the magnitude of the peaks of the Fourier Transform for heart rate and respiration at each frequency to the magnitude of the peaks in the Fourier Transform of the accelerometer or gyroscope data in all three axes at each frequency.
10. The method of claim 1 , wherein said oxygen saturation in the blood of said subject is determined by comparing the relative signal strength of red and infrared light collected over several seconds of time.
11. A method to measure heart rate and respiration rate of a subject with a single device comprising the step of:
(a) measuring reflectance of red and infrared lights off skin tissue using a biometric sensor board controlling one or more light emitting diodes (LEDs), wherein brightness of the LEDs are automatically adjusted to account for skin tone, thereby generating photoplethysmographic data based on a time-varying photosensor signal;
(b) measuring movement of the subject, thereby generating a time-varying motion signal;
(c) processing and analyzing data collected in steps (a) and (b), wherein the processing and analyzing data includes:
(i) sampling the time-varying photosensor signal and the time-varying motion signals to thereby generate a digitized time-varying photosensor signal and digitized time-varying motion sensor signals,
(ii) applying a Fourier transform to the digitized time-varying photosensor signal and the digitized time-varying motion signals to thereby generate frequency domain spectra associated with magnitudes of the digitized time-varying photosensor signal and the digitized time-varying motions signals,
(iii) detecting peaks of the magnitudes of the spectra of the digitized time-varying photosensor signal and the digitized time-varying motions signals,
(iv) comparing the peaks of magnitudes of the frequency domain spectrum associated with the digitized time-varying photosensor signal with the peaks of magnitudes of the frequency domain spectrum associated with the digitized time-varying motion signals,
(v) identifying a peak present in the frequency domain spectrum associated with the digitized time-varying photosensor signal which is not present in the peaks of magnitudes of the frequency domain spectrum associated with the digitized time-varying motion signals, and
(vi) multiplying the frequency associated with the identified peak by 60 to thereby generate activity per minute as respiration rate; and
(d) displaying or sharing results of the processed data remotely on a display.
12. The method of claim 11 , further comprising:
(vii) computing a weighted average about the identified peak, and
(viii) segmenting the respiration rate by repeating steps i)-vii) with under-sampling digitized data obtained in step (i) based on one of N/2 or N/4, where N represents number of samples.
13. The method of claim 11 , wherein said device is a wrist-worn device.
14. The method of claim 11 , wherein said biometric sensor board extracts and collects photoplethysmographic data from said subject.
15. The method of claim 11 , wherein said biometric sensor board further comprises a light sensor, and a plurality of active filters for an enhanced signal to noise ratio with an auto-gain feedback loop to maintain a signal strength for signal processing.
16. The method of claim 11 , wherein said data processing and analyzing carried out by a microcontroller equipped with a central processing unit comprises noises elimination from extracted photoplethysmographic data using a motion tracking sensor for an enhanced signal to noise ratio.
17. The method of claim 16 , wherein said motion tracking sensor is an accelerometer or a gyroscope.
18. The method of claim 17 , wherein said Fourier transform is performed on data collected over several seconds of time, wherein said frequency is related to a specific biometric measurement of heart rate and respiration.
19. The method of claim 18 , wherein said frequency for heart rate measurement ranges from about 0.4 Hertz (Hz) to about 4 Hz; said frequency for respiration measurement ranges from about 0.05 Hz to about 0.5 Hz; and said heart rate and respiration are determined by comparing the magnitude of the peaks of the Fourier Transform for heart rate and respiration at each frequency to the magnitude of the peaks in the Fourier Transform of the accelerometer or gyroscope data in all three axes at each frequency.
20. The method of claim 11 , wherein said oxygen saturation in the blood of said subject is determined by comparing the relative signal strength of red and infrared light collected over several seconds of time.