Application of SWT for Heart Rate Monitoring Using Smartphone Camera

Application of SWT for Heart Rate Monitoring Using Smartphone Camera

Paper in proceedings (conference paper)

Monitoring of heart rate using smartphone is very popular nowadays. There exist some applications for smartphone with usually unknown accuracy. But there is no certified application for this purpose. The article introduces new method for heart rate monitoring which uses smartphone´s built-in camera and LED light. The algorithm is based on extraction of photoplethysmogram and use of stationary wavelet transform. 52 various wavelets were tested in terms of their suitability for heart rate monitoring. The accuracy is compared with heart rate estimated from electrocardiogram. In the range of 55-111 bpm, the heart rate can be estimated with mean error of 0.4093 bpm and maximum error of 0.8458 bpm. The recommended settings of the algorithm is to use green photoplethysmogram (green color channel of the video), provide stationary wavelet transform with 6-level decomposition, rbio2.4 wavelet, and calculate heart rate using PPG peaks’ distance. Data of lower and higher heart rate were tested as well.

Monitoring of heart rate using smartphone is very popular nowadays. There exist some applications for smartphone with usually unknown accuracy. But there is no certified application for this purpose. The article introduces new method for heart rate monitoring which uses smartphone´s built-in camera and LED light. The algorithm is based on extraction of photoplethysmogram and use of stationary wavelet transform. 52 various wavelets were tested in terms of their suitability for heart rate monitoring. The accuracy is compared with heart rate estimated from electrocardiogram. In the range of 55-111 bpm, the heart rate can be estimated with mean error of 0.4093 bpm and maximum error of 0.8458 bpm. The recommended settings of the algorithm is to use green photoplethysmogram (green color channel of the video), provide stationary wavelet transform with 6-level decomposition, rbio2.4 wavelet, and calculate heart rate using PPG peaks’ distance. Data of lower and higher heart rate were tested as well.

heart rate, pulse rate, HR, wavelet transform, WT, smartphone, camera, Faros, ECG, photoplethysmogram, PPG

heart rate, pulse rate, HR, wavelet transform, WT, smartphone, camera, Faros, ECG, photoplethysmogram, PPG

NĚMCOVÁ, A.; VÍTEK, M.

2018

30.08.2017

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

Brno

978-80-214-5526-9

Proceedings of IEEE Student Branch Conference Mikulov 2017

49

52

4

http://www.radio.feec.vutbr.cz/ieee/userfiles/downloads/archive/2017-Mikulov/Proceedings_Mikulov_2017.pdf

http://hdl.handle.net/