Determination of respiratory and heart rates from PPG signals using FBSE-EWT method

Abstract

Respiratory rate (RR) and heart rate (HR) are vital parameters that show signs of abnormal human breathing activity. There are various techniques for extracting RR and HR. In addition to oxygen saturation (SpO2) and cardiac rate measurement, the photoplethysmography (PPG) signal can be used to obtain breathing information that prevents the additional measurement sensor from being used. An algorithm has been suggested for the extraction of RR and HR from PPG signals using Fourier-Bessel series expansion based empirical wavelet transform (FBSE-EWT) in this work. We have taken 310 and 632 epochs of simultaneous recorded PPG and breathing signals from MIMIC and capnobase databases in order to investigate the e ciency of the suggested algorithm. RR extraction from PPG signals by FBSE-EWT shows that the root mean square errors (RMSEs) for both MIMIC and capnobase databases are 0.48549 breaths/minute and 0.92545 breaths/minute. For HR, RMSEs are 2.39632 beats/min and 1.444 beats/min for both MIMIC and capnobase databases, respectively. These ndings show that the suggested FBSE-EWT method is more accurate in estimating RR in comparison to other existing techniques.