Fbse-ewt-based approach for the determination of respiratory rate from ppg signals

Abstract

Respiratory rate (RR) is a vital parameter that shows signs of abnormal human breathing activity. There are various techniques for extracting RR. 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 respiratory data from PPG signals using Fourier-Bessel series expansion-based empirical wavelet transform (FBSE-EWT) in this article. We have taken 310 and 632 epochs of simultaneous recorded PPG and breathing signals from the MIMIC and Capnobase databases in order to investigate the efficiency of the suggested algorithm. RR extraction from PPG signals by FBSE-EWT shows that the root mean square errors (RMSEs) for both the MIMIC and Capnobase databases are 0.48549 breaths/min and 0.92545 breaths/min, respectively. These findings show that the suggested FBSE-EWT method is more accurate in estimating RR in comparison to other existing techniques. © 2017 IEEE.