Research on methods for detecting respiratory rate from photoplethysmographic signal. (April 2021)

• Record Type: Journal Article
• Authors: Kuwalek, Piotr; Burlaga, Bartlomiej; Jesko, Waldemar; Konieczka, Patryk
• Is Part Of: Biomedical signal processing and control. Volume 66(2021)
• Publication Date: 2021-04
• Subjects: Photoplethysmographic (PPG) signal -- Respiratory rate (RR) -- Fast Fourier transform (FFT) -- Spectrum leakage -- Empirical mode decomposition (EMD) -- Empirical wavelet transform (EWT) -- Enhanced empirical wavelet transform (EEWT); Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2021.102483
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: The use of new decomposition method (i.e. enhanced empirical wavelet transform) has been proposed to estimate respiratory rate based on the PPG signal. The accuracy of the proposed decomposition method was compared with other currently used decomposition methods (e.g. EMD, EWT) for the estimation of respiratory rate. The correctness of detection of the lack of breath has been taken into account in the evaluation of algorithms. The computational complexity of the algorithm with the proposed EEWT decomposition method was estimated and it was compared with other PPG signal decomposition methods used. The experimental results indicate that the proposed algorithm is reliable. Abstract: The persons detained by the Police require constant monitoring of their life functions. Many of them may have unidentified disease or be under the influence of psychoactive substances. The paper discusses the specifics of the considered problem and propose the solution that intercorporate registration of the photoplethysmographic signal (PPG). The heart rate, oxygen saturation and respiration rate (RR) are determined based on this signal. The main purpose of this paper is improvement and evaluation of RR estimation based on PPG signal. Although some of algorithms of this estimation are known, the problem is sensor placement and poor measuring conditions in case of detainees affecting the algorithms accuracy. For this purpose, a new approach was proposed using the enhanced empirical wavelet transform algorithm. The results obtained were compared with selected conventional methods using the PPG signal envelope, empirical mode decomposition and empirical wavelet transform. The selected measurement windows were used to reduce the inaccuracy of RR estimation (resulting from the phenomenon of spectrum leakage) based on the respiratory associated signal. The experimental data obtained from laboratory studies and clinical database were used in the research. The metrological interpretation of the results obtained from the research is discussed and conclusions are presented.