Extraction of Respiratory Activity from Photoplethysmographic Signals

P. Rajesh
2018 International Journal for Research in Applied Science and Engineering Technology  
The clinical significance of certain cardiac arrhythmias can be understood only with reference to respiration. In normal healthy conditions, the respiratory rate is 10-20 breaths/minute. But, certain problems of illness, accidents or some other causes affect the regular sinus rhythm. A non-invasive, non-occlusive and non-intrusive respiration monitoring is desirable in a number of situations such as ambulatory monitoring, stress tests and sleep disorder investigations. Such methods are based on
more » ... ethods are based on deriving the respiratory activity from signals such as the electrocardiogram (ECG), the photoplethysmogram (PPG). There have been several efforts for such a purpose particularly in the case of ECG-Derived Respiration (EDR). This paper presents an efficient filtering technique with a pre-processing block for extraction of respiratory signal from PPG signal. A PPG is obtained by illuminating a part of the body of interest and acquiring either the reflected or transmitted light. As the PPG signals are most frequently corrupted by the motion artifacts, the pre-processing block essentially includes a motion artifact reduction algorithm. We applied an efficient algorithm based on singular value decomposition (SVD) to extract artifact-free PPG signals. The power spectral density (PSD) of the artifact-free PPG signal, thus obtained, clearly indicates the respiration induced component in addition to the heart rate. An adaptive FIR filter, designed in frequency sampling method with suitable specifications drawn automatically from the PSD, efficiently separated heart and respiratory related signals. The respiratory rate is estimated by an automatic peak-detection algorithm applied on the extracted respiratory signal. The results indicate the efficacy of the proposed method.
doi:10.22214/ijraset.2018.5139 fatcat:4j2s4tzwxbdedfa4mcts2nwkgu