PPG Signal for Extraction of Respiratory Activity and HR Monitoring of CHF Patients

The fact that the Photoplethysmograph (PPG) signal caries respiratory information in addition to arterial blood oxygen saturation attracted the researchers to extract the respiratory information from it. In this current work, we present an efficient algorithm, based on the multi scale principal component analysis (MSPCA) technique to extract the respiratory activity from the PPG signals. MSPCA is a powerful combination of wavelets and principal component analysis (PCA). In MSPCA technique, PCA is used in computing coefficients of wavelet at each scale, and finally combining all the results at relevant scales. With this aim displaying of heart rate and the extraction of respiratory activity is done. MSPCA performed exceptionally well for extraction of respiratory activity from PPG. Index terms – Heart rate, MSPCA, PCA, Photoplethysmogram (PPG), Respiratory signal, Wavelets.