Modified Thresholding Technique of MMSPCA for Extracting Respiratory Activity from Short Length PPG Signal

In this paper, we propose an automatic threshold selection of modified multi scale principal component analysis (MMSPCA) for reliable extraction of respiratory activity (RA) from short length photoplethysmographic (PPG) signals. MMSPCA was applied to the PPG signal with a varying data length, from 30 seconds to 60 seconds, to extract the respiratory activity. To examine the performance, we used 100 epochs of simultaneously recorded PPG and respiratory signals extracted from the MIMIC database (Physionet ATM data bank). The respiratory signal used as the ground truth and several performance measurement metrics such as magnitude squared coherence (MSC), correlation coefficients (CC), and normalized root mean square error (NRMSE) were used to compare the performance of MMSPCA based PPG derived RA. At the data length of 30 seconds, MSC, CC and NRMSE for proposed thresholding were 0.65, 0.62 and -0.82 dB respectively where as they were 0.68, 0.47 and 0.25 dB respectively for existing thresholding. These results illustrated that the proposed threshold selection performs better than existing threshold selection for short length data.