Nagarjuna Reddy Komalla

TL;DR: The merit of the method is clearly demonstrated using convergence and correlation analysis, thus making it best suitable for present-day pulse oximeters utilizing PPG sensor head with a single pair of source and detector, which does not have any extra hardware meant for capturing noise reference signal.

TL;DR: This paper presents a robust algorithm called modified multi scale principal component analysis (MMSPCA), for extraction of respiratory activity embedded in the PPG signals, which clearly outperformed the conventional MSPCA-based method in the presence of MA.

TL;DR: Test results on ECG, BP and PPG signals of the well known MIMIC database from Physiobank archive reveal that the proposed EMD method has efficiently extracted respiratory information from ECG; the evaluated similarity parameters in both time and frequency domains have shown the superiority of the method.

TL;DR: The I2DTCWT outperformed other DTCWT processing methods in respect of MA reduction and the computed spectra revealed that safe extraction of respiratory information is guaranteed from these MA reduced PPGs, and resulted in less computation cost compared to the MASIMO SET.

TL;DR: Experimental results revealed that DTCWT processing of MA corrupted PPG's outperformed the db10 wavelet processing for MA reduction of PPG signals and can be referred as best suitable MA reduction technique for pulse oximetry applications.