Performance Comparison of EM, MEM, CTM, PCA, ICA, Entropy and MI for Photoplethysmography Signals
P. Sunil Kumar and R. HarikumarResearch Scholar, Department of ECE Bannari Amman Institute of Technology India
Abstract: Photoplethysmography (PPG) is used for the estimation of the blood flow of skin using an infrared light technique. It can measure parameters such as cardiac output, blood saturation level, blood pressure and oxygen saturation to a great extent. The greatest advantage of Photoplethysmography is that it is non-invasive in nature, has a low production and maintenance cost. For the early screening and detection of much body related pathologies PPG is the most developed and helpful tool nowadays. This paper analyses the PPG signals with respect to the parameters like Principal Component Analysis (PCA), Independent Component Analysis (ICA), Mutual Information (MI) and Entropy. PPG has also proved to be one of the most promising technologies for the early screening of heart related pathologies. This paper also analyses the PPG signals with respect to the parameters like Expectation Maximization (EM), Minimum Expectation Maximization (MEM) and Centre Tendency Moment (CTM).
Keywords: PPG; PCA; ICA; MI; Entropy EM; MEM; CTM Back to TOC