Motion Artifact Reduction In Photoplethysmography Utilizing Empirical Mode Decomposition Method
1. Motion Artifact Reduction In Photoplethysmography Utilizing Empirical Mode Decomposition Method Wang Qian Institute of biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Key Laboratory of Biomedical information and Health Engineering. D.Y. Che, Institute of biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Key Laboratory of Biomedical information and Health Engineering. Y. T Zhang. is with the Joint Research Center for Biomedical Engineering, Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong. CAS/CUHK Research centre for Biosensors and Medical Instruments
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3. CAS/CUHK Research centre for Biosensors and Medical Instruments (a) seven IMF components of simulated PPG by EMD method;
4. CAS/CUHK Research centre for Biosensors and Medical Instruments (b) instantaneous frequencies of IMF components in (a).
5. CAS/CUHK Research centre for Biosensors and Medical Instruments (c) extracted clean PPG using EMD method and band-pass filter
6. Lauterbur Biomedical Imaging Center For the PPG signal is not generated from a stationary, randomly rescaled linear Gaussian noise [3], the EMD method is will suited to processing of the PPG especially with the motion artifact. The signal-to-noise is 6.2 dB after processing compared to 1.7 dB before processing, and the peak detection rate rises from 38.3% to 86.9%. Qualitative analysis of a larger number of signals shows that the algorithm appears to exhibit sound effects. However, the problem still exist, there is much room for improvement in the motion artifact reduction in PPG using the EMD method. Thank you Results