In this paper, we present a new approach for PPG based heart rate monitoring. We first perform the variational mode decomposition to decompose the PPG signal into multiple modes then eliminate the modes whose frequencies coincides with those from accelerator signals. Finally, the spectral analysis step is applied to estimate the spectrum of the signal and selects the spectral peaks corresponding to heart rate. Experimental results on a public available dataset recorded from 12 subjects during fast running validate the performance of the proposed algorithm. | Journal of Science & Technology 131 (2018) 100-104 A Variational Mode Decomposition-Based Approach for Heart Rate Monitoring using Wrist-Type Photoplethysmographic Signals during Intensive Physical Exercise Thi-Thao Tran, Van-Truong Pham *, Dang-Thanh Bui Hanoi University of Science and Technology, No. 1, Dai Co Viet, Hai Ba Trung, Hanoi, Viet Nam Received: September 07, 2018; Accepted: November 26, 2018 Abstract Heart rate monitoring using photoplethysmographic (PPG) signals recorded from wrist during intensive physical exercise is challenging because the PPG signals are contaminated by strong motion artifact. In this paper, we present a new approach for PPG based heart rate monitoring. We first perform the variational mode decomposition to decompose the PPG signal into multiple modes then eliminate the modes whose frequencies coincides with those from accelerator signals. Finally, the spectral analysis step is applied to estimate the spectrum of the signal and selects the spectral peaks corresponding to heart rate. Experimental results on a public available dataset recorded from 12 subjects during fast running validate the performance of the proposed algorithm. Keywords: Adaptive motion artifact cancellation, Photoplethysmographic (PPG), Heart rate monitoring Variational mode decomposition, Spectral analysis 1. Introduction* There have many signal processing algorithms for motion artifact reduction from PPG signals using the simultaneously recorded accelerometer signals ., adaptive filtering [4, 6, 7], independent component analysis [8], spectral subtraction [9] models. More recently, the empirical mode decomposition (EMD) [10] has been proposed for MA reduction for PPG signals [3, 11]. Though having advantages in motion artifact cancellation, EMD have shortcomings. In the EMD, the mode-mixing problem should be handled, and the number of modes vary with different signals. As an alternative to the EMD approach, variational mode decomposition (VMD) [12] has .
