Motion Artifact Cancellation of Seismocardiographic Recording from Moving Subjects

This paper presents a novel method of extracting seismocardiographic (SCG) data from moving adult subjects recorded via micro-electromechanical (MEMS) accelerometers. A digital signal processing system based on the normalized least mean square (NLMS) adaptive filter design is developed in MATLAB to process the signals collected from the MEMS sensor node. Standardized experiments were performed on 40 moving adult subjects. False-positives were ruled out for a more precise detection rate. The research on sliding ensemble average was also conducted to find the minimum required window size. The results indicate a detection rate of 96% and a sliding window size of 32 intervals for robust continuous monitoring, showing that adaptive filtering could be a promising technique for the cancellation of motion noise artifacts from SCG recordings in moving subjects.