Motion Artifact Cancellation From a Single Channel SCG Using Adaptive Forgetting Factor Recursive Least Square Filter

This work proposes a novel filter for motion artifact cancellation from a single channel seismocardiography (SCG) data recorded by a tri-axis accelerometer. A real time adaptive forgetting factor recursive least square filter (AFFRLSF) was developed and embedded in our designed single channel SCG recorder system (SCSRS) for motion artifact cancellation, heartbeat signal extraction, and heart rate calculation. This SCSRS was placed on the chest wall of 24 subjects who were asked to perform standing, walking, jogging, and jumping movements on a treadmill. We recorded the single channel SCG signal and the standard Electrocardiogram (ECG) lead I signal by placing one electrode on the right arm (RA) and another on the left arm (LA) of the subjects. The heartbeat signals were extracted and heart rates were calculated from the output of AFFRLSF. The graphs of the extracted heartbeat signals were very clear under all the standing, walking, jogging, and jumping motions. The results indicate an average correlation coefficient of up to 0.9878 between heart rates estimated from SCG and ECG of all the 24 subjects. This observation shows that the proposed AFFRLSF could be an effective method for motion artifact cancellation from recorded single channel SCG signals.