Utilization of Mean and Median Strains in Principal and Independent Component Analysis to Remove Motion Artefact from Electrocardiography Signals
Motion artefact is the biggest concern in Electrocardiogram signals, especially when recording long-term measurements. Current studies fail to address the major source of motion artefact, which is skin stretch. This study utilizes two-dimensional strain fields as motion information in two advanced algorithms- Principal Component Analysis (PCA) and Independent Component Analysis (ICA). The strain fields were computed using point tracking and infinitesimal strain theory and a comparison of mean and median strains as motion information was made. The highest improvement in Signal to Noise ratio (SNR) was observed when the mean values of strain fields over a region of interest per ECG sample were taken as motion information in ICA. The lowest SNRs were obtained when PCA and ICA were implemented without any motion information.