
Ambulatory electrocardiogram (ECG) recorders are increasingly in use by people suffering from cardiac abnormalities. However, the ECG signal acquired by the ambulatory recorder is influenced by motion artifacts induced by any body movement activity (BMA). The goal of the paper is to demonstrate that it is possible to determine the BMA from the motion artifacts in the ECG signal itself. The ECG signal during a specific BMA is presumed to be an additive mix of signals due to cardiac activities, motion artifacts induced due to the BMA and sensor noise. We propose to characterize and determine the BMA from the corresponding motion artifact data in the ECG signal itself. The proposed technique is useful for removal of motion artifacts from the ECG signals for ambulatory cardiac monitoring.
Electrocardiography, Data Interpretation, Statistical, Movement, Biomedical Engineering, Humans, Monitoring, Ambulatory, Signal Processing, Computer-Assisted
Electrocardiography, Data Interpretation, Statistical, Movement, Biomedical Engineering, Humans, Monitoring, Ambulatory, Signal Processing, Computer-Assisted
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