Modeling and Removal of Physiological Motion Artifacts in Capacitive ECG (PMA-cECG)

点击翻译按钮获取中文摘要

Due to the non-contact measurement, the capacitive ECG (cECG) has advantages, especially where the monitoring of the heart activity has to be carried out as unobtrusively as possible. However, the stronger motion artifacts generated by the movement of the limbs or the head exhibit a severe drawback for monitoring the electrical activity of the heart and the heart rate over more extended periods. This interference can be partially compensated for by special techniques to reduce motion artifacts (such as adaptive filters) or by redundant measurements that result from the fusion of cECG with other biomedical signals. However, these previous approaches primarily aim to monitor the heart rate, where the actual ECG waveform is of little interest. However, we, the applicants, are convinced that the cECG also has high clinical relevance concerning the signal morphology, which should be developed through the understanding and compensation of the waveform deformation of the cECG signal.According to our understanding, physiological motion artifacts (internal organ movements) should be differentiated from the body's classical motion artifacts, where relatively high interference amplitudes can significantly reduce signal coverage. Physiological movement artifacts (PMAs) arise, among other things, from the cardiomechanical activity of the heart and the resulting impedance change at the electrode-tissue interface. With smaller amplitudes and synchronized nature with the ECG, PMAs can be misinterpreted as part of the signal, resulting in a faulty ECG analysis.In order to better understand the inherent waveform deformations, the time-variant coupling impedance model of the motion artifacts will be extended to a source-filter model, which represents the interference of the heart's mechanical activity on the measurement of the cECG. A multimodal sensor capturing cECG, ballistocardiography, and time-variant coupling impedance measurements will be developed to capture these signals in a study on volunteers. Physiological motion artifacts will then be analyzed in numerical simulations and a dedicated physical test bench that mimics their behavior. Finally, the results are interpreted to derive standardized procedures to handle PMAs in the cECG morphology analysis.