Session P76.1

Evaluation Measures for Adaptive PLI Filters in ECG Signal Processing

FC Chang, YD Lin*, CC Chiu, KY Chi,
CT Chang, JG Chang

Feng Chia University
Taichung, Taiwan

Many studies have been devoted to the adaptive power-line interference (PLI) filter design in ECG signal processing. However, almost all existing PLI suppression filters are developed for applications in which the presence of PLI noise is assumed a priori. Indiscriminate application of PLI suppression over ECG signal that is free of PLI noise may deform ECG morphology, and even cause degraded performance of subsequent processing. To date, little work has been done on the possibility of ECG signal degradation by such filtering operation and its impact on further processing. In order to evaluate the difference between the original and the filtered pattern, this study proposes the quantitative evaluation measures to serve the purpose. The assessments include the time needed for filtering convergence, the efficacy of frequency tracking of the adaptive filter, the relative RMS statistics in time and frequency domain, and the computational complexity of the filter. Extensive experiments have been done with artificially and practically corrupted ECG signals for four existing PLI adaptive filtering techniques (Ahlstrom and Tompkins’, Pei and Tseng’s, So's, and Ziarani and Konrad’s algorithm). The results reveal that there’s indeed ECG signal distortion resulted from these existing adaptive filters, and its severity is closely related to the selection of filter parameters. Besides, none of the existing algorithms outperform the others in all assessments. The proposed evaluation measures can also be used for the performance evaluation of suppressing the other types of artifact, such as the baseline wander and EMG corruption contaminated in ECG, after minor modification. The proposed measures also make the optimal filter design under different constraints possible in ECG signal processing.

(Abstract Control Number: 164)