TY - GEN
T1 - Filtering of noise in electrocardiographic signals using an unbiased and normalized adaptive artifact cancellation system
AU - Wu, Yunfeng
AU - Rangayyan, Rangaraj M.
AU - Wu, Ye
AU - Ng, Sin Chun
PY - 2007
Y1 - 2007
N2 - The electrocardiogram (ECG) is routinely used for the diagnosis of cardiovascular diseases. The removal of artifacts in ambulatory ECG recordings is essential in many biomedical applications. In this paper, we present the design of an unbiased linear filter with normalized weight coefficients in an adaptive artifact cancellation (UNAAC) system. We also develop a new weight coefficient adaptation algorithm that normalizes the filter coefficients, and utilize the steepest-descent algorithm to effectively cancel the artifacts present in ECG signals. The proposed UNAAC system was tested through experiments on the benchmark MIT-BIH database. Empirical results demonstrate that the UNAAC system can effectively eliminate two types of predominant artifacts: baseline wander and muscle-contraction artifact. Furthermore, the proposed UNAAC system achieved significantly higher signal-to-noise and signal-to-error ratios in the enhanced ECG signals, as compared with the normalized least-mean-square (NLMS) filter.
AB - The electrocardiogram (ECG) is routinely used for the diagnosis of cardiovascular diseases. The removal of artifacts in ambulatory ECG recordings is essential in many biomedical applications. In this paper, we present the design of an unbiased linear filter with normalized weight coefficients in an adaptive artifact cancellation (UNAAC) system. We also develop a new weight coefficient adaptation algorithm that normalizes the filter coefficients, and utilize the steepest-descent algorithm to effectively cancel the artifacts present in ECG signals. The proposed UNAAC system was tested through experiments on the benchmark MIT-BIH database. Empirical results demonstrate that the UNAAC system can effectively eliminate two types of predominant artifacts: baseline wander and muscle-contraction artifact. Furthermore, the proposed UNAAC system achieved significantly higher signal-to-noise and signal-to-error ratios in the enhanced ECG signals, as compared with the normalized least-mean-square (NLMS) filter.
UR - http://www.scopus.com/inward/record.url?scp=48049117350&partnerID=8YFLogxK
U2 - 10.1109/NFSI-ICFBI.2007.4387718
DO - 10.1109/NFSI-ICFBI.2007.4387718
M3 - Conference contribution
AN - SCOPUS:48049117350
SN - 1424409489
SN - 9781424409488
T3 - Proc. of 2007 Joint Meet. of the 6th Int. Symp. on Noninvasive Functional Source Imaging of the Brain and Heart and the Int. Conf. on Functional Biomedical Imaging, NFSI and ICFBI 2007
SP - 173
EP - 176
BT - Proc. of 2007 Joint Meet. of the 6th Int. Symp. on Noninvasive Functional Source Imaging of the Brain and Heart and the Int. Conf. on Functional Biomedical Imaging, NFSI and ICFBI 2007
T2 - 2007 Joint Meeting of the 6th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the International Conference on Functional Biomedical Imaging, NFSI and ICFBI 2007
Y2 - 12 October 2007 through 14 October 2007
ER -
