Abstract
Accurate recording and precise analysis of the electrocardiogram (ECG) signals are crucial in the pathophysiological study and clinical treatment. These recordings are often corrupted by different artifacts. The aim of this study is to propose two different methods, wavelet transform based on nonlinear thresholding and a combination method using wavelet and independent component analysis (ICA), to remove motion artifact from ECG signals. To evaluate the performance of the proposed methods, the developed techniques are applied to the real and simulated ECG data. The results of this evaluation are presented using quantitative and qualitative criteria. The results show that the proposed methods are able to reduce motion artifacts in ECG signals. Signal to noise ratio (SNR) of the wavelet technique is equal to 13.85. The wavelet-ICA method performed better with SNR of 14.23.
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© 2015 Springer International Publishing Switzerland
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Abbaspour, S., Gholamhosseini, H., Linden, M. (2015). Evaluation of Wavelet Based Methods in Removing Motion Artifact from ECG Signal. In: Mindedal, H., Persson, M. (eds) 16th Nordic-Baltic Conference on Biomedical Engineering. IFMBE Proceedings, vol 48. Springer, Cham. https://doi.org/10.1007/978-3-319-12967-9_1
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DOI: https://doi.org/10.1007/978-3-319-12967-9_1
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12966-2
Online ISBN: 978-3-319-12967-9
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