Abstract
This study evaluated the effectiveness of different types of wavelets and thresholds to process electrocardiograms. An electrocardiogram, or ECG, shows the electrical activity in the heart and can be used to detect abnormalities. The first process used term-by-term thresholding to denoise ECGs. The second process denoised and compressed ECGs using global thresholding. The effectiveness was determined by using the signal-to-noise ratio (SNR) and the percentage root mean square difference (PRD).
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Acknowledgements
This research was conducted as part of the Central Michigan University LURE program during 2009–2011 and was supported by NSF-REU grant # 0606-36528. The authors are grateful for the support and would like to thank the anonymous referees’ helpful comments as well.
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Lin, EB., Haske, M., Smith, M., Sowards, D. (2013). Wavelet Analysis of ECG Signals. In: Shen, X., Zayed, A. (eds) Multiscale Signal Analysis and Modeling. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4145-8_10
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DOI: https://doi.org/10.1007/978-1-4614-4145-8_10
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