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Noise Reduction in ECG Signals Using Wavelet Transform and Dynamic Thresholding

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Emerging Trends in Neuro Engineering and Neural Computation

Part of the book series: Series in BioEngineering ((SERBIOENG))

Abstract

Biomedical signals produced by mobile sensors usually carry various noises. This poses great challenges for the subsequent signal processing and disease analysis. Thus, noise removal becomes an important step of signal processing. This research proposes a noise reduction algorithm which can be applied to noisy ECG (electrocardiogram) signals to obtain a higher signal-to-noise ratio (SNR) for further processing. The proposed algorithm utilises wavelet transform and dynamic thresholding to reduce specific types of noise embedded in raw ECG signals. To prove the efficiency of the proposed algorithm, we employ a half-hour-long real ECG signal and add different types of noise for the evaluation of the proposed algorithm. We also compare the results obtained using different families of wavelets and different decomposition levels. The experimental results show that the proposed algorithm is able to produce a higher SNR in the output signal than that in the raw test signals.

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Acknowledgements

This research is supported by European Union (EU) sponsored (Erasmus Mundus) cLINK (Centre of excellence for Learning, Innovation, Networking and Knowledge) project (EU Grant No. 2645).

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Authors and Affiliations

  1. Computational Intelligence Research Group, Faculty of Engineering and Environment, Department of Computing Science and Digital Technologies, University of Northumbria Newcastle, NE1 8ST, Newcastle, UK

    Diptangshu Pandit, Li Zhang & Nauman Aslam

  2. Institute of Biomedical Engineering Shandong University Jinan, Jinan, China

    Chengyu Liu

  3. Department of Information Technology, Jadavpur University Kolkata, Kolkata, India

    Samiran Chattopadhyay

  4. Institute for Intelligent Systems Research and Innovation, Deakin University, Waurn Ponds, VIC 3216, Geelong, Australia

    Chee Peng Lim

Authors
  1. Diptangshu Pandit
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  2. Li Zhang
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  3. Chengyu Liu
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  4. Nauman Aslam
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  5. Samiran Chattopadhyay
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  6. Chee Peng Lim
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Corresponding author

Correspondence to Li Zhang .

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Editors and Affiliations

  1. Geelong Waurn Ponds Campus, Deakin University, Institute for Intelligent Systems Research and Innovation, 3216 Waurn Ponds, Victoria, Australia

    Asim Bhatti

  2. Mayo Clinic, 55905 Rochester, Minnesota, USA

    Kendall H. Lee

  3. Materials Science and Engineering, Georgia Institute of Technology, 30332-0245 Atlanta, Georgia, USA

    Hamid Garmestani

  4. Geelong Waurn Ponds Campus, Deakin University, Institute for Intelligent Systems Research and Innovation, 3216 Waurn Ponds, Victoria, Australia

    Chee Peng Lim

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Pandit, D., Zhang, L., Liu, C., Aslam, N., Chattopadhyay, S., Lim, C.P. (2017). Noise Reduction in ECG Signals Using Wavelet Transform and Dynamic Thresholding. In: Bhatti, A., Lee, K., Garmestani, H., Lim, C. (eds) Emerging Trends in Neuro Engineering and Neural Computation. Series in BioEngineering. Springer, Singapore. https://doi.org/10.1007/978-981-10-3957-7_10

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  • DOI: https://doi.org/10.1007/978-981-10-3957-7_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3955-3

  • Online ISBN: 978-981-10-3957-7

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