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ECG Signal Compression Using Different Techniques

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Advances in Computing, Communication and Control (ICAC3 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 125))

Abstract

In this paper, a transform based methodology is presented for compression of electrocardiogram (ECG) signal. The methodology employs different transforms such as Discrete Wavelet Transform (DWT), Fast Fourier Transform (FFT) and Discrete Cosine Transform (DCT). A comparative study of performance of different transforms for ECG signal is made in terms of Compression ratio (CR), Percent root mean square difference (PRD), Mean square error (MSE), Maximum error (ME) and Signal-to-noise ratio (SNR). The simulation results included illustrate the effectiveness of these transforms in biomedical signal processing. When compared, Discrete Cosine Transform and Fast Fourier Transform give better compression ratio, while Discrete Wavelet Transform yields good fidelity parameters with comparable compression ratio.

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Author information

Authors and Affiliations

  1. Indian Institute of Information Technology Design and Manufacturing, Jabalpur, 482005, MP, India

    K. Ranjeet, A. Kumar & R. K. Pandey

Authors
  1. K. Ranjeet
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  2. A. Kumar
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  3. R. K. Pandey
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Editor information

Editors and Affiliations

  1. Fr. Conceicao Rodrigues College of Engineering Fr. Agnel Ashram, 400050, Bandstand, Bandra (West) Mumbai, India

    Srija Unnikrishnan , Sunil Surve  & Deepak Bhoir ,  & 

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Ranjeet, K., Kumar, A., Pandey, R.K. (2011). ECG Signal Compression Using Different Techniques. In: Unnikrishnan, S., Surve, S., Bhoir, D. (eds) Advances in Computing, Communication and Control. ICAC3 2011. Communications in Computer and Information Science, vol 125. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18440-6_29

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  • DOI: https://doi.org/10.1007/978-3-642-18440-6_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-18439-0

  • Online ISBN: 978-3-642-18440-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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