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Nonlinear Complexity Sorting Approach for 2D ECG Data Compression

Nonlinear Complexity Sorting Approach for 2D ECG Data Compression

Anukul Pandey, Butta Singh, Barjinder Singh Saini, Neetu Sood
Copyright: © 2017 |Pages: 21
ISBN13: 9781522506607|ISBN10: 1522506608|EISBN13: 9781522506614
DOI: 10.4018/978-1-5225-0660-7.ch001
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MLA

Pandey, Anukul, et al. "Nonlinear Complexity Sorting Approach for 2D ECG Data Compression." Computational Tools and Techniques for Biomedical Signal Processing, edited by Butta Singh, IGI Global, 2017, pp. 1-21. https://doi.org/10.4018/978-1-5225-0660-7.ch001

APA

Pandey, A., Singh, B., Saini, B. S., & Sood, N. (2017). Nonlinear Complexity Sorting Approach for 2D ECG Data Compression. In B. Singh (Ed.), Computational Tools and Techniques for Biomedical Signal Processing (pp. 1-21). IGI Global. https://doi.org/10.4018/978-1-5225-0660-7.ch001

Chicago

Pandey, Anukul, et al. "Nonlinear Complexity Sorting Approach for 2D ECG Data Compression." In Computational Tools and Techniques for Biomedical Signal Processing, edited by Butta Singh, 1-21. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-0660-7.ch001

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Abstract

Cardiovascular Disease (CVD) is globally acknowledged research problem. The continuous Electrocardiogram (ECG) monitoring can assist in tackling the problem of CVD. The redundancy in the monitoring of ECG signal is reduced by various signal processing techniques either in 1D or 2D domain. This chapter is having the sole objective of reviewing the existing 2D ECG data compression techniques and comparing it with the 1D compression techniques. Furthermore, proposing a novel nonlinear complexity sorting approach for 2D ECG data compression. The broad basic steps involved in the procedure are preprocessing, transformation and encoding. The preprocessing steps includes QRS detection, 2D ECG image formulation, Dc quantization and complexity sorting. The second stage of transformation includes the various decomposition techniques. At encoding stage, standard image codec (JPEG2000) can be employed. The performance evaluation of the proposed complexity sorting algorithm is performed on records of Massachusetts Institute of Technology – Beth Israel Hospital arrhythmia database.

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