An ECG Data Compression Method Via Local Maxima and ASCII Character Encoding
Raj Kumar1, Sandeep Kumar2, Manish Rai3, Sanket Kumar4
1Raj Kumar, Electronics & Communication Department, NIT Patna, India.
2Sandeep Kumar, Electronics & Communication Department, NIT Patna, India.
3Manish Rai, Electronics & Communication Department, NIT Patna, India.
4Sanket kumar, Electronics & Communication Department, NIT Patna, India.
Manuscript received on March 20, 2013. | Revised Manuscript received on April 13, 2013. | Manuscript published on April 30, 2013. | PP: 783-788 | Volume-2, Issue-4, April 2013. | Retrieval Number: D1520042413/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The electrocardiogram (ECG) compression method presented in this paper is based on ASCII character encoding. In this compression methodology, at first individual standard deviation of each part of the signal is calculated. For the region of high deviation, local maxima are extracted. To achieve a strict lossless compression in regions of high standard deviation and a tolerable lossy compression in rest of the signal, two different compression algorithms have been developed. The compression algorithm has been evaluated with the MIT-BIH Arrhythmia Database which revealed that this proposed algorithm can reduce the file size significantly with almost negligible loss of information. By using the reversed logic for reconstruction the data can be reconstructed preserving the significant ECG signal morphology.
Keywords: Creating difference array, local maxima, standard deviation, replacement of critical numbers.