ECG Signal Compression Implementation by a New 2-Dimensional Transform Technique
Pushpendra Singh1, Om Prakash Yadav2, Yojana Yadav3
1Pushpendra Singh, Electronics & Telecommunication Engineering, Chhatrapati Shivaji Institute of Technology, Durg (C.G.), India.
2Om Prakash Yadav, Electronics & Telecommunication Engineering, Chhatrapati Shivaji Institute of Technology, Durg (C.G.), India.
3Yojana Yadav, Electronics & Telecommunication Engineering, Chhatrapati Shivaji Institute of Technology, Durg (C.G.), India.
Manuscript received on July 17, 2012. | Revised Manuscript received on August 16, 2012. | Manuscript published on August 30, 2012. | PP:167-170 | Volume-1 Issue-6, August 2012. | Retrieval Number: F0654081612/2012©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: Electrocardiogram signal compression algorithm is needed to reduce the amount of data to be transmitted, stored and analyzed, without losing the clinical information content. This work investigates a set of ECG signal compression schemes to compare their performances in compressing ECG signals. These schemes are based on transform methods such as discrete cosine transform (DCT), fast fourier transform (FFT), discrete sine transform (DST), and their improvements. An improvement of a discrete cosine transform (DCT)-based method for electrocardiogram (ECG) compression is also presented as DCT-II. A comparative study of performance of different transforms is made in terms of Compression Ratio (CR) and Percent root mean square difference (PRD).The appropriate use of a block based DCT associated to a uniform scalar dead zone quantiser and arithmetic coding show very good results, confirming that the proposed strategy exhibits competitive performances compared with the most popular compressors used for ECG compression. Each specific transform is applied to a pre-selected data segment from the CSE database, and then compression is performed.
Keywords: Compression Ratio, Compression factor, Compression time, ECG, PRD.