Lossless Encoders in Compression of Arrhythmia Signals

D.M. Ballesteros and A.E. Gaona Barrera (Columbia)


Modelling and simulation, intelligent analysis and design, D W T, lossless encoding.


Data compression algorithms are frequently used by data communication systems and data storage systems to reduce the information transmitted, to increase the number of channels and to reduce the storage requirements. This paper presents a real time ECG compression model which is considered in long time acquisitions as HOLTER systems. The model consists of three steps: first is to pre-process the ECG signals, second is to perform the DWT (Discrete Wavelet Transform), and third is to apply lossless encoding: run length and Huffman. The performance metrics are obtained by estimating the percentage root mean square difference (PRD) and the compression ratio (CR) in 6 ECGs (electrocardiograms) from the MIT-BIH arrhythmia database. The best results were founded with Huffman encoding with 10:1 of CR for 0.5 of PRD.

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