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Proceedings Paper

Storage analysis and compression of signals with application in medicine
Author(s): Volodymyr I. Ponomaryov; Leonardo Badillo; Cristina Juarez; Jose L. Sanchez; Luis Igartua
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Paper Abstract

This paper presents the use of Wavelet function technique to compress and storage the electroencephalographic (EEG) signal into a multichannel EEG system. The system consists of such components: multichannel bio-amplifier, analog filters, ADC, microprocessor, DSP, PCMCIA memory, etc. The algorithms to compress EEG signal have been implemented using language C/C++. The proposed digital FIR filter to compress the signal has own coefficients chosen as the coefficients of Daubechies Wavelets. The results of the experiments with implemented procedures have shown the compression ratio and SNR values for EEG signal in the case of real time compression. Values of real time compressing and storing parameters are presented when DSP and AMD586 processor used. The Backpropagation Neural Network was used to carry out the identification of EEG Patterns in the case of epilepsy illness.

Paper Details

Date Published: 10 January 2003
PDF: 9 pages
Proc. SPIE 5021, Storage and Retrieval for Media Databases 2003, (10 January 2003); doi: 10.1117/12.476303
Show Author Affiliations
Volodymyr I. Ponomaryov, Instituto Politecnico Nacional (Mexico)
Leonardo Badillo, Instituto Politecnico Nacional (Mexico)
Cristina Juarez, Instituto Politecnico Nacional (Mexico)
Jose L. Sanchez, Instituto Politecnico Nacional (Mexico)
Luis Igartua, Instituto Politecnico Nacional (Mexico)


Published in SPIE Proceedings Vol. 5021:
Storage and Retrieval for Media Databases 2003
Minerva M. Yeung; Rainer W. Lienhart; Chung-Sheng Li, Editor(s)

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