Storage analysis and compression of signals with application in medicine

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.