V.I. Ponomaryov, L. Nino-de-Rivera, L. Badillo, C. Juarez, and J.L. Sanchez.

Wavelet function technique to compress electroencephalographic (EEG) signals into a multichannel EEG system is presented here. Basic concepts about compression with wavelets, analysis of compression, error of compression and compression in real time are reported. The system consists of such components as multichannel bio-amplifier, analog filters, ADC, microprocessor, DSP, PCMCIA memory, etc. The algorithms to compress an 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 Wavelets functions. 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.