Data compression and storage into an EEG multichannel system using Wavelets technique

This paper presents the use of Wavelet function technique to compress and storage the EEG signal into a multichannel EEG system. This system consists of such components: multichannel bio-amplify, 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 experiments with implemented procedures have shown the compression ratio and SNRs values EEG in real time. Different results of the values of time for real compressing and storing are presented for DSP and AMD586 processor used.