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Application of bioradiophotonics methods for the processing of bioelectric signals

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The application of modern and perspective bioradiophotonics methods on the basis of optical and acousto-optic devices for the processing of bioelectric signals (BES) have been considered. The basic application difficulties of these methods are connected with the fact that the studied signals are of low frequencies, and development of special actions are required for the processing devices adapting. It has been proposed to introduce into acousto-optic processing system with time integration the bioelectric signals using method of high frequency carrier with linear frequency modulation which is modulated by low frequency signal. The system configuration has to provide the realization of convolution procedure; hence, the used Bragg cells must be oriented oppositely to each other. The performed analysis has shown that it is possible to realize both signal power spectrum calculation and its wavelet transform; the presence of carrier is obligatory for both kinds of processing. Also, the method of the preliminary BES compression has been proposed for its transmission into the high frequency area. In this case, the possibility occurs to introduce the signal into the acousto-optic processing system with spatial integration. In the simple acousto-optic correlator with the reference transparency the envelope of the correlation function is formed depending on time. Using the set of the reference transparencies in the multichannel correlator, it is possible to realize the prolonged BES wavelet analysis using the mother wavelet. The optical preliminary BES processing can be also performed using liquid crystal arrays. The analysis of the processing of electrocardiac signals obtained from the experimental animals (rats) has been listed using the liquid crystal array for the signal introduction into optical processing system. It has been shown that both spectral and wavelet processing can be realized in this case without using of the high frequency carrier by the low frequency signal. The use of the obtained results will make it possible to create a new family of devices for wavelet processing of bioelectrical signals implemented in real time which will make an important contribution to improving the diagnosis of diseases of the cardiovascular system, the cortex, and the central nervous system.

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