Wavelet analysis of compressed biomedical signals

The paper proposes mathematical apparatus that can be used for wavelet analysis of compressed biomedical signals. As an example of biomedical signals, electrocardiogram and electroencephalogram are considered. A brief description of these signals is given. In the basis of the proposed algorithm of wavelet analysis of compressed biomedical signals lies the use of wavelet decomposition of the signal with the subsequent analysis of approximating coefficients of the set level with the use of continuous wavelet transform and synthesized wavelet. Below is suggested a brief description of the wavelet synthesis procedure for continuous wavelet transform as well as neural network and spline wavelet models proposed by the author. It has been practically proven that application of this algorithm allows us to compress electrocardiogram and electroencephalogram 8 times. In this case possibility to detect the target feature in biomedical signal based on the analysis results of the continuous wavelet transform. Noted, however, that the use of wavelet compression results in a loss of high frequency information in a signal. Therefore, the algorithm must not be applied in cases where the preservation of small fragments in a signal typical of high-frequency components is very important. This algorithm can be applied in the implementation of wavelet analysis of biomedical signals system on mobile devices, where it is important to reduce the amount of stored, transmitted and / or processed information.