Boronoyev V.V., Garmaev B.Z.

Detection algorithms of signal components are essential for many types of biomedical signal analysis and patient monitoring. There are a few publications in which algorithms detect ing signal components of pressure signals are described. Nowadays, wavelet transform is used for the analysis of non-stationary signals. Wavelet transform is applied to the detail analysis of non-stationary signals which have complicated structures like pressure waves. This is especially important for detecting the signal components in low amplitude segments; the definition of their positions has principle importance for the accuracy of the diagnosis. The aim of this work is the development of novel wavelet-based detection method for the pressure signal components. The method have three steps of signal processing. Step 1. Wavelet transform: For continuous wavelet transform we use the Haar wavelet. Step 2. Choice of scale: This stage of the algorithm consists in the choice of the scale of wavelet coefficients for subsequent analysis. The scale value has to be chosen for error minimization. Step 3. Signal component detection: On the final stage, the zero (or nearest to the zero) values of the wavelet coefficients on the selected scale determine the signal extrema. Using these points we can detect signal components. For estimation of precision we damp modeling signal and detect its components. The estimation show that method is able to detect signal component which has amplitude equal to one sampling interval. In paper we compare wavelet-based method with other methods. There are methods based on The algorithm is more precise detect pressure signal components than method based on spline approximation. This algorithm have same precision as one based on Tikhinov-s regularization. But wavelet-based algorithm is faster and not required high computational resource. That why the wavelet-based detection method for pressure signal components is more effective. Novel detection method can be used to detect the beat of pressure signals and the pressure signal components. This method is very simple to use and can have many applications