Detection of Characteristic Points of Ventricular Assist Device Driving Signal, Using Wavelet Decomposition.

摘要

Pneumatic and hydraulic pressure and flow signals, measured on working ventricular assist device (VAD) during its test, describe its temporal hydrodynamic conditions, Signals registered as time samples series contain characteristic points or fragments, which reflect consecutive stages of VAD pulsate work, Because of nature of signals describing biological objects, they often can be time-varying, transient, non-stationary and affected by multi- sources noise, It makes in some situations characteristic points of pressure- flow curves unseen in time domain and automatic detection of these important instants is very difficult or even not possible. We proposed time-frequency (T- F) analysis approach, where signals are decomposed into adaptive, frequency sub- bands, using wavelet transform (WT), which is known as a suitable tool for biomedical non-stationary signal analysis As a result of using WT, the multi- resolution T-F representation is obtained, which is sensitive and can detect both long-term trends and dynamic, sudden changes in input signal. Our research signal database was created as a result of VAD tests performed for different control parameters on mock circulatory system, designed and made in our Institute, Results of proposed automatic detection procedure were presented for three types of WT basis function, We work on application of our study effects in control algorithm of testing devices for the determination of the critical control parameters of VAD work conditions.