A time-varying AR modeling of heart wall vibration

We present a new method that can be used to estimate the spectrum transition of nonstationary signals in low signal-to-noise ratio (SNR) cases. If the spectrum transition pattern is complex and/or there are large differences in the transition patterns among the individual nonstationary signals, it is difficult to estimate the transition pattern stably by the previously proposed time-varying AR modeling because the results are considerably dependent on the choice of the basic functions to be used. We propose a new modeling approach to estimate the spectrum transition of nonstationary signals by using a linear algorithm without assuming any basic functions. Instead of basic functions we use the spectrum transition constraint. By applying this method to the analysis of vibration signals on the interventricular septum of the heart, noninvasively measured by a method developed in our laboratory using ultrasonic, a spectrum transition pattern is obtained during one beat period. The proposed method will serve a tool for the noninvasive acoustic diagnosis of heart diseases in the near future