PARCORR-based time-dependent AR spectrum estimation of heart wall vibrations

We present a new method for estimation of spectrum transition of nonstation ary signals in cases of low signal-to-noise ratio (SNR). Instead of the bas ic functions employed in the previously proposed time-varying autoregressiv e (AR) modeling, we introduce a spectrum transition constraint into the cos t function described by the partial correlation (PARCORR) coefficients so t hat the method is applicable to noisy nonstationary signals of which spectr um transition patterns are complex. By applying this method to the analysis of vibration signals on the interventricular septum (IVS) of the heart, no ninvasively measured by the novel method developed in our laboratory using ultrasonics, the spectrum transition pattern is clearly obtained during one cardiac cycle for normal subjects and a patient with cardiomyopathy.