Spectral analysis of cardiovascular series has been proposed as a noninvasive tool for investigating the autonomic control of the cardiovascular system. The analysis of such series during autonomic tests requires high resolution estimators that are capable to track the transients of the tests. A comparative evaluation has been made among classical (FFT based), autoregressive (both block and sequential mode) and time-frequency representation (TFR) based power spectral estimators. The evaluation has been performed on artificial data that have typical patterns of the nonstationary series. The results documented the superiority of the TFR approach when a sharp time resolution is required. Moreover, the test on a RR-like series has shown that the smoothing operation is effective for rejecting TFR cross-terms when a simple, two-three components series is concerned. Finally, the preliminary application of the selected methods to real RR interval time series obtained during some autonomic tests has shown that the TFR are capable to correctly represent the transient of the series in the joint time-frequency domain.
This paper proposes a multiresolution transform which allows to choose, at eachfrequency, the most appropriate balance between time and frequency resolution according to the signal characteristics and to spec@ goals of the analysis. For the analysis of cardiovascular time series it is proposed to use a resolution in time which changes with frequency according to a parametric sigmoid junction. It results a near constant Q analysis in the central range of frequency and a near constant time-frequency resolution at the extremities. Synthetic and real data obtained from 20 patients during of autonomic tests were analyzed. The ,following results were obtained: at high ,frequency high time resolution is achieved and even short duration components are detected; at low frequency the good ,frequency resolution allows to discriminate among close low frequency components.
The current role of ECG and signal monitoring in the diagnosis of Ischaemic Heart Disease is outlined in relation to imaging techniques giving accurate information on myocardial anatomy and function. ECG monitoring during stress testing remains the first step non-invasive method providing pathophysiological information. Long term continuous monitoring of the ECG and of other signals (e.g. arterial blood pressure and respiration) is commonly used to control patients with suspected or ascertained IHD. Progress of technology and of signal processing methods are driving the exploitation of signal information for diagnosis, prognosis and therapy control of ischaemic patients.
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