Phonocardiography and auscultation are noninvasive, low-cost and
accurate methods for assessing heart disease. However, diagnosis by
auscultation requires great experience and there is considerable
inter-observer variation. The primary aim of this book is to
present objective signal processing tools able to extract
information from the phonocardiographic (PCG) signal. The PCG
signal is traditionally analyzed and characterized by morphological
properties in the time domain, by spectral properties in the
frequency domain or by nonstationary properties in a joint
time-frequency domain. Besides reviewing these techniques, this
book also covers recent advancements in nonlinear PCG signal
analysis. Especially, Takens' delay embedding theorem is used to
reconstruct the underlying system's state space. This processing
step provides a geometrical interpretation of the signal's
dynamics, whose structure can be used for both system
characterization and classification as well as for signal
processing tasks such as detection and prediction. In a world where
modern health care is striving for time- and cost-contained
point-of-care testing, it is now time to bring phonocardiography up
to date.
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