Accessing heart dynamics to estimate durations of heart sounds.
Segmentation of the phonocardiogram into its major sound components is the first step in the automated diagnosis of cardiac abnormalities. Almost all of the existing phonocardiogram segmentation algorithms utilize absolute amplitude or frequency characteristics of heart sounds, which vary from one cardiac cycle to the other and across different patients. The objective of this work is to provide an efficient phonocardiogram segmentation technique, under difficult recording situations, by utilizing the underlying complexity of the dynamical system (heart) giving rise to the heart sound. Complexity-based segmentation is invariant to amplitude and frequency variations of the heart sound and yields better time gates for heart sounds.
Nigam
Vivek
V
Electrical and Computer Engineering Department, University of Illinois at Chicago, M/C 154, 851 South Morgan, 60607, USA. vnigam1@uic.edu
Priemer
Roland
R
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006331:Heart Diseases / Q000175:diagnosis* / Q000503:physiopathology*; D006347:Heart Sounds / Q000502:physiology*; D006801:Humans; D008955:Models, Cardiovascular; D010363:Pattern Recognition, Automated / Q000379:methods; D010701:Phonocardiography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013018:Sound Spectrography / Q000379:methods*; D013997:Time Factors