Title :
Delineation of systolic murmurs by autoregressive modelling
Author :
Ning, Taikang ; Hsieh, Kai-Sheng
Author_Institution :
Dept. of Eng. & Comput. Sci., Trinity Coll., Hartford, CT, USA
Abstract :
Autoregressive (AR) models are used in this paper to delineate four types of systolic murmurs. The study shows that second order AR models can be effectively utilized to extract quantitative measures to accurately characterize different heart sound episodes
Keywords :
autoregressive processes; bioacoustics; cardiology; medical signal processing; physiological models; autoregressive modelling; diagnostic method; heart sound episodes characterization; heart sounds; quantitative measures; second order models; systolic murmurs delineation; Cardiovascular system; Computer science; Ear; Educational institutions; Frequency estimation; Heart; Humans; Power system modeling; Reactive power; Variable speed drives;
Conference_Titel :
Bioengineering Conference, 1995., Proceedings of the 1995 IEEE 21st Annual Northeast
Conference_Location :
Bar Harbor, ME
Print_ISBN :
0-7803-2692-X
DOI :
10.1109/NEBC.1995.513717
