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Heart Sound Segmentation of Pediatric Auscultations Using Wavelet Analysis

Castro, A. C. ; Vinhoza, T. T. V. ; Mattos, S. S. ; Coimbra, M.

Heart Sound Segmentation of Pediatric Auscultations Using Wavelet Analysis, Proc International Conf. of the IEEE Engineering in Medicine and Biology Society - EMBC, Osaka, Japan, Vol. -, pp. 3909 - 3912, July, 2013.

Digital Object Identifier: 10.1109/EMBC.2013.6610399

Auscultation is widely applied in clinical activity,
nonetheless sound interpretation is dependent on clinician
training and experience. Heart sound features such as spatial
loudness, relative amplitude, murmurs, and localization of
each component may be indicative of pathology. In this study
we propose a segmentation algorithm to extract heart sound
components (S1 and S2) based on it’s time and frequency characteristics.
This algorithm takes advantage of the knowledge
of the heart cycle times (systolic and diastolic periods) and of
the spectral characteristics of each component, through wavelet
analysis. Data collected in a clinical environment, and annotated
by a clinician was used to assess algorithm’s performance. Heart
sound components were correctly identified in 99.5% of the
annotated events. S1 and S2 detection rates were 90.9% and
93.3% respectively. The median difference between annotated
and detected events was of 33.9 ms.