Heart Sound Segmentation of Pediatric Auscultations Using Wavelet Analysis

• Type: Article in International Conference Proceedings Book
• Date: 2013

Authors

Ana Castro (Author) FEUP; Tiago T V Vinhoza (Author) FCUP; Sandra S Mattos (Author) Other; Miguel T Coimbra (Author) FCUP

Conference proceedings International

Title: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Pages: 3909-3912

35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

Osaka, JAPAN, JUL 03-07, 2013

Indexing

ISI Web of Knowledge - 34 Citations

Scopus - 51 Citations

Scientific classification

FOS: Engineering and technology > Environmental biotechnology

Other information

Authenticus ID: P-008-FN1

DOI: 10.1109/embc.2013.6610399

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4