Paper Info
Title
An Approach For Automatic Identification Of Fundamental And Additional Sounds From Cardiac Sounds Recordings
Abstract
This paper presents an approach for automatic segmentation of cardiac events from non-invasive sounds recordings, without the need of having an auxiliary signal reference. In addition, methods are proposed to subsequently differentiate cardiac events which correspond to normal cardiac cycles, from those which are due to abnormal activity of the heart. The detection of abnormal sounds is based on a model built with parameters which are obtained following feature extraction from those segments that were previously identified as normal fundamental heart sounds. The proposed algorithm achieved a sensitivity of 91.79% and 89.23% for the identification of normal fundamental, S-1 and S-2 sounds, and a true positive (TP) rate of 81.48% for abnormal additional sounds. These results were obtained using the PASCAL Classifying Heart Sounds challenge (CHSC) database.
Year
DOI
Venue
2019
10.1109/EMBC.2019.8857695
2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Field
DocType
Volume
Computer vision,Stethoscope,Computer science,Segmentation,Speech recognition,Feature extraction,Time–frequency analysis,Artificial intelligence,Cardiac sounds,Heart sounds
Conference
2019
ISSN
Citations 
PageRank 
1557-170X
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Amit Krishna Dwivedi100.34
Esther O. Rodríguez-Villegas2247.08