Imperial College London
Alternate

Dr Syed Anas Imtiaz

Faculty of Engineering, Department of Electrical and Electronic Engineering

Research Fellow
 
 
 
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Contact

 

+44 (0)20 7594 6297anas.imtiaz Website

 
 
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Location

 

907Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Dwivedi:2018:10.1109/ACCESS.2018.2889437,
author = {Dwivedi, AK and Imtiaz, SA and Rodriguez, Villegas E},
doi = {10.1109/ACCESS.2018.2889437},
journal = {IEEE Access},
pages = {8316--8345},
title = {Algorithms for automatic analysis and classification of heart sounds – a systematic review},
url = {http://dx.doi.org/10.1109/ACCESS.2018.2889437},
volume = {7},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Cardiovascular diseases currently pose the highest threat to human health around the world. Proper investigation of the abnormalities in heart sounds is known to provide vital clinical information that can assist in the diagnosis and management of cardiac conditions. However, despite significant advances in the development of algorithms for automated classification and analysis of heart sounds, the validity of different approaches has not been systematically reviewed. This paper provides an in-depth systematic review and critical analysis of all the existing approaches for automatic identification and classification of the heart sounds. All statements on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2009 Checklist were followed and addressed thoroughly to maintain the quality of the accounted systematic review. Out of 1347 research articles available in the academic databases from 1963 to 2018, 117 peer-reviewed articles were found to fall under the search and selection criteria of this paper. Amongst them: 53 articles are focused on segmentation, 72 of the studies are related to the feature extraction approaches and 88 to classification, and 56 reported on the databases and heart sounds acquisition. From this review, it is clear that, although a lot of research has been done in the field of automated analysis, there is still some work to be done to develop robust methods for identification and classification of various events in the cardiac cycle so that this could be effectively used to improve the diagnosis and management of cardiovascular diseases in combination with the wearable mobile technologies.
AU  - Dwivedi,AK
AU  - Imtiaz,SA
AU  - Rodriguez,Villegas E
DO  - 10.1109/ACCESS.2018.2889437
EP  - 8345
PY  - 2018///
SN  - 2169-3536
SP  - 8316
TI  - Algorithms for automatic analysis and classification of heart sounds – a systematic review
T2  - IEEE Access
UR  - http://dx.doi.org/10.1109/ACCESS.2018.2889437
UR  - http://hdl.handle.net/10044/1/66674
VL  - 7
ER  -
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