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Sensors 2017, 17(2), 234; doi:10.3390/s17020234

Set-Based Discriminative Measure for Electrocardiogram Beat Classification

1,* , 1,2
and
1
1
School of Instrument Science and Engineering, Southeast University, 2 Sipailou, Nanjing 210096, China
2
School of Basic Medical Sciences, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
*
Author to whom correspondence should be addressed.
Academic Editor: Subhas Chandra Mukhopadhyay
Received: 2 December 2016 / Revised: 10 January 2017 / Accepted: 16 January 2017 / Published: 25 January 2017
(This article belongs to the Section State-of-the-Art Sensors Technologies)
View Full-Text   |   Download PDF [788 KB, uploaded 25 January 2017]   |  

Abstract

Computer aided diagnosis systems can help to reduce the high mortality rate among cardiac patients. Automatical classification of electrocardiogram (ECG) beats plays an important role in such systems, but this issue is challenging because of the complexities of ECG signals. In literature, feature designing has been broadly-studied. However, such methodology is inevitably limited by the heuristics of hand-crafting process and the challenge of signals themselves. To address it, we treat the problem of ECG beat classification from the metric and measurement perspective. We propose a novel approach, named “Set-Based Discriminative Measure”, which first learns a discriminative metric space to ensure that intra-class distances are smaller than inter-class distances for ECG features in a global way, and then measures a new set-based dissimilarity in such learned space to cope with the local variation of samples. Experimental results have demonstrated the advantage of this approach in terms of effectiveness, robustness, and flexibility based on ECG beats from the MIT-BIH Arrhythmia Database. View Full-Text
Keywords: ECG beat classification; set-based discriminative measure; metric space; set-based dissimilarity ECG beat classification; set-based discriminative measure; metric space; set-based dissimilarity
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Li, W.; Li, J.; Qin, Q. Set-Based Discriminative Measure for Electrocardiogram Beat Classification. Sensors 2017, 17, 234.

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