A comparison of statistical machine learning methods in heartbeat detection and classification

Tony Basil, Bollepalli S. Chandra, Choudur Lakshminarayan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

In health care, patients with heart problems require quick responsiveness in a clinical setting or in the operating theatre. Towards that end, automated classification of heartbeats is vital as some heartbeat irregularities are time consuming to detect. Therefore, analysis of electro-cardiogram (ECG) signals is an active area of research. The methods proposed in the literature depend on the structure of a heartbeat cycle. In this paper, we use interval and amplitude based features together with a few samples from the ECG signal as a feature vector. We studied a variety of classification algorithms focused especially on a type of arrhythmia known as the ventricular ectopic fibrillation (VEB). We compare the performance of the classifiers against algorithms proposed in the literature and make recommendations regarding features, sampling rate, and choice of the classifier to apply in a real-time clinical setting. The extensive study is based on the MIT-BIH arrhythmia database. Our main contribution is the evaluation of existing classifiers over a range sampling rates, recommendation of a detection methodology to employ in a practical setting, and extend the notion of a mixture of experts to a larger class of algorithms.

Original languageEnglish
Title of host publicationBig Data Analytics - First International Conference, BDA 2012, Proceedings
Pages16-25
Number of pages10
DOIs
StatePublished - 2012
Event1st International Conference on Big Data Analytics, BDA 2012 - New Delhi, India
Duration: 24 Dec 201226 Dec 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7678 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Conference on Big Data Analytics, BDA 2012
Country/TerritoryIndia
CityNew Delhi
Period24/12/1226/12/12

Keywords

  • Classification
  • ECG
  • Heart arrhythmia
  • Mixture of experts

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