An application of EMD technique in detection of tachycardia beats

Usha Desai, C. Gurudas Nayak, G. Seshikala

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

An intelligent tachycardia diagnosis system assists the clinicians in discriminating normal and various tachycardia classes of heartbeats generally in the life-threatening conditions. This paper proposes, a methodology to classify multiclass tachycardia class using Electrocardiogram (ECG) signal. In this work, tachycardia classes are marked using nonlinear transform domain method Empirical Mode Decomposition (EMD). Using which tachycardia beats namely Atrial Flutter (AFL), Atrial Fibrillation (A-Fib), Ventricular Fibrillation (V-Fib) and Normal Sinus Rhythm (NSR) is discriminated. Independent Component Analysis (ICA) is applied on the patterns for dimensionality reduction and ten-fold cross validation is executed during the classifier development. Performance of diagnosis is compared individually using these three classifiers viz. Decision Tree (DT), Rotation Forest (ROF) and Random Forest (RAF) through Cohen's kappa statistic (κ), overall accuracy (%) and class specific accuracy (%). In current study, altogether 3858 ECG beats, belonging to four classes of tachycardia are used. The results obtained presents EMD coefficients clinical significance (p<0.0001). Besides, using RAF ensemble classifier we have achieved with an accuracy of 91.21% in diagnosis of tachycardia beats. The proposed approach can be used in the cardiac portable devices such as defibrillators and telemonitoring applications.

Original languageEnglish
Title of host publicationInternational Conference on Communication and Signal Processing, ICCSP 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1420-1424
Number of pages5
ISBN (Electronic)9781509003969
DOIs
Publication statusPublished - 22-11-2016
Event2016 International Conference on Communication and Signal Processing, ICCSP 2016 - Melmaruvathur, Tamilnadu, India
Duration: 04-04-201606-04-2016

Conference

Conference2016 International Conference on Communication and Signal Processing, ICCSP 2016
CountryIndia
CityMelmaruvathur, Tamilnadu
Period04-04-1606-04-16

Fingerprint

Decomposition Techniques
Beat
Classifiers
Decomposition
Electrocardiography
Defibrillators
Random Forest
Independent component analysis
Decision trees
Classifier
Cohen's kappa
Atrial Fibrillation
Ensemble Classifier
Ventricular Fibrillation
Decompose
Statistics
Flutter
Independent Component Analysis
Dimensionality Reduction
Multi-class

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Control and Optimization

Cite this

Desai, U., Nayak, C. G., & Seshikala, G. (2016). An application of EMD technique in detection of tachycardia beats. In International Conference on Communication and Signal Processing, ICCSP 2016 (pp. 1420-1424). [7754389] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCSP.2016.7754389
Desai, Usha ; Nayak, C. Gurudas ; Seshikala, G. / An application of EMD technique in detection of tachycardia beats. International Conference on Communication and Signal Processing, ICCSP 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 1420-1424
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Desai, U, Nayak, CG & Seshikala, G 2016, An application of EMD technique in detection of tachycardia beats. in International Conference on Communication and Signal Processing, ICCSP 2016., 7754389, Institute of Electrical and Electronics Engineers Inc., pp. 1420-1424, 2016 International Conference on Communication and Signal Processing, ICCSP 2016, Melmaruvathur, Tamilnadu, India, 04-04-16. https://doi.org/10.1109/ICCSP.2016.7754389

An application of EMD technique in detection of tachycardia beats. / Desai, Usha; Nayak, C. Gurudas; Seshikala, G.

International Conference on Communication and Signal Processing, ICCSP 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1420-1424 7754389.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - An intelligent tachycardia diagnosis system assists the clinicians in discriminating normal and various tachycardia classes of heartbeats generally in the life-threatening conditions. This paper proposes, a methodology to classify multiclass tachycardia class using Electrocardiogram (ECG) signal. In this work, tachycardia classes are marked using nonlinear transform domain method Empirical Mode Decomposition (EMD). Using which tachycardia beats namely Atrial Flutter (AFL), Atrial Fibrillation (A-Fib), Ventricular Fibrillation (V-Fib) and Normal Sinus Rhythm (NSR) is discriminated. Independent Component Analysis (ICA) is applied on the patterns for dimensionality reduction and ten-fold cross validation is executed during the classifier development. Performance of diagnosis is compared individually using these three classifiers viz. Decision Tree (DT), Rotation Forest (ROF) and Random Forest (RAF) through Cohen's kappa statistic (κ), overall accuracy (%) and class specific accuracy (%). In current study, altogether 3858 ECG beats, belonging to four classes of tachycardia are used. The results obtained presents EMD coefficients clinical significance (p<0.0001). Besides, using RAF ensemble classifier we have achieved with an accuracy of 91.21% in diagnosis of tachycardia beats. The proposed approach can be used in the cardiac portable devices such as defibrillators and telemonitoring applications.

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Desai U, Nayak CG, Seshikala G. An application of EMD technique in detection of tachycardia beats. In International Conference on Communication and Signal Processing, ICCSP 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1420-1424. 7754389 https://doi.org/10.1109/ICCSP.2016.7754389