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Authors: Diana Batista 1 and Ana Fred 2

Affiliations: 1 Instituto Superior Técnico, Portugal ; 2 Instituto Superior Técnico and Instituto de Telecomunicações / IST, Portugal

ISBN: 978-989-758-069-7

Keyword(s): Atrial fibrillation, ECG, Wavelet, Pattern Analysis, Artificial Neural Network, k-Nearest Neighbours, Support Vector Machine.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Medical Image Detection, Acquisition, Analysis and Processing ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing ; Wavelet Transform

Abstract: Atrial fibrillation (AF) is the most common type of arrhythmia. This work presents a pattern analysis approach to automatically classify electrocardiographic (ECG) records as normal sinus rhythm or AF. Both spectral and time domain features were extracted and their discrimination capability was assessed individually and in combination. Spectral features were based on the wavelet decomposition of the signal and time parameters translated heart rate characteristics. The performance of three classifiers was evaluated: k-nearest neighbour (kNN), artificial neural network (ANN) and support vector machine (SVM). The MITBIH arrhythmia database was used for validation. The best results were obtained when a combination of spectral and time domain features was used. An overall accuracy of 99.08 % was achieved with the SVM classifier.

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Paper citation in several formats:
Batista, D. and Fred, A. (2015). Spectral and Time Domain Parameters for The Classification of Atrial Fibrillation.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015) ISBN 978-989-758-069-7, pages 329-337. DOI: 10.5220/0005283403290337

@conference{biosignals15,
author={Diana Batista. and Ana Fred.},
title={Spectral and Time Domain Parameters for The Classification of Atrial Fibrillation},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015)},
year={2015},
pages={329-337},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005283403290337},
isbn={978-989-758-069-7},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015)
TI - Spectral and Time Domain Parameters for The Classification of Atrial Fibrillation
SN - 978-989-758-069-7
AU - Batista, D.
AU - Fred, A.
PY - 2015
SP - 329
EP - 337
DO - 10.5220/0005283403290337

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