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Authors: Filipe Canento 1 ; André Lourenço 2 ; Hugo Silva 1 and Ana Fred 3

Affiliations: 1 Instituto Superior Técnico, Portugal ; 2 Instituto Superior Técnico and Instituto Superior de Engenharia de Lisboa, Portugal ; 3 Technical University of Lisbon / IT, Portugal

ISBN: 978-989-8565-36-5

Keyword(s): QRS Detection, ECG Segmentation, Biometrics, Identity Recognition, Real-time Analysis.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Biometrics ; Biometrics and Pattern Recognition ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Multimedia ; Multimedia Signal Processing ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing ; Telecommunications

Abstract: Recognizing an individual’s identity through the use of characteristics intrinsic to that subject is a biometric recognition problem with increasingly number of modalities and applications. Recently, the electrical activity of the heart (the Electrocardiogram or ECG) has been explored as an additional modality to recognize individuals. The ECG signal contains several features, which are unique to each individual. The preprocessing of the ECG signal and the feature extraction steps are crucial for biometric recognition to be successful. In fiducial approaches, this last step is accomplished by correctly detecting the heart beats, and performing their segmentation to extract the biometric templates afterwards. In this work, we present an overview of the different steps of an ECG biometric system, focusing on the evaluation and comparison of multiple real-time heart beat detection and ECG segmentation algorithms, and their application to biometric systems. An evaluation and comparison of the algorithms with annotated datasets (MITDB, NSTDB) is presented, and methods to combine them in order to improve performance are discussed. (More)

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Paper citation in several formats:
Canento, F.; Lourenço, A.; Silva, H. and Fred, A. (2013). On Real Time ECG Segmentation Algorithms for Biometric Applications.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013) ISBN 978-989-8565-36-5, pages 228-235. DOI: 10.5220/0004245902280235

@conference{biosignals13,
author={Filipe Canento. and André Louren\c{C}o. and Hugo Silva. and Ana Fred.},
title={On Real Time ECG Segmentation Algorithms for Biometric Applications},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)},
year={2013},
pages={228-235},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004245902280235},
isbn={978-989-8565-36-5},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)
TI - On Real Time ECG Segmentation Algorithms for Biometric Applications
SN - 978-989-8565-36-5
AU - Canento, F.
AU - Lourenço, A.
AU - Silva, H.
AU - Fred, A.
PY - 2013
SP - 228
EP - 235
DO - 10.5220/0004245902280235

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