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Authors: Carlos Carreiras 1 ; André Lourenço 2 ; Helena Aidos 1 ; Hugo Plácido da Silva 1 and Ana Fred 1

Affiliations: 1 Instituto de Telecomunicações, Portugal ; 2 Instituto Superior de Engenharia de Lisboa and Instituto de Telecomunicações, Portugal

Keyword(s): Physiological Computing, Attention, ECG, EEG, Unsupervised Learning, Cluster Validation.

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

Abstract: The electroencephalogram (EEG) signal, acquired on the scalp, has been extensively used to understand cognitive function, and in particular attention. However, this type of signal has several drawbacks in a context of Physiological Computing, being susceptible to noise and requiring the use of impractical head-mounted apparatuses, which impacts normal human-computer interaction. For these reasons, the electrocardiogram (ECG) has been proposed as an alternative source to assess emotion, which is also continuously available, and related with the psychophysiological state of the subject. In this paper we present a study focused on the morphological analysis of the ECG signal acquired from subjects performing a task demanding high levels of attention. The analysis is made using various unsupervised learning techniques, which are validated against evidence found in a previous study by our team, where EEG signals collected for the same task exhibit distinct patterns as the subjects progres s in the task. (More)


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Paper citation in several formats:
Carreiras, C.; Lourenço, A.; Aidos, H.; Plácido da Silva, H. and Fred, A. (2013). Morphological ECG Analysis for Attention Detection. In Proceedings of the 5th International Joint Conference on Computational Intelligence (IJCCI 2013) - NCTA; ISBN 978-989-8565-77-8; ISSN 2184-3236, SciTePress, pages 381-390. DOI: 10.5220/0004554403810390

author={Carlos Carreiras. and André Louren\c{C}o. and Helena Aidos. and Hugo {Plácido da Silva}. and Ana Fred.},
title={Morphological ECG Analysis for Attention Detection},
booktitle={Proceedings of the 5th International Joint Conference on Computational Intelligence (IJCCI 2013) - NCTA},


JO - Proceedings of the 5th International Joint Conference on Computational Intelligence (IJCCI 2013) - NCTA
TI - Morphological ECG Analysis for Attention Detection
SN - 978-989-8565-77-8
IS - 2184-3236
AU - Carreiras, C.
AU - Lourenço, A.
AU - Aidos, H.
AU - Plácido da Silva, H.
AU - Fred, A.
PY - 2013
SP - 381
EP - 390
DO - 10.5220/0004554403810390
PB - SciTePress