Morphological ECG Analysis for Attention Detection

Carlos Carreiras, André Lourenço, Helena Aidos, Hugo Plácido da Silva, Ana Fred

2013

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 progress in the task.

Paper Citation

in Harvard Style

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 - Volume 1: NCTA, (IJCCI 2013) ISBN 978-989-8565-77-8, pages 381-390. DOI: 10.5220/0004554403810390

in Bibtex Style

@conference{ncta13,
author={Carlos Carreiras and André Lourenço 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 - Volume 1: NCTA, (IJCCI 2013)},
year={2013},
pages={381-390},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004554403810390},
isbn={978-989-8565-77-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2013)
TI - Morphological ECG Analysis for Attention Detection
SN - 978-989-8565-77-8
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