Evidence Accumulation Approach applied to EEG Analysis

Helena Aidos, Carlos Carreiras, Hugo Silva, Ana Fred

Abstract

Human-machine interaction is a rapidly expanding field which benefits from automatic emotion recognition. Therefore, methods that can automatically detect the emotional state of a person are important for this field, as well as for fields such as psychology and psychiatry. This paper proposes the use of clustering ensembles (CEs) to achieve such detection. We use CEs on a dataset containing EEG signals from subjects who performed a stress-inducing task. From the raw EEG data we apply filtering and processing techniques leading to three dataset types: simple EEG, EEG with eye-movement artifacts removed through Independent Component Analysis, and data-driven modes extracted using Empirical Mode Decomposition. Then, for each of these three data types, we compute band power features and phase-locking factors, yielding a total of six different feature spaces. These spaces are then analyzed using the CE framework which combines results of multiple clustering algorithms in a voting scheme. This procedure yields interesting clusters, in particular a natural tendency for finding low numbers of clusters per subject and finding clusters which are composed of consecutive test lines. These two facts combined may indicate that a change in the emotional state of the subject was detected by the proposed framework.

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Paper Citation


in Harvard Style

Aidos H., Carreiras C., Silva H. and Fred A. (2013). Evidence Accumulation Approach applied to EEG Analysis . In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-8565-41-9, pages 479-484. DOI: 10.5220/0004267804790484


in Bibtex Style

@conference{icpram13,
author={Helena Aidos and Carlos Carreiras and Hugo Silva and Ana Fred},
title={Evidence Accumulation Approach applied to EEG Analysis},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2013},
pages={479-484},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004267804790484},
isbn={978-989-8565-41-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Evidence Accumulation Approach applied to EEG Analysis
SN - 978-989-8565-41-9
AU - Aidos H.
AU - Carreiras C.
AU - Silva H.
AU - Fred A.
PY - 2013
SP - 479
EP - 484
DO - 10.5220/0004267804790484