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2 STATE OF THE ART
An emotional state can be defined as a collection of
responses triggered by different parts of the body or
the brain through both neural and hormonal
networks (Damásio, 1998). Experiments conducted
with patients with brain lesions in specific areas led
to the conclusion that their social behaviour was
highly affective, together with the emotional
responses. It is unequivocal to state that emotions
are essential for humans, as they play a vital role in
their everyday life: in perception, judgment and
action processes (Damásio, 1994).
Due to the complexity of human emotions, their
analysis is often based on the identification of
distinct basic emotional states so that the analysis
and processing is simplified. For this project, three
emotional states will be studied: joy, sadness and a
neutral emotional state.
In order to analyse biometric data that contains
mainly positive and negative emotional states, it is
essential to create and define an experimental
environment that is able to induce a subject in a
specific and controlled emotional state. Nowadays, it
is common to use an actor as one possible approach
to human beings emotions’ simulation (Chanel et al.,
2005). As the actor predicts specific emotions,
outside aspects as facial expression or voice change
accordingly. However, the physiological responses
will not suffer any variations, which lead to one of
the biggest disadvantages of this approach, as the
gathered biometric information does not represent
the real emotional state of the actor.
An alternative method, adopted in this study, is
the use of multimedia stimuli (Chanel et al., 2005).
These stimuli contain a variety of contents such as
music, videos, text and images. The main advantage
of this method resides in the strong correlation
between the induced emotional states and the
physiological responses, as the emotions are no
longer simulated.
The electroencephalograph used on this project
was the NeurobitLite and is composed by 3
electrodes, one functioning as and active one and the
other two as references, using a monopolar method
strategy.
3 PROJECT DESCRIPTION
The development of an automatic tool that able to
determine the emotional state of a subject through
EEG biometric information was based on data
analysis’ methods. These methods included the
decimation; the weighted average; spikes’ removal;
and clusters for the final emotion’s assessment.
The implementation of the weighted average
technique culminated with the enunciation of a
hypothesis concerning the behaviour of the electrical
brain waves when subjects are emotionally induced.
The hypothesis follows a specific temporal
distribution and a pattern that was observed in the
majority of the experimental sessions. Figure 3
represents the evolution of Beta and Gamma
amplitudes’ over the entire experimental session.
This behaviour is considered as the pattern
behaviour for high frequency brain waves (Teixeira,
Vinhas, 2008).
The enunciated expected behaviour represents
a three step chart with each step having the duration
of two minutes. This data treatment had in mind the
three steps took into account to IAPS session
management – three sets of twenty pictures lasting
for two minutes with a grading emotional effect
from joy to sadness passing through an intermediate
neutral state.
Figure 1: Expected behaviour for high frequency waves.
In what concerns to cluster analysis, the
emotional induction results in an amplitude’s
variation according to a specific emotional state.
Having these concepts in mind, and based on the
pattern-behaviour for the EEG data previously
described, three distinct groups of data were created
based on the brain waves’ mean amplitude. Each of
these three groups have one specific centroide, a
point that is used as a reference for the neighbours of
the same cluster.
The emotional state classification, performed by the
EAT, is based on the predominant emotional state of
the subject, as previously described. In order to
evaluate the success rate of the EAT classification,
at the end of each experimental session, self-
assessment interviews were performed to subjects.
The main objective of these interviews was to attain
information concerning the predominant emotional
state, so that it could be later compared with the
results obtained from the EAT analysis. Besides this
fact, other important aspects like the apreciation of
the presented visual stimuli sequence, the
environment conditions and any disturbs during the
experimental session have been collected.
BIOSIGNALS 2009 - International Conference on Bio-inspired Systems and Signal Processing
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