2016
DOI: 10.1109/tcyb.2015.2498974
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A Classification Algorithm for Electroencephalography Signals by Self-Induced Emotional Stimuli

Abstract: The aim of this paper is to propose a real-time classification algorithm for the low-amplitude electroencephalography (EEG) signals, such as those produced by remembering an unpleasant odor, to drive a brain-computer interface. The peculiarity of these EEG signals is that they require ad hoc signals preprocessing by wavelet decomposition, and the definition of a set of features able to characterize the signals and to discriminate among different conditions. The proposed method is completely parameterized, aimi… Show more

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Cited by 45 publications
(21 citation statements)
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References 40 publications
(42 reference statements)
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“…One of their findings for the most relevant frequency band is same as that of ours. Lacoviello et al [17] worked on same paradigm of self-induced emotions, but with recalling unpleasant odor for the feeling of disgust. They used an eight-channel EEG sensor and found classification accuracy using only one channel.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…One of their findings for the most relevant frequency band is same as that of ours. Lacoviello et al [17] worked on same paradigm of self-induced emotions, but with recalling unpleasant odor for the feeling of disgust. They used an eight-channel EEG sensor and found classification accuracy using only one channel.…”
Section: Resultsmentioning
confidence: 99%
“…From the studies conducted in the domain of electroencephalography (EEG) based brain computer interfaces (BCI), it has been found that human emotions can be identified and discriminated from each other using EEG brain signals [12,13,14,15,16,17]. Although at the same time, we observe that studies on neural correlations of memory-evoked emotions, specifically fear, are scant.…”
Section: Introductionmentioning
confidence: 87%
“…Many researchers have endeavored to develop algorithms to improve performance [22,23]. Channel selection methods have been widely used in MI based BCIs to enhance performance by removing task irrelevant and redundant channels [24][25][26].…”
Section: Introductionmentioning
confidence: 99%
“…Emotions generate temporal patterns of brain activation [40], which can be identified and discriminated using the electroencephalogram (EEG) [41,42].…”
Section: Objective Measurement Of Emotional Response: Physiological Cmentioning
confidence: 99%