Deception detection of EEG-P300 component classified by SVM method

A Turnip, MF Amri, H Fakrurroja, AI Simbolon… - Proceedings of the 6th …, 2017 - dl.acm.org
Proceedings of the 6th international conference on software and computer …, 2017dl.acm.org
This study will explore the differences in brain wave activity while a person is either telling
the truth or being deceptive. A subject brain wave activities based EEG-P300 component will
be monitored while they first respond truthfully and then falsely to questions in regards to a
mock theft scenario. Eleven males whose age are around 24±3 years old were subject to the
experiment. For extraction and classification, an independent component analysis and
support vector machine methods were adopted. The gathered data were then divided into …
This study will explore the differences in brain wave activity while a person is either telling the truth or being deceptive. A subject brain wave activities based EEG-P300 component will be monitored while they first respond truthfully and then falsely to questions in regards to a mock theft scenario. Eleven males whose age are around 24 ± 3 years old were subject to the experiment. For extraction and classification, an independent component analysis and support vector machine methods were adopted. The gathered data were then divided into training and test data to produce several models. The results show that a larger spike in the P300 component when the subject was instructed to conceal which watch they had chosen. The findings of these experiments have been promising in testing the validity of using an EEG in deception detection.
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