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Detecting Different Emotional States of Human Brain Using Bio-potential Signals
P. Mukherjee,
Published in Springer Science and Business Media Deutschland GmbH
Volume: 147
Pages: 94 - 101
The essence of this paper is to design a mechanism for detecting emotional state of person using different bio-potential signals like electroencephalogram (EEG) signals of frontal lobe, pulse rate and SpO2. We record EEG signals of Fp1, Fp2, F3 and F4 electrodes, pulse rate and SpO2 of thirty subjects and extract twenty-two features from the recorded bio-potential signals. We design a k-nearest neighbor (KNN) classifier model for predicting the emotional state of a person. The designed KNN classifier model is trained with the extracted feature values of the thirty subjects. We again record the same bio-potential signals of ten new subjects and extract features. These extracted feature values are used for validating the performance of the trained KNN classifier model. The obtained overall efficiency of our designed emotion detection mechanism is 95.4%. © 2021, Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetLecture Notes in Networks and Systems
PublisherData powered by TypesetSpringer Science and Business Media Deutschland GmbH