Multichannel EEG Signal Acquisition and Multiwavelet Based Emotion Recognition using BCI

JOGESH, MOTWANI and SHANTALA, C P (2015) Multichannel EEG Signal Acquisition and Multiwavelet Based Emotion Recognition using BCI. In: Third International Conference on Advances in Information Processing and Communication Technology - IPCT 2015, 10-11 December, 2015, Rome, Italy.

[img]
Preview
Text
20151223_112227.pdf - Published Version

Download (542kB) | Preview
Official URL: https://www.seekdl.org/conferences/paper/details/7...

Abstract

This paper aims to recognize emotion through EEG. The EEG signals are acquired from the wireless wearable 8- channel Enobio device for the emotions such as smile and anger. The acquired EEG signals are processed to recognize selected emotions. The features like mean, standard deviation, median, entropy, variance, minimum, maximum and skewness have been extracted from sub-signals obtained by multiwavelet decomposition of EEG signals. These features are used as an input to support vector machine (SVM) for classification of human emotions. The proposed method has provided classification accuracy of 87.5% using SVM.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: EEG, Multi-wavelet, SVM, BCI
Depositing User: Mr. John Steve
Date Deposited: 04 Apr 2019 12:00
Last Modified: 04 Apr 2019 12:00
URI: http://publications.theired.org/id/eprint/1165

Actions (login required)

View Item View Item