The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Enhanced BiLSTM Model for EEG Emotional Data Analysis
|
|
Author(s): Shanthalakshmi Revathy J. (Velammal College of Engineering and Technology, India), Uma Maheswari N. (PSNA College of Engineering and Technology, India)and Sasikala S. (Velammal College of Engineering and Technology, India)
Copyright: 2023
Pages: 13
Source title:
Principles and Applications of Socio-Cognitive and Affective Computing
Source Author(s)/Editor(s): S. Geetha (Vellore Institute of Technology, Chennai, India), Karthika Renuka (PSG College of Technology, India), Asnath Victy Phamila (Vellore Institute of Technology, Chennai, India)and Karthikeyan N. (Syed Ammal Engineering College, India)
DOI: 10.4018/978-1-6684-3843-5.ch005
Purchase
|
Abstract
Emotion recognition based on biological signals from the brain necessitates sophisticated signal processing and feature extraction techniques. The major purpose of this research is to use the enhanced BiLSTM (E-BiLSTM) approach to improve the effectiveness of emotion identification utilizing brain signals. The approach detects brain activity that has distinct characteristics that vary from person to person. This experiment uses an emotional EEG dataset that is publicly available on Kaggle. The data was collected using an EEG headband with four sensors (AF7, AF8, TP9, TP10), and three possible states were identified, including neutral, positive, and negative, based on cognitive behavioral studies. A big dataset is generated using statistical brainwave extraction of alpha, beta, theta, delta, and gamma, which is then scaled down to smaller datasets using the PCA feature selection technique. Overall accuracy was around 98.12%, which is higher than the present state of the art.
Related Content
|
Hemalatha J. J., Bala Subramanian Chokkalingam, Vivek V., Sekar Mohan.
© 2023.
14 pages.
|
|
R. Muthuselvi, G. Nirmala.
© 2023.
12 pages.
|
|
Jerritta Selvaraj, Arun Sahayadhas.
© 2023.
16 pages.
|
|
Vidhya R., Sandhia G. K., Jansi K. R., Nagadevi S., Jeya R..
© 2023.
8 pages.
|
|
Shanthalakshmi Revathy J., Uma Maheswari N., Sasikala S..
© 2023.
13 pages.
|
|
Uma N. Dulhare, Shaik Rasool.
© 2023.
29 pages.
|
|
R. Nareshkumar, G. Suseela, K. Nimala, G. Niranjana.
© 2023.
22 pages.
|
|
|