Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm
We present a preliminary study on the use of a Brain Computer Interface(BCI) device to investigate the feasibility of recognizing patterns of natural language morphemes from EEG signals. This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artif...
Main Authors: | Sulaiman, Suriani, Ahmed Yahya, Saba, Mohd Shukor, Nur Sakinah, Ismail , Amelia Ritahani, Zaahirah, Qazi, Yaacob, Hamwira, Abdul Rahman, Abdul Wahab, Dzulkifli, Mariam Adawiah |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2015
|
Subjects: | |
Online Access: | http://irep.iium.edu.my/40882/ http://irep.iium.edu.my/40882/1/Clustering_Natural_Language_Morphemes_from_EEG_Signals_using_ABC.pdf |
Similar Items
-
Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm
by: Sulaiman, Suriani, et al.
Published: (2015) -
Artificial Bee Colony Algorithm for Pairwise Test Generation
by: Alazzawi, Ammar K., et al.
Published: (2017) -
EEG emotion recognition based on the dimensional models of emotions
by: Othman, Marini, et al.
Published: (2013) -
Emotion detection using physiological signals EEG & ECG
by: AlzeerAlhouseini, Amjad M.R., et al.
Published: (2016) -
Revolving traditional EEG device into mobile architecture
by: Muhd Adnan, Hafizuddin, et al.
Published: (2016)