Logo

Discrimination of four class simple limb motor imagery movements for brain�computer interface

Abdalsalam M, E. and Yusoff, M.Z. and Mahmoud, D. and Malik, A.S. and Bahloul, M.R. (2018) Discrimination of four class simple limb motor imagery movements for brain�computer interface. Biomedical Signal Processing and Control, 44 . pp. 181-190.

Full text not available from this repository.

Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

The discrimination of four simple limb motor imagery movements for brain-computer interface (BCI) applications is still challenging. This is because most of the movement imaginations have close spatial representations on the motor cortex area. Nevertheless, due to its potential applications in significant areas including BCI, solutions need to be formulated to overcome the task discrimination issues faced when a motor imagery movement approach is utilized. Feature extraction is one of the most important steps in any BCI system; as such, enhancement to the existing methods has been incorporated in this work. For this, we propose four-class movement imaginations of the right hand, left hand, right foot, and left foot, and develop feature extraction methods utilizing discrete wavelet transform (DWT) and empirical mode decomposition (EMD); in both methods, artificial neural network (ANN) was used as a classifier. Based on the processed electroencephalography (EEG) data recorded from eleven subjects, it can be seen that EMD features outperform DWT features; the average accuracy achieved by the EMD features is 90.02, and 84.77 using the DWT features. EMD even performs better than DWT in discriminating the most challenging tasks involving the right foot and left foot imageries, whose EEG data were derived from the same Cz node of the motor cortex. © 2018 Elsevier Ltd

Item Type:Article
Impact Factor:cited By 0
Uncontrolled Keywords:Biomedical signal processing; Discrete wavelet transforms; Electroencephalography; Electrophysiology; Extraction; Feature extraction; Interfaces (computer); Neural networks; Signal reconstruction; Wavelet decomposition, Eeg datum; Empirical Mode Decomposition; Feature extraction methods; Motor cortex; Motor imagery; Spatial representations, Brain computer interface
Departments / MOR / COE:Research Institutes > Institute for Health Analytics
ID Code:21470
Deposited By: Ahmad Suhairi
Deposited On:25 Sep 2018 06:32
Last Modified:16 Nov 2018 08:24

Repository Staff Only: item control page