TY  - JOUR
JF  - Biomedical Signal Processing and Control
VL  - 44
Y1  - 2018///
A1  - Abdalsalam M, E.
A1  - Yusoff, M.Z.
A1  - Mahmoud, D.
A1  - Malik, A.S.
A1  - Bahloul, M.R.
N1  - cited By 15
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046446150&doi=10.1016%2fj.bspc.2018.04.010&partnerID=40&md5=3a5adf1694a9333e1b9bf2d967e9af75
SP  - 181
PB  - Elsevier Ltd
AV  - none
SN  - 17468094
N2  - 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
KW  - Biomedical signal processing; Discrete wavelet transforms; Electroencephalography; Electrophysiology; Extraction; Feature extraction; Neural networks; Signal reconstruction; Wavelet decomposition
KW  -  Eeg datum; Empirical Mode Decomposition; Feature extraction methods; Motor cortex; Motor imagery; Spatial representations
KW  -  Brain computer interface
KW  -  accuracy; adult; Article; artificial neural network; brain computer interface; comparative study; controlled study; decomposition; discrete wavelet transform; electroencephalography; empirical mode decomposition; feature extraction; female; human; human experiment; imagery; male; motor cortex; movement (physiology); normal human; priority journal
TI  - Discrimination of four class simple limb motor imagery movements for brainâ??computer interface
ID  - scholars10197
EP  - 190
ER  -