Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering
Md. Wasiur Rahman
Khulna University of Engineering & Technology
Computer Science & IT Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Left and Right Hand Movements EEG Signals Classification Using Wavelet Transform and Probabilistic Neural Network A. B. M. Aowlad Hossain; Md. Wasiur Rahman; Manjurul Ahsan Riheen
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 1: February 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (450.901 KB) | DOI: 10.11591/ijece.v5i1.pp92-101

Abstract

Electroencephalogram (EEG) signals have great importance in the area of brain-computer interface (BCI) which has diverse applications ranging from medicine to entertainment. BCI acquires brain signals, extracts informative features and generates control signals from the knowledge of these features for functioning of external devices. The objective of this work is twofold. Firstly, to extract suitable features related to hand movements and secondly, to discriminate the left and right hand movements signals finding effective classifier. This work is a continuation of our previous study where beta band was found compatible for hand movement analysis. The discrete wavelet transform (DWT) has been used to separate beta band of the EEG signal in order to extract features.  The performance of a probabilistic neural network (PNN) is investigated to find better classifier of left and right hand movements EEG signals and compared with classical back propagation based neural network. The obtained results shows that PNN (99.1%) has better classification rate than the BP (88.9%). The results of this study are expected to be helpful in brain computer interfacing for hand movements related bio-rehabilitation applications.
Co-Authors A. B. M. Aowlad Hossain Manjurul Ahsan Riheen