A REVIEW ON BRAIN COMPUTER INTERFACE OF MUSCLE MOVEMENT CLASSIFICATION FOR THE UPPER LIMBS
Rudra Kumar Mishra
M.E. Scholar, Department of Electrical Engineering, NITTTR, Chandigarh-160019 , IN
Dr. Lini Mathew
M.E. Scholar, Department of Electrical Engineering, NITTTR, Chandigarh-160019 , IN
Keywords: BCI, ANN, SVM, EMG, sEMG
Abstract
Brain Computer Interface (BCI) encompasses an amalgamation of the brain and computer for sharing an interface which could be used as a communication channel between them. Bio-signals are extracted with the help of electrodes by EMG from muscle, EEG from brain, EOG from eyes etc. but these signal are not much useful as they are very small in magnitude and contain noises. For
getting meaning information from the noisy and highly non-linear signals classification of the data has to be done. This paper studies the different artificial intelligent methods of BCI for the classification of signals for the upper limb. The methods included in this study are SVM, Random Tree, Neural Network, Time Domain Power- Spectral Analysis, Ultra Sound Images, Icasso clustering
and some hybrid classifiers.
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