Acquiring and processing of female EEG signals of various wrist movements for neuro prosthetic applications

Abstract

Human brain contain neurons which generate electrical signals, this can be recorded through electro encephalograph(EEG). Sensory motor cortices are responsible for motor activity i.e., various body movements, among which wrist movement reveals frequency change in Alpha & Beta bands of EEG signal. The aim of this approach is to calculate frequency changes responsible for various wrist movements such as flexion, extension, clockwise rotation and anticlockwise rotation, pronation and supination of female in both eyes open and eyes close conditions using FFT, wavelet transform classifier, where the largest set of EEG data is reduced to dimensions and the spectral frequencies for particular wrist movements are classified and the statistical analysis is done of various trials for both eyes open and eyes close conditions in both time domain and frequency domain and the mean and standard deviation of various trials will be compared for eyes open and eyes close condition in both time domain and frequency domain and these values can be implemented for neuro prosthetic applications.

Spectral Analysis and Validation of Parietal Signals for Different Arm Movements

“…As FFT is a time-shift invariant, it is considered one of the best transformations between the time and frequency domain [19]. In addition, one of the key benefits of FFT is that the dominant features can easily be spotted in the input EEG signal.…”