Construction of an electroencephalogram-based brain-computer interface using an artificial neural network
A brain-computer interface using an electroencephalogram as input into an artificial neural network is investigated as a potentially general control system applicable to all subjects and time frames. Using the intent and imagination of bending the left or right elbow, the left and right desired movements are successfully distinguished using event-related desynchronization resolved by fast Fourier transformation of the electroencephalogram and analysis of the power spectrum using the artificial neural network. The influence of age was identified and eliminated through the use of a frequency distribution in the alpha band, and the recognition rate was further improved by confirmation based on forced excitement of the beta band in the case of an error. The proposed system was effectively trained for general use by using the combined data of a cross-section of subjects.
electroencephalogram brain-computer interface artificial neural network event-related desynchronization fast fourier transform