Non-Invasive Neural Controller

This project seeks to evaluate alternative means of controlling a prosthetic (in this case, a hand) using electroencephalographic control. The project consists of four methods; an unsure-feedback neural network, a neural network which lets the user know where it assumes the user wants to go, if unsure; a neutrally-iterated tree, which stores a preset list of locations that the user moves between based on how intently they focus on a task; a continuously-trained neural network, which tries to assume the users hand position and trains relative to that; and a direct neural network, as described above. The selected methods will be compared to determine training efficiency, accuracy, and response time relative to each other on a universal platform