FROM MAN TO MACHINE: NEURAL CONTROL OF FINE HAND MOVEMENTS

Our hands are amazing tools we use constantly throughout the day without putting much thought into it. We use them to communicate with others, to move objects, and to receive information about the world around us. Movements we make on a daily basis, such as picking up a cup of coffee, involve an intricate coordination of muscles. The work in the first part of this thesis explores how our brain is organized to create these muscle patterns seemingly effortlessly. We studied muscle patterns of the hand while people performed a range of different movements, and also while the brain was stimulated externally. In the second part of the thesis, we explored if we can use these muscle patterns to restore hand movement for upper limb amputees. Dexterous hand prostheses, which allow the separate control of fingers, have been introduced into the healthcare market. With the advance of this new hardware, the control of the prostheses became the bottleneck. Through a computer game, we showed that we can use the muscles from the lower arm to control the different fingers of a prosthesis. In a very short setup phase, we trained the computer to recognize the muscle patterns associated with each finger movement, after which the participants were also able to control these fingers simultaneously. By studying the muscle patterns that people created while playing the game, we showed that people can learn this new task by reacting to the mistakes they make in the game.