Complexity reduction in control of human hand prosthesis for a limited set of gestures

This paper carried out a statistical analysis of human finger’s joint angles during hand specific daily activities, studying the correlations among the joints and applying a linear regression to express their correlations. The aim was to reduce the number of myoelectric sensors necessary in devices such as prosthesis, stands the current surgery difficulties and the problem of rejection, but without losing too many degrees of freedom. Measures were taken using our special hand movement acquisition system called HITEG data glove. As a preliminary work, we decided to limit the set of gestures performed to 9 of the most common movements of the human hand. The results shown that the number of sensors can be reduced from 14 to 7 with an acceptable error on the presumed value of each finger joint angle which can be as low as 10 degrees.