Signal processing for the multistate myoelectric channel

In the multistate myoelectric channel, a single myoelectric signal source is used to control a multifunction powered prosthesis. The selection of a prosthesis function requires a receiver to process the myoelectric signal, contaminated with noise, and to decide on the basis of the received signals which function is desired. Thus the channnel cleady presents a problem of choice of receiver and of decision strategy. Previous sotutions to this problem have been basically empirical. In this paper we seek the optimum receiver where optimum is in the minimum probability of error sense. First a model is developed for the bipolar myoelectric signal to provide information about the relevant signal parameters and statistics. Using this information the Bayes minimum probability of error receiver is derived for an orbitrary signal parameter set. The optimum signal parameter set is then found for the Bayes receiver, and the receiver performance calculated. The receiver performance is measured and compared with the calculated performance. A significant performance improvement is seen in the optimum receiver over a more conventional receiver.