Sequential Multistate EMG Signal Processor

A feature of multifunction EMG control is that the operator is always aware when a decision is made. Thus, a sequential processor which observes the EMG signal for the length of time necessary to make a reliable decision would be a logical one. In this paper, two sequential processors are developed for the EMG signal. Exact expressions for the processor performance, error probability, and the average number of samples required to make a decision are derived. The two processors are modeled on a computer and verified experimentally. Both the theoretical and experimental results show that compared to an optimal Bayes receiver the sequential processor, for a given efror probability, requires, on the average, approximately half the number of samples. Finally, a proof is given for the optimum signal set and this set is used in the paper.