前腕筋電位に基づく手指動作識別技術

抄録

The authors attempt to estimate finger gesture only by biological signals of forearm, because finger motion of human being affects not only finger muscles but forearm muscles. It is necessary but difficult to relate the forearm muscle activity to the finger gestures. This paper studies identification of finger movement based on myoelectric signals of the forearm skin surface. Genetic programming technique helps us to automatically generate the algorithm to estimate finger shapes by learning characteristics of muscle activation. We examined the influence of several genetic programming parameters such as Crossover rate, Mutation rate, Population size, and Target number of nodes to establish the optimum identification.