표면 근전도를 기반 최대 우도 추정법을 이용한 9가지 방향 분류

초록

In this paper, 9 directions which can be used as input data were classified using Maximum Likelihood Estimation (MLE) based on surface electromyography (sEMG) of both forearms. 5 subjects who participated in the experiment and estimated movements for the subjects are 3 kinds in each forearm. And then the features of obtained electromyography signal are combined to classify 9 directions. According to the research results, we confirmed that 9 directions average classification accuracy by each feature is 95.8%.