Favieiro Gabriela W, Balbinot Alexandre
Department of Electrical Engineering, Laboratory IEE – PPGEE, Federal University of Rio Grande do Sul, Av Osvaldo Aranha, 103 – 206, 90035190 PortoAlegre, RS, Brazil.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:7888-91. doi: 10.1109/IEMBS.2011.6091945.
The myoelectric signal is a sign of control of the human body that contains the information of the user's intent to contract a muscle and, therefore, make a move. Studies shows that the Amputees are able to generate standardized myoelectric signals repeatedly before of the intention to perform a certain movement. This paper presents a study that investigates the use of forearm surface electromyography (sEMG) signals for classification of five distinguish movements of the arm using just three pairs of surface electrodes located in strategic places. The classification is done by an adaptive neuro-fuzzy inference system (ANFIS) to process signal features to recognize performed movements. The average accuracy reached for the classification of five motion classes was 86-98% for three subjects.
肌电信号是人体控制的一种信号，它包含了使用者收缩肌肉从而做出动作的意图信息。研究表明，截肢者在有执行特定动作的意图之前，能够反复产生标准化的肌电信号。本文提出了一项研究，该研究调查了仅使用位于特定位置的三对表面电极，利用前臂表面肌电图（sEMG）信号对手臂的五种不同动作进行分类。分类是通过自适应神经模糊推理系统（ANFIS）来处理信号特征以识别所执行的动作。对于三名受试者，五个动作类别的分类平均准确率达到了86%-98%。
