Li Guanglin, Geng Yanjuan, Tao Dandan, Zhou Ping
Key Laboratory of Health Informatics of Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, CAS, Shenzhen, Guangdong 518055, China. gl.li@)siat.ac.cn
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:4243-6. doi: 10.1109/IEMBS.2011.6091053.
Electromyography (EMG) signals are commonly recorded using the Ag/AgCl gel electrodes in myoelectric prosthetic control. While a gelled electrode may provide high-quality EMG recordings, it is inconvenient in clinical application of a myoelectric prosthesis. A novel type of signal sensors-textile electrodes should be ideal in control of myoelectric prostheses. However, it is unknown whether the performance of textile electrodes is comparable to commonly used electrodes in classifying arm movements. In this study, the custom-made bipolar textile electrodes were fabricated using copper-based nickel-plated conductive fabric and were used to record EMG signals. The performance of EMG signals recorded with textile electrodes in identifying nine arm and hand movements were investigated. Our pilot results showed that the average classification accuracy across six able-bodied subjects was 94.05% when using textile electrodes and 94.26% when using conventional electrodes, with no significant difference between the two types of electrodes (p=0.81). The pilot results suggest that the textile electrodes could achieve similar performance in classifying arm movements in control of myoelectric prostheses as the gelled metal electrodes.
在肌电假肢控制中，通常使用银/氯化银凝胶电极来记录肌电图（EMG）信号。虽然凝胶电极可以提供高质量的肌电图记录，但在肌电假肢的临床应用中却不方便。一种新型的信号传感器——纺织电极，在肌电假肢控制中应该是理想的。然而，在对手臂运动进行分类时，纺织电极的性能是否与常用电极相当尚不清楚。在本研究中，使用铜基镀镍导电织物制作了定制的双极纺织电极，并用于记录肌电图信号。研究了用纺织电极记录的肌电图信号在识别九种手臂和手部运动方面的性能。我们的初步结果表明，六名健全受试者使用纺织电极时的平均分类准确率为94.05%，使用传统电极时为94.26%，两种电极之间无显著差异（p = 0.81）。初步结果表明，在肌电假肢控制中，纺织电极在对手臂运动进行分类时可以达到与凝胶金属电极相似的性能。
