Recognition of combined arm motions using support vector machine
文献类型：会议论文
| 作者 | Yanjuan Geng; Dandan Tao; Liang Chen; Guanglin Li |
| 出版日期 | 2011 |
| 会议名称 | 2011 3rd International Asia Conference on Informatics in Control, Automation and Robotics, CAR 2011 |
| 会议地点 | Shenzhen, China |
| 英文摘要 | To investigate the classification performance of combined arm motions only using surface electromyography (EMG) signal, six different feature sets were adopted to match support vector machine (SVM) classifier respectively. Four unilateral transradial amputees participated in multi-channel surface EMG signal collection. The results show that the wavelet features outperforms others with average classification accuracy 98%±2% for intact arm and 89%±6% for amputated arm across all subjects. And the classification performance of intact arm motions was significantly better than that of amputated arm motions. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/3528]  |
| 专题 | 深圳先进技术研究院_医工所 |
| 作者单位 | 2011 |
| 推荐引用方式 GB/T 7714 | Yanjuan Geng,Dandan Tao,Liang Chen,et al. Recognition of combined arm motions using support vector machine[C]. 见:2011 3rd International Asia Conference on Informatics in Control, Automation and Robotics, CAR 2011. Shenzhen, China. |
入库方式： OAI收割
来源：深圳先进技术研究院
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