A Novel Time-Domain Descriptor for Improved Prediction of Upper Limb Movement Intent in EMG-PR System
文献类型：会议论文
| 作者 | Pang Feng; Guanglin Li; Lin Wang; Oluwarotimi Williams Samuel; Mojisola Grace Asogbon; Yanjuan Geng; Shixiong Chen; Lin Chuang |
| 出版日期 | 2018 |
| 会议日期 | 2018 |
| 会议地点 | Honolulu, Hawaii, USA |
| 英文摘要 | Electromyogram pattern recognition (EMG-PR) based control is a potential method capable of providing intuitively dexterous control functions in upper limb prostheses. Meanwhile, the feature extraction method adopted in EMG-PR based control is considered as an important factor that influences the performance of the prostheses. By exploiting the limitations of the existing feature extraction methods, this study proposed a new feature extraction method to effectively characterize EMG signal patterns associated with different limb movement intent. The performance of the proposed 2- dimensional novel time-domain feature set (NTDFS) was investigated using classification accuracy and feature space separability metrics across five subjects’ EMG recordings, and compared with four different existing methods. In comparison to four other previously proposed feature extraction methods, the NTDFS achieved significantly better performance with increment in accuracy in the range of 5.20% ~ 8.40% at p<0.05. Additionally, by applying principal component analysis (PCA) technique, the PCA feature space for NTDFS show obvious class separability in comparison to the other existing feature extraction methods. Thus, the proposed NTDFS may facilitate the development of accurate and robust clinically viable EMG-PR based prostheses. |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/14456]  |
| 专题 | 深圳先进技术研究院_医工所 |
| 推荐引用方式 GB/T 7714 | Pang Feng,Guanglin Li,Lin Wang,et al. A Novel Time-Domain Descriptor for Improved Prediction of Upper Limb Movement Intent in EMG-PR System[C]. 见:. Honolulu, Hawaii, USA. 2018. |
入库方式： OAI收割
来源：深圳先进技术研究院
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