Name
Abstract | ||
|---|---|---|
This paper presents a control method of grasping force of prosthetic hand. Firstly, the correlated features of surface electromyogram (sEMG) signal that collected by MYO are calculated, and then principal component analysis (PCA) dimension reduction is processed. According to pattern classification model and sEMG-force regression model which based on support vector machine (SVM) to gain the force prediction value. In this approach, force is divided into different grades. The predicted force value is used as the given signal, and grasping force of prosthetic hand is controlled by a fuzzy controller, and combined with vibration feedback device to feedback grasping force value to patient's arm. The test results show that the method of prosthetic hand grasping force control is effective. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-981-10-6370-1_22 | Communications in Computer and Information Science |
Keywords | DocType | Volume |
MYO,PCA,sEMG-force,SVM,Fuzzy controller,Vibration feedback device | Conference | 761 |
ISSN | Citations | PageRank |
1865-0929 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jian Ren | 1 | 0 | 0.34 |
| chuanjiang li | 2 | 1 | 3.09 |
| huaiqi huang | 3 | 2 | 2.20 |
| Peng Wang | 4 | 385 | 106.03 |
| Yanfei Zhu | 5 | 3 | 1.10 |
| Bin Wang | 6 | 1788 | 246.68 |
| Kang An | 7 | 248 | 34.27 |