Name
Abstract | ||
|---|---|---|
This work reports on the research and development of a lightweight neuroprosthesis that can control impaired motion using voluntary biological signals. The total weight of the developed neuroprosthesis is 900g, which is the weight of 40% of the defective limb. Further, it is lighter than commercially available models. For a transhumeral amputee who had targeted muscle reinnervation (TMR) surgery, we attempted pattern classification using an artificial neural network (ANN) of a surface electromyogram (s-EMG) extracted from an innervated muscle. The result shows that classification of only five motions was possible using an s-EMG extracted from four dry electrodes. However, seven motion classifications were possible using eight wet-gel electrodes. The transhumeral amputee who had TMR surgery could thus successfully perform pick-and-place tasks using the neuroprosthesis. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1080/01691864.2018.1507836 | ADVANCED ROBOTICS |
Keywords | Field | DocType |
Electromyography,above-elbow prosthesis,targeted muscle reinnervation,pattern recognition | Neuroprosthetics,Upper limb,Elbow,Electromyography,Control engineering,Engineering,Physical medicine and rehabilitation,Artificial neural network,Reinnervation | Journal |
Volume | Issue | ISSN |
32.0 | 16 | 0169-1864 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yosuke Ogiri | 1 | 0 | 1.01 |
| Yusuke Yamanoi | 2 | 1 | 2.10 |
| Wataru Nishino | 3 | 0 | 0.68 |
| Ryu Kato | 4 | 78 | 18.23 |
| Takehiko Takagi | 5 | 1 | 1.72 |
| Hiroshi Yokoi | 6 | 383 | 92.58 |