Name
Abstract | ||
|---|---|---|
In the recent years important steps forward have been made in the field of signal processing on muscle signals for hand prosthetics control. At the state of the art different algorithms and techniques allow a precise estimation of hand movements. However, they mostly work exclusively on the electrode space, not seeking for any information about the currents on the contracted muscles. In this study we propose a novel simplified method to estimate the muscles currents in the forearm, along with a first experimental application on two simple movements to assess its performance. We modeled the signal propagation from muscles to electrodes using a purely resistive electrical networks and afterwards apply the graph theory to assess the muscle currents. The proposed method considerably simplify the estimation of muscle's current, decreasing the problem complexity, and therefore potentially it can be a suitable approach for future prosthetics' control. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICORR.2019.8779462 | 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR) |
Keywords | Field | DocType |
Adult,Biomechanical Phenomena,Electromyography,Female,Forearm,Humans,Muscle Contraction,Muscle, Skeletal,Signal Processing, Computer-Assisted | Graph theory,Signal processing,Resistive touchscreen,Computer science,High density,Electromyography,Algorithm,Electric potential,Problem complexity,Radio propagation | Conference |
Volume | ISSN | ISBN |
2019 | 1945-7898 | 978-1-7281-2756-9 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| E. Piovanelli | 1 | 0 | 0.34 |
| D. Piovesan | 2 | 0 | 0.68 |
| Shouhei Shirafuji | 3 | 20 | 10.19 |
| J. Ota | 4 | 0 | 0.34 |