Name
Abstract | ||
|---|---|---|
This paper proposes a novel control algorithm for torque-controlled exoskeletons assisting cyclic movements. The control strategy is based on the injection of energy parcels into the human-robot system with a timing that minimizes perturbations, i.e., when the angular momentum is maximum. Electromyographic activity of main flexor-extensor knee muscles showed that the proposed controller mostly favors extensor muscles during extension, with a statistically significant reduction in muscular activity in the range of 10-20% in 60 out of 72 trials (i.e., 83%), while no effect related to swinging speed was recorded (speed variation was lower than 10% in 92% of the trials). In the remaining cases muscular activity increment, when statistically significant, was less than 10%. These results showed that the proposed algorithm reduced muscular effort during the most energetically demanding part of the movement (the extension of the knee against gravity) without perturbing the spatio-temporal characteristics of the task and making it particularly suitable for application in exoskeleton-assisted cyclic motions. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3389/fnbot.2019.00041 | FRONTIERS IN NEUROROBOTICS |
Keywords | Field | DocType |
assistive exoskeleton,adaptive controller,lower limb assistance,cyclic motions,series elastic actuator | Control algorithm,Angular momentum,Control theory,Computer science,Control theory,Limit cycle,Artificial intelligence,Exoskeleton,Machine learning | Journal |
Volume | ISSN | Citations |
13 | 1662-5218 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nevio Luigi Tagliamonte | 1 | 24 | 5.58 |
| Simona Valentini | 2 | 0 | 0.68 |
| Angelo Sudano | 3 | 0 | 0.34 |
| Iacopo Portaccio | 4 | 0 | 0.68 |
| Chiara De Leonardis | 5 | 0 | 0.34 |
| Domenico Formica | 6 | 88 | 26.60 |
| Dino Accoto | 7 | 100 | 23.61 |