Tagliamonte Nevio Luigi, Valentini Simona, Sudano Angelo, Portaccio Iacopo, De Leonardis Chiara, Formica Domenico, Accoto Dino
Biomedical Robotics and Biomicrosystems Research Unit, Department of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy.
NEXT: Neurophysiology and Neuroengineering of Human-Technology Interaction Research Unit, Department of Medicine, Università Campus Bio-Medico di Roma, Rome, Italy.
Front Neurorobot. 2019 Jun 19;13:41. doi: 10.3389/fnbot.2019.00041. eCollection 2019.
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.
本文提出了一种用于扭矩控制外骨骼辅助循环运动的新型控制算法。该控制策略基于在角动量最大时,以最小化扰动的时机向人机系统注入能量包。主要膝关节屈伸肌的肌电活动表明,所提出的控制器在伸展过程中大多有利于伸肌,在72次试验中的60次(即83%)中,肌肉活动在统计学上显著降低了10%-20%,而未记录到与摆动速度相关的影响(92%的试验中速度变化低于10%)。在其余情况下,当肌肉活动在统计学上显著增加时,增加幅度小于10%。这些结果表明,所提出的算法在运动中能量需求最大的部分(膝关节对抗重力伸展)减少了肌肉用力,同时不干扰任务的时空特征,使其特别适用于外骨骼辅助的循环运动。