Villani Margherita, Avaltroni Priscilla, Scordo Giulia, Rubeca Damiana, Kreynin Peter, Bereziy Ekaterina, Berger Denise, Cappellini Germana, Sylos-Labini Francesca, Lacquaniti Francesco, Ivanenko Yury
Laboratory of Neuromotor Physiology, Istituto di Ricovero e Cura a Carattere Scientifico Fondazione Santa Lucia, Rome, Italy.
Department of Systems Medicine and Center of Space Biomedicine, University of Rome Tor Vergata, Rome, Italy.
Front Neurosci. 2024 Oct 24;18:1461323. doi: 10.3389/fnins.2024.1461323. eCollection 2024.
While exoskeleton technology is becoming more and more common for gait rehabilitation in children with neurological disorders, evaluation of gait performance still faces challenges and concerns. The reasoning behind evaluating the spinal locomotor output is that, while exoskeleton's guidance forces create the desired walking kinematics, they also affect sensorimotor interactions, which may lead to an abnormal spatiotemporal integration of activity in particular spinal segments and the risk of abnormalities in gait recovery. Therefore, traditional indicators based on kinematic or kinetic characteristics for optimizing exoskeleton controllers for gait rehabilitation may be supplemented by performance measures associated with the neural control mechanisms. The purpose of this study on a sample of children was to determine the basic features of lower limb muscle activity and to implement a method for assessing the neuromechanics of spinal locomotor output during exoskeleton-assisted gait. To this end, we assessed the effects of a robotic exoskeleton (ExoAtlet Bambini) on gait performance, by recording electromyographic activity of leg muscles and analyzing the corresponding spinal motor pool output. A slower walking setting (about 0.2 m/s) was chosen on the exoskeleton. The results showed that, even with slower walking, the level of muscle activation was roughly comparable during exoskeleton-assisted gait and normal walking. This suggests that, despite full assistance for leg movements, the child's locomotor controllers can interpret step-related afferent information promoting essential activity in leg muscles. This is most likely explained by the active nature of stepping in the exoskeleton (the child was not fully relaxed, experienced full foot loading and needed to maintain the upper trunk posture). In terms of the general muscle activity patterns, we identified notable variations for the proximal leg muscles, coactivation of the lumbar and sacral motor pools, and weak propulsion from the distal extensors at push-off. These changes led to the lack of characteristic lumbosacral oscillations of the center of motoneuron activity, normally associated with the pendulum mechanism of bipedal walking. This work shows promise as a useful technique for analyzing exoskeleton performance to help children develop their natural gait pattern and to guide system optimization in the future for inclusion into clinical care.
虽然外骨骼技术在神经疾病患儿的步态康复中越来越普遍,但步态性能评估仍面临挑战和问题。评估脊髓运动输出的背后原因是,虽然外骨骼的引导力创造了所需的步行运动学,但它们也会影响感觉运动相互作用,这可能导致特定脊髓节段活动的时空整合异常以及步态恢复异常的风险。因此,基于运动学或动力学特征来优化步态康复外骨骼控制器的传统指标,可能需要辅以与神经控制机制相关的性能指标。本研究以儿童为样本,目的是确定下肢肌肉活动的基本特征,并实施一种评估外骨骼辅助步态期间脊髓运动输出神经力学的方法。为此,我们通过记录腿部肌肉的肌电图活动并分析相应的脊髓运动池输出,评估了一款机器人外骨骼(ExoAtlet Bambini)对步态性能的影响。在外骨骼上选择了较慢的步行速度(约0.2米/秒)。结果表明,即使步行速度较慢,外骨骼辅助步态和正常步行期间的肌肉激活水平大致相当。这表明,尽管腿部运动得到了充分辅助,但儿童的运动控制器能够解读与步幅相关的传入信息,促进腿部肌肉的基本活动。这很可能是由于在外骨骼中步行的主动性质(儿童并未完全放松,经历了全足负重,且需要保持上半身姿势)。就一般肌肉活动模式而言,我们发现近端腿部肌肉有显著变化、腰骶运动池共同激活,以及蹬离时远端伸肌的推进力较弱。这些变化导致运动神经元活动中心缺乏典型的腰骶部振荡,而这种振荡通常与双足步行的摆动机制相关。这项工作有望成为一种有用的技术,用于分析外骨骼性能,帮助儿童形成自然步态模式,并为未来纳入临床护理的系统优化提供指导。