Ambrosini Emilia, De Marchis Cristiano, Pedrocchi Alessandra, Ferrigno Giancarlo, Monticone Marco, Schmid Maurizio, D'Alessio Tommaso, Conforto Silvia, Ferrante Simona
Neuroengineering and Medical Robotics Laboratory, Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy.
Physical Medicine and Rehabilitation Unit, Scientific Institute of Lissone, Salvatore Maugeri Foundation, Institute of Care and Research (IRCCS), Lissone, Italy.
Ann Biomed Eng. 2016 Nov;44(11):3238-3251. doi: 10.1007/s10439-016-1660-0. Epub 2016 Jun 1.
Cycling training is strongly applied in post-stroke rehabilitation, but how its modular control is altered soon after stroke has been not analyzed yet. EMG signals from 9 leg muscles and pedal forces were measured bilaterally during recumbent pedaling in 16 post-acute stroke patients and 12 age-matched healthy controls. Patients were asked to walk over a GaitRite mat and standard gait parameters were computed. Four muscle synergies were extracted through nonnegative matrix factorization in healthy subjects and patients unaffected legs. Two to four synergies were identified in the affected sides and the number of synergies significantly correlated with the Motricity Index (Spearman's coefficient = 0.521). The reduced coordination complexity resulted in a reduced biomechanical performance, with the two-module sub-group showing the lowest work production and mechanical effectiveness in the affected side. These patients also exhibited locomotor impairments (reduced gait speed, asymmetrical stance time, prolonged double support time). Significant correlations were found between cycling-based metrics and gait parameters, suggesting that neuro-mechanical quantities of pedaling can inform on walking dysfunctions. Our findings support the use of pedaling as a rehabilitation method and an assessment tool after stroke, mainly in the early phase, when patients can be unable to perform a safe and active gait training.
骑行训练在中风后康复中得到广泛应用,但中风后不久其模块化控制如何改变尚未得到分析。在16名急性中风后患者和12名年龄匹配的健康对照者进行卧式蹬车时,双侧测量了9条腿部肌肉的肌电图信号和踏板力。要求患者在GaitRite垫子上行走,并计算标准步态参数。通过非负矩阵分解在健康受试者和患者未受影响的腿部提取了四种肌肉协同作用。在受影响侧识别出两到四种协同作用,协同作用的数量与运动指数显著相关(斯皮尔曼系数=0.521)。协调复杂性的降低导致生物力学性能下降,双模块亚组在受影响侧表现出最低的工作产出和机械效率。这些患者还表现出运动障碍(步态速度降低、站立时间不对称、双支撑时间延长)。发现基于骑行的指标与步态参数之间存在显著相关性,这表明蹬车的神经力学量可以反映行走功能障碍。我们的研究结果支持将蹬车作为中风后的康复方法和评估工具,主要是在早期阶段,此时患者可能无法进行安全有效的步态训练。