Department of Electronics, Information and Bioengineering, Neuroengineering and Medical Robotics Laboratory, Politecnico di Milano, Milan, Italy.
Istituti Clinici Scientifici Maugeri, IRCSS, Lissone, Italy.
J Neuroeng Rehabil. 2020 Feb 27;17(1):35. doi: 10.1186/s12984-020-00662-w.
Muscle synergies analysis can provide a deep understanding of motor impairment after stroke and of changes after rehabilitation. In this study, the neuro-mechanical analysis of leg cycling was used to longitudinally investigate the motor recovery process coupled with cycling training augmented by Functional Electrical Stimulation (FES) in subacute stroke survivors.
Subjects with ischemic subacute stroke participated in a 3-week training of FES-cycling with visual biofeedback plus usual care. Participants were evaluated before and after the intervention through clinical scales, gait spatio-temporal parameters derived from an instrumented mat, and a voluntary pedaling test. Biomechanical metrics (work produced by the two legs, mechanical effectiveness and symmetry indexes) and bilateral electromyography from 9 leg muscles were acquired during the voluntary pedaling test. To extract muscles synergies, the Weighted Nonnegative Matrix Factorization algorithm was applied to the normalized EMG envelopes. Synergy complexity was measured by the number of synergies required to explain more than 90% of the total variance of the normalized EMG envelopes and variance accounted for by one synergy. Regardless the inter-subject differences in the number of extracted synergies, 4 synergies were extracted from each patient and the cosine-similarity between patients and healthy weight vectors was computed.
Nine patients (median age of 75 years and median time post-stroke of 2 weeks) were recruited. Significant improvements in terms of clinical scales, gait parameters and work produced by the affected leg were obtained after training. Synergy complexity well correlated to the level of motor impairment at baseline, but it did not change after training. We found a significant improvement in the similarity of the synergy responsible of the knee flexion during the pulling phase of the pedaling cycle, which was the mostly compromised at baseline. This improvement may indicate the re-learning of a more physiological motor strategy.
Our findings support the use of the neuro-mechanical analysis of cycling as a method to assess motor recovery after stroke, mainly in an early phase, when gait evaluation is not yet possible. The improvement in the modular coordination of pedaling correlated with the improvement in motor functions and walking ability achieved at the end of the intervention support the role of FES-cycling in enhancing motor re-learning after stroke but need to be confirmed in a controlled study with a larger sample size.
ClinicalTrial.gov, NCT02439515. Registered on May 8, 2015, .
肌肉协同作用分析可以深入了解中风后的运动障碍以及康复后的变化。在这项研究中，使用腿部循环的神经机械分析，纵向研究伴有功能性电刺激（FES）的循环训练的亚急性中风幸存者的运动恢复过程。
患有缺血性亚急性中风的受试者参加了为期 3 周的 FES 循环训练，具有视觉生物反馈和常规护理。参与者在干预前后通过临床量表，仪器化垫得出的步态时空参数以及自愿踩踏测试进行评估。在自愿踩踏测试过程中，获得了生物力学指标（两条腿产生的功，机械效率和对称性指数）和 9 条腿部肌肉的双侧肌电图。为了提取肌肉协同作用，应用加权非负矩阵分解算法对归一化肌电图包络进行处理。协同复杂性通过解释归一化肌电图包络的总方差超过 90％所需的协同数量以及一个协同解释的方差来衡量。无论从每个患者中提取的协同数量存在个体差异，仍从每个患者中提取 4 个协同，然后计算患者与健康体重向量之间的余弦相似性。
共招募了 9 名患者（中位年龄为 75 岁，中风后中位时间为 2 周）。训练后，在临床量表，步态参数和患侧产生的功方面均有明显改善。协同复杂性与基线时的运动障碍水平密切相关，但训练后并未改变。我们发现，在踩踏周期的拉动阶段负责膝关节弯曲的协同作用的相似性有了明显提高，而这在基线时是最受影响的。这种改善可能表明正在重新学习更生理的运动策略。
我们的研究结果支持使用神经机械分析来评估中风后的运动恢复，主要是在早期阶段，当步态评估还不可行时。踩踏模块化协调的改善与干预结束时获得的运动功能和行走能力的改善相关，支持 FES 循环在中风后增强运动再学习中的作用，但需要在更大样本量的对照研究中加以证实。
ClinicalTrial.gov，NCT02439515。于 2015 年 5 月 8 日注册。
