Neuroprosthetics Group, Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.
International Max Planck Research School for Cognitive and Systems Neuroscience, Tübingen, Germany.
J Neural Eng. 2021 May 18;18(4). doi: 10.1088/1741-2552/abe244.
. Stroke affects the expression of muscle synergies underlying motor control, most notably in patients with poorer motor function. The majority of studies on muscle synergies have conventionally approached this analysis by assuming alterations in the inner structures of synergies after stroke. Although different synergy-based features based on this assumption have to some extent described pathological mechanisms in post-stroke neuromuscular control, a biomarker that reliably reflects motor function and recovery is still missing.. Based on the theory of muscle synergies, we alternatively hypothesize that functional synergy structures are physically preserved and measure the temporal correlation between the recruitment profiles of healthy modules by paretic and healthy muscles, a feature hereafter reported as the FSRI. We measured clinical scores and extracted the muscle synergies of both ULs of 18 chronic stroke survivors from the electromyographic activity of 8 muscles during bilateral movements before and after 4 weeks of non-invasive BMI controlled robot therapy and physiotherapy. We computed the FSRI as well as features quantifying inter-limb structural differences and evaluated the correlation of these synergy-based measures with clinical scores.. Correlation analysis revealed weak relationships between conventional features describing inter-limb synergy structural differences and motor function. In contrast, FSRI values during specific or combined movement data significantly correlated with UL motor function and recovery scores. Additionally, we observed that BMI-based training with contingent positive proprioceptive feedback led to improved FSRI values during the specific trained finger extension movement.. We demonstrated that FSRI can be used as a reliable physiological biomarker of motor function and recovery in stroke, which can be targeted via BMI-based proprioceptive therapies and adjuvant physiotherapy to boost effective rehabilitation.
中风会影响运动控制的肌肉协同作用的表达，在运动功能较差的患者中最为明显。大多数关于肌肉协同作用的研究都通过假设中风后协同作用的内在结构发生变化来进行这种分析。尽管基于这一假设的不同协同作用特征在某种程度上描述了中风后神经肌肉控制的病理机制，但仍然缺乏一种可靠反映运动功能和恢复的生物标志物。基于肌肉协同作用理论，我们假设功能协同结构在物理上是被保留的，并测量了患侧和健康肌肉募集模式之间的时间相关性，这一特征被称为 FSRI。我们测量了临床评分，并从 18 名慢性中风幸存者的 8 块肌肉的肌电图活动中提取了双侧运动前和 4 周非侵入性 BMI 控制机器人治疗和物理治疗后的双侧上肢肌肉协同作用。我们计算了 FSRI 以及量化肢体间结构差异的特征，并评估了这些基于协同作用的测量与临床评分的相关性。相关分析显示，描述肢体间协同作用结构差异的常规特征与运动功能之间存在弱相关性。相比之下，特定或组合运动数据期间的 FSRI 值与上肢运动功能和恢复评分显著相关。此外，我们观察到，基于 BMI 的、带有条件正本体感觉反馈的训练会导致特定训练的手指伸展运动期间 FSRI 值的提高。我们证明了 FSRI 可以作为中风运动功能和恢复的可靠生理生物标志物，通过基于 BMI 的本体感觉治疗和辅助物理治疗来提高其效果。
