Barios Juan A, Ezquerro Santiago, Bertomeu-Motos Arturo, Catalan Jose M, Sanchez-Aparicio Jose M, Donis-Barber Luis, Fernandez Eduardo, Garcia-Aracil Nicolas
Biomedical Neuroengineering Research Group (nBio), Miguel Hernández, University, Avda. de la Universidad s/n, 03202 Elche, Spain.
Laboratory for New Technologies in Neurorehabilitation, Fundación Instituto San Jose, Pinar San Jose s/n, 28003 Madrid, Spain.
Int J Neural Syst. 2021 Dec;31(12):2150053. doi: 10.1142/S0129065721500532. Epub 2021 Oct 29.
Conventional rehabilitation strategies for stroke survivors become difficult when voluntary movements are severely disturbed. Combining passive limb mobilization, robotic devices and EEG-based brain-computer interfaces (BCI) systems might improve treatment and clinical follow-up of these patients, but detailed knowledge of neurophysiological mechanisms involved in functional recovery, which might help for tailoring stroke treatment strategies, is lacking. Movement-related EEG changes (EEG event-related desynchronization (ERD) in [Formula: see text] and [Formula: see text] bands, an indicator of motor cortex activation traditionally used for BCI systems), were evaluated in a group of 23 paralyzed chronic stroke patients in two unilateral motor tasks alternating paretic and healthy hands ((i) passive movement, using a hand exoskeleton, and (ii) voluntary movement), and compared to nine healthy subjects. In tasks using unaffected hand, we observed an increase of contralesional hemisphere activation for stroke patients group. Unexpectedly, when using paralyzed hand, motor cortex activation was reduced or absent in severely affected group of patients, while patients with moderate motor deficit showed an activation greater than control group. Cortical activation was reduced or absent in damaged hemisphere of all the patients in both tasks. Significant differences related to severity of motor deficit were found in the time course of [Formula: see text]-[Formula: see text] bands power ratio in EEG of contralesional hemisphere while moving affected hand. These findings suggest the presence of different compensation mechanisms in contralesional hemisphere of stroke patients related to the grade of motor disability, that might turn quantitative EEG during a movement task, obtained from a BCI system controlling a robotic device included in a rehabilitation task, into a valuable tool for monitoring clinical progression, evaluating recovery, and tailoring treatment of stroke patients.
当中风幸存者的自主运动严重受扰时，传统的康复策略就会变得困难。将被动肢体活动、机器人设备和基于脑电图的脑机接口（BCI）系统相结合，可能会改善这些患者的治疗和临床随访，但目前缺乏对功能恢复所涉及的神经生理机制的详细了解，而这可能有助于制定中风治疗策略。在一组23名瘫痪的慢性中风患者中，针对两项单侧运动任务（交替使用患侧手和健侧手）（(i) 使用手部外骨骼进行被动运动，以及 (ii) 自主运动），评估了与运动相关的脑电图变化（脑电图事件相关去同步化（ERD）在[公式：见正文]和[公式：见正文]频段，这是传统上用于BCI系统的运动皮层激活指标），并与9名健康受试者进行了比较。在使用未受影响手的任务中，我们观察到中风患者组对侧半球激活增加。出乎意料的是，当使用瘫痪手时，严重受影响的患者组运动皮层激活减少或缺失，而中度运动功能缺损的患者表现出比对照组更大的激活。在两项任务中，所有患者受损半球的皮层激活均减少或缺失。在移动患侧手时，对侧半球脑电图中[公式：见正文]-[公式：见正文]频段功率比的时间进程中，发现了与运动功能缺损严重程度相关的显著差异。这些发现表明，中风患者对侧半球存在与运动残疾程度相关的不同补偿机制，这可能会使从控制康复任务中包含的机器人设备的BCI系统获得的运动任务期间的定量脑电图，成为监测临床进展、评估恢复情况和制定中风患者治疗方案的有价值工具。
