Sale Patrizio, Infarinato Francesco, Del Percio Claudio, Lizio Roberta, Babiloni Claudio, Foti Calogero, Franceschini Marco
aDepartment of Neurorehabilitation, IRCCS San Raffaele Pisana bDepartment of Physiology and Pharmacology, University of Rome Sapienza cPhysical Rehabilitation Medicine Chair, Clinical Sciences and Translational Medicine DPT, Tor Vergata University, Rome, Italy.
Int J Rehabil Res. 2015 Dec;38(4):294-305. doi: 10.1097/MRR.0000000000000125.
Stroke is the leading cause of permanent disability in developed countries; its effects may include sensory, motor, and cognitive impairment as well as a reduced ability to perform self-care and participate in social and community activities. A number of studies have shown that the use of robotic systems in upper limb motor rehabilitation programs provides safe and intensive treatment to patients with motor impairments because of a neurological injury. Furthermore, robot-aided therapy was shown to be well accepted and tolerated by all patients; however, it is not known whether a specific robot-aided rehabilitation can induce beneficial cortical plasticity in stroke patients. Here, we present a procedure to study neural underpinning of robot-aided upper limb rehabilitation in stroke patients. Neurophysiological recordings use the following: (a) 10-20 system electroencephalographic (EEG) electrode montage; (b) bipolar vertical and horizontal electrooculographies; and (c) bipolar electromyography from the operating upper limb. Behavior monitoring includes the following: (a) clinical data and (b) kinematic and dynamic of the operant upper limb movements. Experimental conditions include the following: (a) resting state eyes closed and eyes open, and (b) robotic rehabilitation task (maximum 80 s each block to reach 4-min EEG data; interblock pause of 1 min). The data collection is performed before and after a program of 30 daily rehabilitation sessions. EEG markers include the following: (a) EEG power density in the eyes-closed condition; (b) reactivity of EEG power density to eyes opening; and (c) reactivity of EEG power density to robotic rehabilitation task. The above procedure was tested on a subacute patient (29 poststroke days) and on a chronic patient (21 poststroke months). After the rehabilitation program, we observed (a) improved clinical condition; (b) improved performance during the robotic task; (c) reduced delta rhythms (1-4 Hz) and increased alpha rhythms (8-12 Hz) during the resting state eyes-closed condition; (d) increased alpha desynchronization to eyes opening; and (e) decreased alpha desynchronization during the robotic rehabilitation task. We conclude that the present procedure is suitable for evaluation of the neural underpinning of robot-aided upper limb rehabilitation.
中风是发达国家永久性残疾的主要原因；其影响可能包括感觉、运动和认知障碍，以及自我护理能力下降和参与社会及社区活动的能力降低。多项研究表明，在因神经损伤导致运动障碍的患者的上肢运动康复计划中使用机器人系统可提供安全且强化的治疗。此外，机器人辅助治疗被证明为所有患者所接受和耐受；然而，尚不清楚特定的机器人辅助康复是否能在中风患者中诱导有益的皮质可塑性。在此，我们提出一种研究中风患者机器人辅助上肢康复的神经基础的方法。神经生理学记录采用以下方式：(a) 10-20系统脑电图(EEG)电极蒙片；(b) 双极垂直和水平眼电图；以及(c) 操作上肢的双极肌电图。行为监测包括：(a) 临床数据和(b) 操作上肢运动的运动学和动力学。实验条件包括：(a) 闭眼和睁眼静息状态，以及(b) 机器人康复任务(每个区块最长80秒以获取4分钟的EEG数据；区块间停顿1分钟)。数据收集在每日30次康复疗程的计划前后进行。EEG指标包括：(a) 闭眼状态下的EEG功率密度；(b) EEG功率密度对睁眼的反应性；以及(c) EEG功率密度对机器人康复任务的反应性。上述方法在一名亚急性患者(中风后29天)和一名慢性患者(中风后21个月)身上进行了测试。康复计划后，我们观察到：(a) 临床状况改善；(b) 机器人任务期间表现改善；(c) 闭眼静息状态下δ波(1-4Hz)减少，α波(8-12Hz)增加；(d) 睁眼时α去同步化增加；以及(e) 机器人康复任务期间α去同步化减少。我们得出结论，本方法适用于评估机器人辅助上肢康复的神经基础。
