De Marchis Cristiano, Santos Monteiro Thiago, Simon-Martinez Cristina, Conforto Silvia, Gharabaghi Alireza
Division of Functional and Restorative Neurosurgery, Department of Neurosurgery, Eberhard Karls University, Otfried-Mueller-Str.45, 72076, Tübingen, Germany.
Neuroprosthetics Research, Centre for Integrative Neuroscience, Eberhard Karls University, Tübingen, Germany.
J Neuroeng Rehabil. 2016 Mar 8;13:22. doi: 10.1186/s12984-016-0129-6.
Functional Electrical Stimulation (FES) is increasingly applied in neurorehabilitation. Particularly, the use of electrode arrays may allow for selective muscle recruitment. However, detecting the best electrode configuration constitutes still a challenge.
A multi-contact set-up with thirty electrodes was applied for combined FES and electromyography (EMG) recording of the forearm. A search procedure scanned all electrode configurations by applying single, sub-threshold stimulation pulses while recording M-waves of the extensor digitorum communis (EDC), extensor carpi radialis (ECR) and extensor carpi ulnaris (ECU) muscles. The electrode contacts with the best electrophysiological response were then selected for stimulation with FES bursts while capturing finger/wrist extension and radial/ulnar deviation with a kinematic glove.
The stimulation electrodes chosen on the basis of M-waves of the EDC/ECR/ECU muscles were able to effectively elicit the respective finger/wrist movements for the targeted extension and/or deviation with high specificity in two different hand postures.
A subset of functionally relevant stimulation electrodes could be selected fast, automatic and non-painful from a multi-contact array on the basis of muscle responses to subthreshold stimulation pulses. The selectivity of muscle recruitment predicted the kinematic pattern. This electrophysiologically driven approach would thus allow for an operator-independent positioning of the electrode array in neurorehabilitation.
功能性电刺激（FES）在神经康复中的应用日益广泛。特别是，电极阵列的使用可能允许选择性地募集肌肉。然而，确定最佳电极配置仍然是一项挑战。
采用一种具有30个电极的多触点设置，用于前臂的FES和肌电图（EMG）联合记录。一种搜索程序通过施加单个亚阈值刺激脉冲来扫描所有电极配置，同时记录指总伸肌（EDC）、桡侧腕伸肌（ECR）和尺侧腕伸肌（ECU）的M波。然后选择具有最佳电生理反应的电极触点，用FES脉冲进行刺激，同时用运动手套捕捉手指/手腕伸展和桡侧/尺侧偏斜。
基于EDC/ECR/ECU肌肉的M波选择的刺激电极能够在两种不同的手部姿势下，以高特异性有效地引发相应的手指/手腕运动，实现目标伸展和/或偏斜。
基于肌肉对亚阈值刺激脉冲的反应，可以从多触点阵列中快速、自动且无痛地选择功能相关的刺激电极子集。肌肉募集的选择性预测了运动模式。因此，这种电生理驱动的方法将允许在神经康复中实现电极阵列的独立于操作者的定位。
