Decoding intra-limb and inter-limb kinematics during treadmill walking from scalp electroencephalographic (EEG) signals.
Decoding intra-limb and inter-limb kinematics during treadmill walking from scalp electroencephalographic (EEG) signals.
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DOI：
10.1109/tnsre.2012.2188304
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发表时间：
2012-03
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影响因子：
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通讯作者：
Contreras-Vidal JL
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文献类型：
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作者：
Presacco A;Forrester LW;Contreras-Vidal JL
脑机接口（BMI）的研究主要集中在上肢。虽然步态功能的恢复一直是康复研究的长期焦点，但令人惊讶的是，很少有人对参与双足运动指导和控制的皮层神经网络进行解码。一个值得注意的例外是杜克大学的Nicolelis小组的工作，他们从恒河猴初级感觉运动区神经元的长期记录中解码了步态运动学。最近，我们表明，人类在跑步机行走期间脚踝、膝关节和髋关节的步态运动学可以从脑电波（EEG）中推断出来，其解码准确度与使用皮质内记录的解码准确度相当。在这里，我们表明，从人类跑步机行走的肢体内和肢体间运动学可以实现高精度，从少至12个电极，使用头皮脑电图。有趣的是，前向和后向预测从EEG信号滞后或领先的运动学，分别表现出不同的空间分布，这表明不同的神经网络的前馈和反馈控制的步态。有趣的是，受试者和解码模式的平均解码准确度为~0.68±0.08，支持基于EEG的BMI系统用于恢复瘫痪患者行走的可行性。
Brain–machine interface (BMI) research has largely been focused on the upper limb. Although restoration of gait function has been a long-standing focus of rehabilitation research, surprisingly very little has been done to decode the cortical neural networks involved in the guidance and control of bipedal locomotion. A notable exception is the work by Nicolelis’ group at Duke University that decoded gait kinematics from chronic recordings from ensembles of neurons in primary sensorimotor areas in rhesus monkeys. Recently, we showed that gait kinematics from the ankle, knee, and hip joints during human treadmill walking can be inferred from the electroencephalogram (EEG) with decoding accuracies comparable to those using intracortical recordings. Here we show that both intra- and inter-limb kinematics from human treadmill walking can be achieved with high accuracy from as few as 12 electrodes using scalp EEG. Interestingly, forward and backward predictors from EEG signals lagging or leading the kinematics, respectively, showed different spatial distributions suggesting distinct neural networks for feedforward and feedback control of gait. Of interest is that average decoding accuracy across subjects and decoding modes was ~0.68±0.08, supporting the feasibility of EEG-based BMI systems for restoration of walking in patients with paralysis.