Rodríguez-Ugarte Marisol, Iáñez Eduardo, Ortiz Mario, Azorín Jose M
Brain-Machine Interface Systems Lab, Systems Engineering and Automation Department, Miguel Hernández University of Elche, Elche, Spain.
Front Neurosci. 2018 Oct 23;12:757. doi: 10.3389/fnins.2018.00757. eCollection 2018.
The aim of this work was to test if a novel transcranial direct current stimulation (tDCS) montage boosts the accuracy of lower limb motor imagery (MI) detection by using a real-time brain-machine interface (BMI) based on electroencephalographic (EEG) signals. The tDCS montage designed was composed of two anodes and one cathode: one anode over the right cerebrocerebellum, the other over the motor cortex in Cz, and the cathode over FC2 (using the International 10-10 system). The BMI was designed to detect two MI states: relax and gait MI; and was based on finding the power at the frequency which attained the maximum power difference between the two mental states at each selected EEG electrode. Two different single-blind experiments were conducted, E1 and a pilot test E2. E1 was based on visual cues and feedback and E2 was based on auditory cues and a lower limb exoskeleton as feedback. Twelve subjects participated in E1, while four did so in E2. For both experiments, subjects were separated into two equally-sized groups: sham and active tDCS. The active tDCS group achieved 12.6 and 8.2% higher detection accuracy than the sham group in E1 and E2, respectively, reaching 65 and 81.6% mean detection accuracy in each experiment. The limited results suggest that the exoskeleton (E2) enhanced the detection of the MI tasks with respect to the visual feedback (E1), increasing the accuracy obtained in 16.7 and 21.2% for the active tDCS and sham groups, respectively. Thus, the small pilot study E2 indicates that using an exoskeleton in real-time has the potential of improving the rehabilitation process of cerebrovascular accident (CVA) patients, but larger studies are needed in order to further confirm this claim.
这项工作的目的是测试一种新型经颅直流电刺激（tDCS）组合是否能通过基于脑电图（EEG）信号的实时脑机接口（BMI）提高下肢运动想象（MI）检测的准确性。所设计的tDCS组合由两个阳极和一个阴极组成：一个阳极置于右侧脑桥小脑上方，另一个置于Cz处的运动皮层上方，阴极置于FC2上方（使用国际10 - 10系统）。该BMI旨在检测两种MI状态：放松和步态MI；并基于在每个选定的EEG电极上找到两种心理状态之间功率差最大的频率处的功率。进行了两个不同的单盲实验，E1和预试验E2。E1基于视觉线索和反馈，E2基于听觉线索和下肢外骨骼作为反馈。12名受试者参与了E1，4名受试者参与了E2。对于这两个实验，受试者被分成两个规模相等的组：假刺激tDCS组和主动tDCS组。在E1和E2中，主动tDCS组的检测准确率分别比假刺激组高12.6%和8.2%，在每个实验中的平均检测准确率分别达到65%和81.6%。有限的结果表明，相对于视觉反馈（E1），外骨骼（E2）增强了MI任务的检测，主动tDCS组和假刺激组的准确率分别提高了16.7%和21.2%。因此，小型预试验E2表明，实时使用外骨骼有改善脑血管意外（CVA）患者康复过程的潜力，但需要更大规模的研究来进一步证实这一说法。
