Iwatsuki Katsuyuki, Hoshiyama Minoru, Oyama Shintaro, Yoneda Hidemasa, Shimoda Shingo, Hirata Hitoshi
Department of Hand Surgery, Graduate School of Medicine, Nagoya University, Nagoya, Japan.
Department of Health Sciences, Faculty of Medicine, Nagoya University, Nagoya, Japan.
Front Synaptic Neurosci. 2020 Feb 28;12:7. doi: 10.3389/fnsyn.2020.00007. eCollection 2020.
We previously created a prosthetic hand with a tacit learning system (TLS) that automatically supports the control of forearm pronosupination. This myoelectric prosthetic hand enables sensory feedback and flexible motor output, which allows users to move efficiently with minimal burden. In this study, we investigated whether electroencephalography can be used to analyze the influence of the auxiliary function of the TLS on brain function. Three male participants who had sustained below-elbow amputations and were myoelectric prosthesis users performed a series of physical movement trials with the TLS inactivated and activated. Trials were video recorded and a sequence of videos was prepared to represent each individual's own use while the system was inactivated and activated. In a subsequent motor imagery phase during which electroencephalography (EEG) signals were collected, each participant was asked to watch both videos of themself while actively imagining the physical movement depicted. Differences in mean cortical current and amplitude envelope correlation (AEC) values between supplementary motor areas (SMA) and each vertex were calculated. For all participants, there were differences in the mean cortical current generated by the motor imagery tasks when the TLS inactivated and activated conditions were compared. The AEC values were higher during the movement imagery task with TLS activation, although their distribution on the cortex varied between the three individuals. In both S1 and other brain areas, AEC values increased in conditions with the TLS activated. Evidence from this case series indicates that, in addition to motor control, TLS may change sensory stimulus recognition.
我们之前创建了一种带有隐性学习系统（TLS）的假手，该系统能自动支持对前臂旋前旋后的控制。这种肌电假手能够实现感觉反馈和灵活的运动输出，使使用者能够以最小的负担高效移动。在本研究中，我们调查了脑电图是否可用于分析TLS辅助功能对脑功能的影响。三名男性参与者因肘部以下截肢而使用肌电假肢，他们在TLS失活和激活的状态下进行了一系列身体运动试验。试验过程被录像，并准备了一系列视频来展示系统失活和激活时每个参与者自己的使用情况。在随后收集脑电图（EEG）信号的运动想象阶段，要求每个参与者观看自己的两段视频，同时积极想象视频中描绘的身体运动。计算了辅助运动区（SMA）与每个顶点之间的平均皮质电流和振幅包络相关性（AEC）值的差异。对于所有参与者，比较TLS失活和激活状态下运动想象任务产生的平均皮质电流存在差异。在TLS激活的运动想象任务中，AEC值更高，尽管它们在三名参与者的皮质上的分布有所不同。在初级体感皮层（S1）和其他脑区中，TLS激活时AEC值均增加。该病例系列的证据表明，除了运动控制外，TLS可能会改变感觉刺激识别。
