Hayta Ünal, Irimia Danut Constantin, Guger Christoph, Erkutlu İbrahim, Güzelbey İbrahim Halil
Pilotage Department, Faculty of Aeronautics and Aerospace, Gaziantep University, 27310 Gaziantep, Turkey.
Department of Energy Utilization, Faculty of Electrical Engineering, Electrical Drives and Industrial Automation (EUEDIA), "Gheorghe Asachi" Technical University of Iasi, 700050 Iași, Romania.
Brain Sci. 2022 Jun 26;12(7):833. doi: 10.3390/brainsci12070833.
Brain-Computer Interface (BCI) technology has been shown to provide new communication possibilities, conveying brain information externally. BCI-based robot control has started to play an important role, especially in medically assistive robots but not only there. For example, a BCI-controlled robotic arm can provide patients diagnosed with neurodegenerative diseases such as Locked-in syndrome (LIS), Amyotrophic lateral sclerosis (ALS), and others with the ability to manipulate different objects. This study presents the optimization of the configuration parameters of a three-class Motor Imagery (MI) -based BCI for controlling a six Degrees of Freedom (DOF) robotic arm in a plane. Electroencephalography (EEG) signals are recorded from 64 positions on the scalp according to the International 10-10 System. In terms of the resulting classification of error rates, we investigated twelve time windows for the spatial filter and classifier calculation and three time windows for the variance smoothing time. The lowest error rates were achieved when using a 3 s time window for creating the spatial filters and classifier, for a variance time window of 1.5 s.
脑机接口（BCI）技术已被证明能提供新的通信可能性，将大脑信息向外传递。基于BCI的机器人控制已开始发挥重要作用，特别是在医疗辅助机器人领域，但不仅限于此。例如，一个由BCI控制的机械臂可以让被诊断患有诸如闭锁综合征（LIS）、肌萎缩侧索硬化症（ALS）等神经退行性疾病的患者有能力操纵不同物体。本研究提出了一种基于三类运动想象（MI）的BCI配置参数优化方法，用于在平面内控制一个六自由度（DOF）的机械臂。根据国际10-10系统，从头皮上的64个位置记录脑电图（EEG）信号。就最终的错误率分类而言，我们研究了用于空间滤波器和分类器计算的12个时间窗口以及用于方差平滑时间的3个时间窗口。当使用3秒的时间窗口来创建空间滤波器和分类器，以及1.5秒的方差时间窗口时，实现了最低的错误率。
