Data from: Noninvasive electroencephalogram based control of a robotic arm for reach and grasp tasks

Brain-computer interface (BCI) technologies aim to provide a bridge between the human brain and external devices. Prior research using non-invasive BCI to control virtual objects, such as computer cursors and virtual helicopters, and real-world objects, such as wheelchairs and quadcopters, has demonstrated the promise of BCI technologies. However, controlling a robotic arm to complete reach-and-grasp tasks efficiently using non-invasive BCI has yet to be shown. In this study, we found that a group of 13 human subjects could willingly modulate brain activity to control a robotic arm with high accuracy for performing tasks requiring multiple degrees of freedom by combination of two sequential low dimensional controls. Subjects were able to effectively control reaching of the robotic arm through modulation of their brain rhythms within the span of only a few training sessions and maintained the ability to control the robotic arm over multiple months. Our results demonstrate the viability of human operation of prosthetic limbs using non-invasive BCI technology.脑机接口（Brain-computer interface，BCI）技术旨在搭建人类大脑与外部设备之间的交互桥梁。此前已有研究借助非侵入式脑机接口控制虚拟对象（如计算机光标、虚拟直升机）与现实世界设备（如轮椅、四旋翼无人机），证实了脑机接口技术的应用前景。然而，利用非侵入式脑机接口高效控制机械臂完成伸手抓取任务的相关成果，迄今尚未见报道。本研究发现，13名人类受试者可通过自主调节大脑活动，结合两项序列低维控制操作，高精度操控机械臂完成具备多自由度要求的任务。受试者仅需数轮训练即可通过调节脑节律，有效控制机械臂的伸展动作，且该操控能力可维持长达数月。本研究结果证实，借助非侵入式脑机接口技术实现人类操控义肢的可行性。