Developing an intelligent EEG platform for manipulation of robotic arms and rehabilitation applications

在本研究中，提出了一种新的基于EEG传感器的平台，以改善残疾人假肢臂的控制。这样的研究结果可以扩展到应用，如康复和控制瘫痪的肌肉。这项研究包括开发一种新的硬件装置来记录人体信号和运动。此外，将开发3D打印假肢手臂。机械臂的运动控制是基于感官输入信号。此外，基于人体自然运动的智能运动算法将被训练和实现。该项目的成功实施将导致一种功能假肢的发展，它将具有类似于人手的运动。值得一提的是，这将是第一次将脑电图、肌电图、运动传感器和摄像头的数据结合起来进行机器人手臂控制的研究。

In this research, a novel EEG sensor-based platform is proposed to improve the control of prosthetic arms for disabled patients. The results of such research can be extended to applications like rehabilitation and control of paralyzed muscles. The research consists of developing a new hardware setup to record the human body signals and movements. Furthermore, a 3D printable prosthetic arm will be developed. The movement control of the robotic arm is based on the sensory input signals. Moreover, an intelligent movement algorithm will be trained and implemented based on natural human body movements. The successful implementation of the project will lead to the development of a functional prosthetic arm that will have a movement similar to that of a human hand. It's not worthy to mention that this will the first research combing data from EEG, EMG, movement sensors and cameras for robotic arm control.