Quadcopter Robot Control Based on Hybrid Brain-Computer Interface System
Quadcopter Robot Control Based on Hybrid Brain-Computer Interface System
复制标题
基于脑机混合接口系统的四轴飞行器机器人控制
DOI：
10.18494/sam.2020.2517
复制
发表时间：
2020-01-01
影响因子：
1.2
通讯作者：
Shin, Duk
中科院分区：
文献类型：
--
作者：
Chao, Chen;Zhou, Peng;Shin, Duk
最近提出了一种混合脑机接口（hBCI），以解决现有的单模态脑机接口（BCI）的准确性和信息传输速率（ITR）方面的限制，通过组合一个以上的模态。hBCI系统也为患者展示了良好的前景，因为以人为中心的智能机器人控制系统的设计可以允许高效率地执行多个任务。在本文中，我们提出了一个混合多控制系统，同时使用脑电（EEG）和眼电（EOG）信号。预处理阶段后，我们使用了一个共同的空间模式（CSP）算法提取EEG和EOG功能的运动想象和眼球运动。此外，使用支持向量机（SVM）来解决多类问题，并通过四轴四轴飞行器（例如，起飞、前进、后退、滑行、滑行和着陆）。在线解码的实验结果表明，97.14，95.23，98.09，和96.66%的平均准确率，和45.80，43.99，46.78，和45.34位/分钟的平均ITR在四轴飞行器的控制下实现。这些在线实验结果表明，所提出的混合系统可能会更好地完成多方向控制任务，以增加多任务和脑机接口的维度。
A hybrid brain-computer interface (hBCI) has recently been proposed to address the limitations of existing single-modal brain computer interfaces (BCIs) in terms of accuracy and information transfer rate (ITR) by combining more than one modality. The hBCI system also showed promising prospects for patients because the design of a human-centered smart robot control system may allow the performance of multiple tasks with high efficiency. In this paper, we present a hybrid multicontrol system that simultaneously uses electroencephalography (EEG) and electrooculography (EOG) signals. After the preprocessing phase, we used a common spatial pattern (CSP) algorithm to extract EEG and EOG features from motor imagery and eye movements. Moreover, a support vector machine (SVM) was used to solve a multiclass problem and complete flight operations through the asynchronous hBCI control of a four-axis quadcopter (e.g., takeoff, forward, backward, rightward, leftward, and landing). Online decoding of experimental results showed that 97.14, 95.23, 98.09, and 96.66% average accuracies, and 45.80, 43.99, 46.78, and 45.34 bits/min average ITRs were achieved in the control of a quadcopter. These online experimental results showed that the proposed hybrid system might be better in terms of completing multidirection control tasks to increase the multitasking and dimensionality of a BCI.