Quadcopter Control System Using a Hybrid BCI Based on Off-Line Optimization and Enhanced Human-Machine Interaction

Nong Yan,Gang Wang,Chang Wang,Kexu Zhang,Jinming Li,Ting Chen,Yi Tao,Xiangguo Yan,Ziwen Yuan

doi:10.1109/access.2019.2961246

Abstract

Quadcopter is an important way for the human to explore the physical world. The brain-computer interface (BCI) technology is used to control the quadcopter flight in order to help disabled persons communicate with the external world freely. In this study, a quadcopter control system using a hybrid BCI based on off-line optimization and enhanced human-machine interaction was designed to control the quadcopter flight in 3D physical space. The proposed system implemented the control of quadcopter moving up/down, forward/backward, left/right by six different SSVEP, and turning left/right by left-hand and right-hand motor imagery. Meanwhile, the optimization of the control system and the human-machine interaction enhancement improved practicability in real-time use. Five subjects participated in an on-line experiment to control the quadcopter flight in real-time. The average classification accuracy of EEG-based commands in the on-line experiment was 87.09±2.82% and information transfer rate (ITR) was 0.857±0.085 bits/min. The results demonstrated the feasibility of multidirectional control of quadcopter flight in 3D space by using hybrid BCI technology and revealed the practicality and operability of the hybrid BCI control system based on off-line optimization and human-machine interaction enhancement.

Highlights

In recent years, the brain-computer interface (BCI), as technology in connecting the human brain with the external world, has been widely concerned due to the increasing needs and fast development of the human-machine interface
To solve the challenges mentioned above, a quadcopter control system using a hybrid BCI based on off-line optimization and enhanced human-machine interaction was designed to control the quadcopter flight in 3D physical space
The EEG in eyes-open state consisted of SSVEP and motor imagery

Summary

Introduction

The brain-computer interface (BCI), as technology in connecting the human brain with the external world, has been widely concerned due to the increasing needs and fast development of the human-machine interface. The BCI is aimed at assisting persons with severe motor function disability to communicate with the external world freely [1]. The quadcopter, as an important way for the human to explore the physical world, becomes an. The BCI and quadcopter control can be combined to explore the external world directly with users’ intention [5]. The quadcopter control system based on BCI is mainly divided into SSVEP-based BCI and motor imagery-based BCI. In the applications of SSVEP-based BCI, Lenis et al proposed an asynchronous system, which accomplished the control of quadcopter in 3D space by six different frequencies visual stimuli, and the detection of the idle state was introduced in this control system to avoid the fatigue of users [6].

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Discussion

Conclusion