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An improved SSVEP-based brain-computer interface with low-contrast visual stimulation and its application in UAV

Yu Cheng¹, Lirong Yan^1,2, Muhammad Usman Shoukat¹

¹Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, People's Republic of China.

Journal of Neurophysiology

|July 10, 2024

Summary

This study introduces an improved steady-state visual-evoked potential (SSVEP) paradigm to reduce visual fatigue in brain-computer interfaces (BCIs). The enhanced SSVEP system successfully navigated unmanned aerial vehicles (UAVs) with high accuracy.

Keywords:

brain-computer interface steady-state visual-evoked potential unmanned aerial vehicle visual fatigue

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Area of Science:

Neuroscience
Human-Computer Interaction
Robotics

Background:

Brain-computer interfaces (BCIs) are vital for advanced human-machine interaction.
Steady-state visual-evoked potential (SSVEP) paradigms offer high accuracy but suffer from visual fatigue and occlusion.
Existing SSVEP methods require improvement for practical, long-term BCI applications.

Purpose of the Study:

To develop an enhanced SSVEP paradigm mitigating visual fatigue and occlusion.
To integrate the improved SSVEP paradigm into a BCI system for unmanned aerial vehicle (UAV) navigation.
To evaluate the performance and usability of the SSVEP-based BCI system in 2-D navigation tasks.

Main Methods:

Proposed an improved SSVEP paradigm by reducing visual stimulation contrast.
Developed a modified method for visual fatigue evaluation, incorporating subjective and objective measures.
Implemented the enhanced SSVEP paradigm in a BCI system for controlling a first-person perspective UAV.

Main Results:

The enhanced SSVEP paradigm significantly reduced visual stimulation and fatigue compared to the traditional method.
The SSVEP-based BCI system demonstrated high accuracy in performing 2-D UAV navigation and search tasks.
Experimental results confirmed the feasibility of the enhanced paradigm in practical BCI applications.

Conclusions:

The improved SSVEP paradigm effectively reduces visual fatigue while maintaining high accuracy.
The SSVEP-based BCI system offers a more intuitive and natural control method for external equipment like UAVs.
This research advances the development of practical and user-friendly BCIs for real-world applications.