Key result
Review highlights prospects and limitations of EEG-based BCI frameworks for vehicle and quadcopter control.
Why the study?
Choosing the suitable brain signal acquisition technique among available options is a major concern when using BCI for operating vehicles, robots, and aircraft.
This review surveys the use of EEG-based brain-computer interfaces for autonomous control of vehicles and quadcopters.
EEG-based BCI merits cautious exploration for vehicle control; leaves open real-world feasibility pending validation of limitations.
Brain-computer interface (BCI) has had exciting improvements in the last decade due to the developments in brain science and computer technology, making BCI a top research area in applied science. With the advancement of technologies, researchers are now experimenting using BCI for operating vehicles, robots, and aircraft. However, choosing the suitable brain signal acquisition technique among the available ones is a big concern. In this paper, we will survey the studies that used the BCI framework for controlling vehicles and quadcopters, its limitations, its prospect, and the reason electroencephalogram (EEG) best suits the BCI framework.
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Biswas et al. (2023) conducted a review in Brain-computer interface (BCI) for autonomous control. EEG-based BCI was evaluated. This review surveys studies using the BCI framework for controlling vehicles and quadcopters, highlighting its prospects, limitations, and the suitability of EEG for BCI applications.
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