P300 Brain–Computer Interface-Based Drone Control in Virtual and Augmented Reality

• Published in: Sensors (Basel, Switzerland) Vol. 21; no. 17; p. 5765
• Main Authors: Kim, Soram, Lee, Seungyun, Kang, Hyunsuk, Kim, Sion, Ahn, Minkyu
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 27.08.2021; MDPI
• Subjects: Accuracy; Augmented reality; augmented reality (AR); BCI application; brain–computer interface (BCI); Cameras; drone; Electroencephalography; Interfaces; P300; Signal processing; Virtual reality; virtual reality (VR)
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s21175765

Since the emergence of head-mounted displays (HMDs), researchers have attempted to introduce virtual and augmented reality (VR, AR) in brain–computer interface (BCI) studies. However, there is a lack of studies that incorporate both AR and VR to compare the performance in the two environments. Therefore, it is necessary to develop a BCI application that can be used in both VR and AR to allow BCI performance to be compared in the two environments. In this study, we developed an opensource-based drone control application using P300-based BCI, which can be used in both VR and AR. Twenty healthy subjects participated in the experiment with this application. They were asked to control the drone in two environments and filled out questionnaires before and after the experiment. We found no significant (p > 0.05) difference in online performance (classification accuracy and amplitude/latency of P300 component) and user experience (satisfaction about time length, program, environment, interest, difficulty, immersion, and feeling of self-control) between VR and AR. This indicates that the P300 BCI paradigm is relatively reliable and may work well in various situations.