When Brain-Computer Interfaces Meet the Metaverse: Landscape, Demonstrator, Trends, Challenges, and Concerns

TL;DR

This work examines how Brain-Computer Interfaces can enhance metaverse immersion by analyzing current status, proposing a modular integration framework, and validating it with a driving metaverse demonstrator. It introduces four BCI use cases—cognitive distraction, emotion, drowsiness, and authentication—showing high F1-scores and underscoring RF as a robust classifier across tasks. The paper also discusses medium and long term trajectories for BCIs across metaverse scenarios and senses, and addresses critical concerns around privacy, cybersecurity, safety, and ethics. Overall, it highlights substantial potential for brain–metaverse integration while outlining key research, standardization, and security challenges to enable scalable, safe deployment.

Abstract

The metaverse has gained tremendous popularity in recent years, allowing the interconnection of users worldwide. However, current systems in metaverse scenarios, such as virtual reality glasses, offer a partial immersive experience. In this context, Brain-Computer Interfaces (BCIs) can introduce a revolution in the metaverse, although a study of the applicability and implications of BCIs in these virtual scenarios is required. Based on the absence of literature, this work reviews, for the first time, the applicability of BCIs in the metaverse, analyzing the current status of this integration based on different categories related to virtual worlds and the evolution of BCIs in these scenarios in the medium and long term. This work also proposes the design and implementation of a general framework that integrates BCIs with different data sources from sensors and actuators (e.g., VR glasses) based on a modular design to be easily extended. This manuscript also validates the framework in a demonstrator consisting of driving a car within a metaverse, using a BCI for neural data acquisition, a VR headset to provide realism, and a steering wheel and pedals. Four use cases (UCs) are selected, focusing on cognitive and emotional assessment of the driver, detection of drowsiness, and driver authentication while using the vehicle. Moreover, this manuscript offers an analysis of BCI trends in the metaverse, also identifying future challenges that the intersection of these technologies will face. Finally, it reviews the concerns that using BCIs in virtual world applications could generate according to different categories: accessibility, user inclusion, privacy, cybersecurity, physical safety, and ethics.

Figures (7)

• Figure 1: Summary of the application of BCIs in the metaverse. The left side presents a study on common metaverse application scenarios. The figure on the right depicts an analysis of the human five senses.
• Figure 2: General representation of the framework functionality. Blue dashed boxes indicate relevant data exchanged, either representing inputs to the framework or the outputs from the framework used as feedback to the VR headset.
• Figure 3: Modules of the proposed framework, representing the main techniques applicable for each module implemented and the relationships between them.
• Figure 4: Setup used to evaluate the performance of the framework in the metaverse for each use case defined.
• Figure 5: Performance obtained by the framework for UC1, considering binary and multiclass approaches to predict distractions while driving.