An Innovative Brain-Computer Interface Interaction System Based on the Large Language Model

TL;DR

This paper presents a novel BCI system integrating SSVEP speller with large language models, enabling natural language input, dynamic paradigm generation, multilingual support, and personalized task interfaces, significantly enhancing BCI functionality and intelligence.

Contribution

The paper introduces an innovative BCI system that combines SSVEP speller with LLM API, providing dynamic paradigm generation, multilingual support, and personalized interfaces, addressing key limitations of existing BCI technologies.

Findings

Supports over ten languages with multilingual capabilities

Enables natural language input for BCI control

Allows dynamic adjustment of command prompts and layouts

Abstract

Recent advancements in large language models (LLMs) provide a more effective pathway for upgrading brain-computer interface (BCI) technology in terms of user interaction. The widespread adoption of BCIs in daily application scenarios is still limited by factors such as their single functionality, restricted paradigm design, weak multilingual support, and low levels of intelligence. In this paper, we propose an innovative BCI system that deeply integrates a steady-state visual evoked potential (SSVEP) speller with an LLM application programming interface (API). It allows natural language input through the SSVEP speller and dynamically calls large models to generate SSVEP paradigms. The command prompt, blinking frequency, and layout position are adjustable to meet the user's control requirements in various scenarios. More than ten languages are compatible with the multilingual support of LLM. A variety of task scenarios, such as home appliance control, robotic arm operation, and unmanned aerial vehicle (UAV) management are provided. The task interfaces of the system can be personalized according to the user's habits, usage scenarios, and equipment characteristics. By combining the SSVEP speller with an LLM, the system solves numerous challenges faced by current BCI systems and makes breakthroughs in functionality, intelligence, and multilingual support. The introduction of LLM not only enhances user experience but also expands the potential applications of BCI technology in real-world environments.