实现可穿戴无线脑机接口，实时解码想象说话意图。
Toward Practical BCI: A Real-time Wireless Imagined Speech EEG Decoding System
- 构建端到端无线系统，支持便携设备实时解码想象说话信号。
- 在有线设备上达62%准确率，在无线头戴设备上达46.67%。
- 集成用户识别，提供个性化服务，适合日常使用场景。
脑机接口（BCI）研究虽具潜力，但多局限于静态固定环境，难以应用于真实场景。为推动实用化BCI发展，本文提出一种面向日常使用的实时无线想象说话脑电（EEG）解码系统。该框架强调实用性，突破有线设备限制，支持便携无线硬件。系统内置用户识别模块，可自动识别操作者并提供个性化服务。通过实验室流数据层（Lab Streaming Layer）实现连续脑电信号的实时传输与个性化解码。该端到端系统可实时分类想象说话指令，在有线设备上实现4类任务平均准确率62.00%，在便携无线头戴设备上达46.67%。本工作标志着向真正实用、可及的神经接口迈出关键一步，明确了未来鲁棒、实用、个性化脑机接口的研究方向。
原文摘要 · Abstract (English)
Brain-computer interface (BCI) research, while promising, has largely been confined to static and fixed environments, limiting real-world applicability. To move towards practical BCI, we introduce a real-time wireless imagined speech electroencephalogram (EEG) decoding system designed for flexibility and everyday use. Our framework focuses on practicality, demonstrating extensibility beyond wired EEG devices to portable, wireless hardware. A user identification module recognizes the operator and provides a personalized, user-specific service. To achieve seamless, real-time operation, we utilize the lab streaming layer to manage the continuous streaming of live EEG signals to the personalized decoder. This end-to-end pipeline enables a functional real-time application capable of classifying user commands from imagined speech EEG signals, achieving an overall 4-class accuracy of 62.00 % on a wired device and 46.67 % on a portable wireless headset. This paper demonstrates a significant step towards truly practical and accessible BCI technology, establishing a clear direction for future research in robust, practical, and personalized neural interfaces.
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