综述脑机接口信号采集与交互范式，揭示技术协同演化路径
A Review of Brain-Computer Interface Technologies: Signal Acquisition Methods and Interaction Paradigms
- 梳理非侵入、微创与侵入式信号采集方法原理与进展
- 分析经典、分类及混合交互范式特性与应用场景
- 适合关注人机交互前沿的科研人员与工程开发者
脑机接口（BCI）技术实现了人脑与外部设备的直接通信，是人机交互的重大突破。本文深入分析了各类BCI范式，包括经典范式、当前分类体系及混合范式，阐述其各自特征与应用。同时，系统探讨了非侵入、介入及侵入式信号采集技术的原理与最新进展。通过剖析范式与信号采集技术之间的相互依赖关系，本综述呈现了两大领域协同创新的全景图景。目标在于为构建更高效、易用且多功能的BCI系统提供洞见，强调范式设计与信号获取技术间的协同潜力，展望该领域的未来发展。
原文摘要 · Abstract (English)
Brain-Computer Interface (BCI) technology facilitates direct communication between the human brain and external devices, representing a substantial advancement in human-machine interaction. This review provides an in-depth analysis of various BCI paradigms, including classic paradigms, current classifications, and hybrid paradigms, each with distinct characteristics and applications. Additionally, we explore a range of signal acquisition methods, classified into non-implantation, intervention, and implantation techniques, elaborating on their principles and recent advancements. By examining the interdependence between paradigms and signal acquisition technologies, this review offers a comprehensive perspective on how innovations in one domain propel progress in the other. The goal is to present insights into the future development of more efficient, user-friendly, and versatile BCI systems, emphasizing the synergy between paradigm design and signal acquisition techniques and their potential to transform the field.
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