Edelman Bradley J, Zhang Shuailei, Schalk Gerwin, Brunner Peter, Muller-Putz Gernot, Guan Cuntai, He Bin
IEEE Rev Biomed Eng. 2025;18:26-49. doi: 10.1109/RBME.2024.3449790. Epub 2025 Jan 28.
Brain-computer interface (BCI) is a rapidly evolving technology that has the potential to widely influence research, clinical and recreational use. Non-invasive BCI approaches are particularly common as they can impact a large number of participants safely and at a relatively low cost. Where traditional non-invasive BCIs were used for simple computer cursor tasks, it is now increasingly common for these systems to control robotic devices for complex tasks that may be useful in daily life. In this review, we provide an overview of the general BCI framework as well as the various methods that can be used to record neural activity, extract signals of interest, and decode brain states. In this context, we summarize the current state-of-the-art of non-invasive BCI research, focusing on trends in both the application of BCIs for controlling external devices and algorithm development to optimize their use. We also discuss various open-source BCI toolboxes and software, and describe their impact on the field at large.
脑机接口（BCI）是一项快速发展的技术，有可能对研究、临床和娱乐用途产生广泛影响。非侵入性BCI方法尤为常见，因为它们能够以相对较低的成本安全地影响大量参与者。传统的非侵入性BCI用于简单的计算机光标任务，而现在这些系统越来越普遍地用于控制机器人设备以执行可能在日常生活中有用的复杂任务。在本综述中，我们概述了通用的BCI框架以及可用于记录神经活动、提取感兴趣信号和解码脑状态的各种方法。在此背景下，我们总结了非侵入性BCI研究的当前技术水平，重点关注BCI在控制外部设备方面的应用趋势以及优化其使用的算法开发。我们还讨论了各种开源BCI工具箱和软件，并描述了它们对整个领域的影响。
