Fu Yunfa, Lu Haichen
Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P. R. China.
Brain Cognition and Brain-computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming 650500, P. R. China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2025 Aug 25;42(4):651-659. doi: 10.7507/1001-5515.202507053.
Brain-computer interface (BCI) technology faces structural risks due to a misalignment between its technological maturity and industrialization expectations. This study used the Technology Readiness Level (TRL) framework to assess the status of major BCI paradigms-such as steady-state visual evoked potential (SSVEP), motor imagery, and P300-and found that they predominantly remained at TRL4 to TRL6, with few stable applications reaching TRL9. The analysis identified four interrelated sources of bubble risk: overly broad definitions of BCI, excessive focus on decoding performance, asynchronous translational progress, and imprecise terminology usage. These distortions have contributed to the misallocation of research resources and public misunderstanding. To foster the sustainable development of BCI, this paper advocated the establishment of a standardized TRL evaluation system, clearer terminological boundaries, stronger support for fundamental research, enhanced ethical oversight, and the implementation of inclusive and diversified governance mechanisms.
脑机接口(BCI)技术因其技术成熟度与产业化期望之间的不匹配而面临结构性风险。本研究使用技术就绪水平(TRL)框架评估了主要BCI范式的现状,如稳态视觉诱发电位(SSVEP)、运动想象和P300,发现它们主要停留在TRL4到TRL6水平,很少有稳定应用达到TRL9。分析确定了泡沫风险的四个相互关联的来源:对BCI的定义过于宽泛、过度关注解码性能、异步的转化进展以及术语使用不精确。这些偏差导致了研究资源的错误分配和公众的误解。为促进BCI的可持续发展,本文主张建立标准化的TRL评估体系、更清晰的术语界限、对基础研究的更强支持、加强伦理监督以及实施包容和多样化的治理机制。