BCIwiki (bciwiki.com) — Researchers led by teams at Kunming University of Science and Technology have proposed Human Factors Engineering for brain-computer interfaces (BCIs) as an emerging interdisciplinary field, arguing that reliability and usability bottlenecks stand in the way of large-scale real-world BCI deployment, in a conceptual review reported in Brain Sciences on October 5, 2026. The authors are Liu Yan, Tianwen Li, Lei Zhao, Anmin Gong, Hao Fang and Wuheng Zuo.
Human factors engineering already covers cognitive ergonomics, workload, adaptive automation and human-in-the-loop systems, but has historically focused on overt behavior and peripheral physiological measures rather than central neural activity as a primary control input, the authors wrote. They said targeted conceptual and methodological frameworks are lacking for interaction that uses brain activity as direct input and relies on long-term brain-computer co-adaptation.
Drawing on features such as the implicit nature of BCI input, the review defines research boundaries and names 4 core research objects: user neurocognitive characteristics, brain-computer collaborative adaptation mechanisms, multimodal feedback regulation and contextual adaptation patterns. It poses 3 core scientific questions on individual differences and dynamic adaptation, human factors optimization and fault tolerance, and contextual generalizability, with ethics, privacy and user rights treated as an overarching dimension.
The paper also outlines a methodological system built on multimodal measurement and modeling, closed-loop validation and multidimensional evaluation, and discusses how artificial intelligence methods can support it. The authors said the approach is intended to provide a theoretical reference for user-friendly BCI design.