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. 2026 Jan 12;18:193. doi: 10.1007/s40820-025-02042-2

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© The Author(s) 2026

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 7 — Schematic illustration of real-time, asynchronous, and collaborative non-invasive BCIs. a Top: Schematic illustration of MI-BCI experimental paradigm. Bottom: Comparative performance of online BCI control. Reproduced with permission [138].

Copyright 2025, IEEE. b Decoding based on EMG signals. Reproduced with permission [139]. Copyright 2025, Springer Nature. c Left: ErrP decoding results. Right: Schematic of the control architecture and experimental protocol. Reproduced with permission [140]. Copyright 2021, Springer Nature. d Left: Schematic of the BCI robot control system and TE of the robot 3D reach task. Right: Comparison of the strategies of direct BCI control and shared BCI control. Reproduced with permission [142]. Copyright 2023, IEEE