A rehabilitation design concept based on brain-computer interface and McKibben artificial muscle

Abstract

This perspective proposes a restrained rehabilitation design that reframes an electroencephalography (EEG)-based brain-computer interface (BCI) from continuous motor control to an intention-gating signal that determines when and how strongly haptic cues should be delivered. A McKibben artificial-muscle haptic navigation module encodes task deviation into a small, semantically consistent directional codebook, enabling intuitive “coach-like” guidance while minimizing visual/verbal dependence. This concept emphasizes safety-biased thresholds, low-intrusion feedback, protocol-level reporting of gating reliability, and cue-dose tapering to promote autonomy and skill transfer under real-world variability and drift.

Keywords

Haptics / Brain-computer interface / Wearable device

Ethics approval

This study proposes a theoretical design concept and framework for rehabilitation devices, and no human or animal experiments were conducted in the research process. Therefore, no ethical approval was required for this work in accordance with the relevant research ethics guidelines. For the potential clinical translation of the proposed design in the future, the implementation of human trials will strictly comply with the Declaration of Helsinki and obtain ethical approval from the institutional review board (IRB) of the host institution, as well as written informed consent from all participants.

Funding information

This work was supported by the Innovative Research Group of the Chongqing Municipal Education Commission (CXQT19026), Cooperative Project between the Chinese Academy of Sciences and the University in Chongqing (HZ2021011), Young Project of Science and Technology Research Program of the Chongqing Education Commission of China (KJQN202501166), and Chongqing Municipal Human Resources and Social Security Bureau (CSTB2025YCJH-KYXM0046).

CRediT authorship contribution statement

Zhen Tian: Supervision, Writing - review & editing. Zhanwei Wang: Writing - original draft. Shaojie Gu: Writing - original draft. Zihao Zuo: Writing - original draft. Yang Jiang: Writing - original draft. Yanhong Peng: Writing - original draft, Writing - review & editing, Conceptualization, Funding acquisition. All the authors have read and approved the final version of this manuscript.

Data availability

No empirical data were generated for this theoretical design concept; thus, data availability is not applicable.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Declaration of Generative AI and AI-assisted technologies in the writing process

ChatGPT (GPT-5.2) was used to review manuscript grammar. All authors reviewed and edited the content and take full responsibility for the final manuscript. No other generative AI tools were used in the preparation of this work. (explicitly state no other AI use).

Acknowledgments

None.

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