Evidence map›Paper›PMID 42919847›Full record

Reviewnpj biomedical innovations2026

Generalizable neural decoding for clinically scalable brain-computer interfaces.

Yuanjie Gu, Haotian Yin, Yiqun Wang, Yan-Qi-Vivian Woon, Yujie Wang, Mengge Teng, Chengze Lu, Zhi Lu, Jie Chen

Abstract readReview
PubMed Publisher
In one paragraph

Review in npj biomedical innovations, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Yuanjie Gu *College of Biomedical Engineering, Fudan University, Shanghai, China.ORCID https://orcid.org/0000-0003-3099-8724
Haotian Yin *College of Biomedical Engineering, Fudan University, Shanghai, China.
Yiqun Wang *College of Biomedical Engineering, Fudan University, Shanghai, China.
Yan-Qi-Vivian Woon *College of Biomedical Engineering, Fudan University, Shanghai, China.
Yujie WangCollege of Biomedical Engineering, Fudan University, Shanghai, China.
Mengge TengCollege of Biomedical Engineering, Fudan University, Shanghai, China.
Chengze LuCollege of Biomedical Engineering, Fudan University, Shanghai, China.
Zhi LuDepartment of Psychological and Cognitive Sciences, Tsinghua University, Beijing, China.ORCID https://orcid.org/0000-0003-3739-8756
Jie ChenCollege of Biomedical Engineering, Fudan University, Shanghai, China. chen_j@fudan.edu.cn.

Funding

Natural Science Foundation of China 62575154Natural Science Foundation of China 625B2053Young Scientists Fund of Beijing Natural Science Foundation 4254114
6 · The paper itself

Abstract

Brain-computer interfaces promise restored communication and movement, yet accuracy achieved under development rarely survives new sessions, users, tasks, or hardware. Generalization, not peak performance, determines clinical scalability. Here we examine generalizable neural decoding from development to deployment, organized by the domain held out at evaluation, target-data access, adaptation strategy, and the clinical conditions under which performance persists, identifying benchmarking standards, prospective validation, and hardware-algorithm co-design as prerequisites for durable benefit.

Identifiers

PMID42919847

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.