Evidence map›Paper›PMID 41152182›Full record

ArticleSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2025

[Ethical considerations for artificial intelligence-enhanced brain-computer interface].

Yuyu Cao, Yuhang Xue, Hengyuan Yang, Fan Wang, Tianwen Li, Lei Zhao, Yunfa Fu

Abstract readEnglish Abstract
PubMed Full text at PMC Publisher
In one paragraph

Article in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. [Analysis of the constraints of inherent limitations on the capability boundaries of brain-computer interfaces and corresponding strategies].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026
    Review
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

7 authors.

Yuyu CaoFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P. R. China.
Yuhang XueFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P. R. China.
Hengyuan YangFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P. R. China.
Fan WangFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P. R. China.
Tianwen LiBrain Cognition and Brain-computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming 650500, P. R. China.
Lei ZhaoBrain Cognition and Brain-computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming 650500, P. R. China.
Yunfa FuFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence-enhanced brain-computer interfaces (BCI) are expected to significantly improve the performance of traditional BCIs in multiple aspects, including usability, user experience, and user satisfaction, particularly in terms of intelligence. However, such AI-integrated or AI-based BCI systems may introduce new ethical issues. This paper first evaluated the potential of AI technology, especially deep learning, in enhancing the performance of BCI systems, including improving decoding accuracy, information transfer rate, real-time performance, and adaptability. Building on this, it was considered that AI-enhanced BCI systems might introduce new or more severe ethical issues compared to traditional BCI systems. These include the possibility of making users' intentions and behaviors more predictable and manipulable, as well as the increased likelihood of technological abuse. The discussion also addressed measures to mitigate the ethical risks associated with these issues. It is hoped that this paper will promote a deeper understanding and reflection on the ethical risks and corresponding regulations of AI-enhanced BCIs.

Indexed as

Artificial IntelligenceBrain-Computer InterfacesDeep LearningElectroencephalographyHumansUser-Computer InterfaceArtificial intelligenceArtificial intelligence-enhanced brain-computer interfaceBrain-computer interfaceDeep learningEthics for brain-computer interface

Identifiers

PMID41152182
PMCPMC12568730

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.