Evidence map›Paper›PMID 41253791›Full record

ArticleScientific data2025

HEFMI-ICH: a hybrid EEG-fNIRS motor imagery dataset for brain-computer interface in intracerebral hemorrhage.

Jian Shi, Danyang Chen, Xingwei Zhao, Zhixian Zhao, Shengjie Li, Yeguang Xu, Tao Ding, Zheng Zhu, Peng Zhang, Qing Ye and 4 more

Abstract readDataset
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

14 authors.

Jian Shi *State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Danyang Chen *Department of Neurology, Tongji Hospital, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Xingwei ZhaoState Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Zhixian ZhaoDepartment of Neurology, Tongji Hospital, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Shengjie LiDepartment of Neurology, Tongji Hospital, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Yeguang XuDepartment of Neurology, Tongji Hospital, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Tao DingState Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Zheng ZhuGigaAI, Beijing, China.
Peng ZhangHubei Bioinformatics and Molecular Imaging Key Laboratory, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Qing YeBig Data and Artificial Intelligence Office, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Yingxin TangDepartment of Neurology, Tongji Hospital, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Ping ZhangDepartment of Neurology, Tongji Hospital, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, Hubei, China. ppkitty0609@163.com.
Bo TaoState Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China. taobo@hust.edu.cn.
Zhouping TangDepartment of Neurology, Tongji Hospital, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, Hubei, China. ddjtzp@163.com.ORCID 0000-0002-4153-8590

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study introduces the first hybrid brain-computer interface dataset specifically designed for research on intracerebral hemorrhage (ICH) rehabilitation. It offers a novel data source through the synchronized acquisition of electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals. The dataset innovatively incorporated neural recordings from 17 normal subjects and 20 patients with ICH under standardized left-right hand motor imagery (MI) paradigms, featuring systematically collected and preprocessed dual-modality neural data. Beyond raw neural signals, the resource provides feature-engineered data optimized for classification algorithms and multidimensional signal decoding. The public availability of this dataset can facilitate the validation and optimization of MI decoding algorithms and advance the development of precision rehabilitation systems based on multimodal neural feedback.

Indexed as

Brain-Computer InterfacesCerebral HemorrhageElectroencephalographyHumansSpectroscopy, Near-Infrared

Identifiers

PMID41253791
PMCPMC12627794

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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.