Evidence map›Paper›PMID 40000219›Full record

ReviewSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2024

[Applications and prospects of electroencephalography technology in neurorehabilitation assessment and treatment].

Weizhong He, Dengyu Wang, Qiangfan Meng, Feng He, Minpeng Xu, Dong Ming

Abstract readReviewEnglish Abstract
In one paragraph

Review in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2024. 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. Application and Research Progress of BCI in Post-Stroke Psychiatric Disorders: A Narrative Review.Medical science monitor : international medical journal of experimental and clinical research · 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

6 authors.

Weizhong HeAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, P. R. China.
Dengyu WangSchool of Medicine, Tsinghua University, Beijing 100084, P. R. China.
Qiangfan MengAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, P. R. China.
Feng HeAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, P. R. China.
Minpeng XuAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, P. R. China.
Dong MingAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the high incidence of neurological diseases such as stroke and mental illness, rehabilitation treatments for neurological disorders have received widespread attention. Electroencephalography (EEG) technology, despite its excellent temporal resolution, has historically been limited in application due to its insufficient spatial resolution, and is mainly confined to preoperative assessment, intraoperative monitoring, and epilepsy detection. However, traditional constraints of EEG technology are being overcome with the popularization of EEG technology with high-density over 64-lead, the application of innovative analysis techniques and the integration of multimodal techniques, which are significantly broadening its applications in clinical settings. These advancements have not only reinforced the irreplaceable role of EEG technology in neurorehabilitation assessment, but also expanded its therapeutic potential through its combined use with technologies such as transcranial magnetic stimulation, transcranial electrical stimulation and brain-computer interfaces. This article reviewed the applications, advancements, and future prospects of EEG technology in neurorehabilitation assessment and treatment. Advancements in technology and interdisciplinary collaboration are expected to drive new applications and innovations in EEG technology within the neurorehabilitation field, providing patients with more precise and personalized rehabilitation strategies.

Indexed as

ElectroencephalographyNervous System DiseasesNeurological RehabilitationBrain-Computer InterfacesEpilepsyHumansTranscranial Direct Current StimulationTranscranial Magnetic StimulationAssessmentElectroencephalographyMultimodal IntegrationNeurorehabilitationTreatment

Identifiers

PMID40000219
PMCPMC11955371

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.