Evidence map›Paper›PMID 34777531›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2021

Motor Imagery-Based Brain-Computer Interface Combined with Multimodal Feedback to Promote Upper Limb Motor Function after Stroke: A Preliminary Study.

Yi-Qian Hu, Tian-Hao Gao, Jie Li, Jia-Chao Tao, Yu-Long Bai, Rong-Rong Lu

Open access · hybridAbstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 7 pooled it
2.1field-weighted citation impact, top 13% of its field
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

16 citing papers in PubMed, 7 syntheses or guidelines pooled it, 27 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Trial
  9. Trial
  10. Brain-computer interface: an update for the clinicians.Frontiers in human neuroscience · 2026
    Review
  11. Article
  12. EEG-based sensorimotor neurofeedback for motor neurorehabilitation in children and adults: A scoping review.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2024
    Article
  13. Article
  14. Article
  15. Article
  16. Article
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 at 2 institutions in 1 country.

Yi-Qian HuDepartment of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China.ORCID https://orcid.org/0000-0001-7480-4210
Tian-Hao GaoDepartment of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China.ORCID https://orcid.org/0000-0002-1823-4134
Jie LiDepartment of Computer Science and Technology, Tongji University, No. 4800 Cao'an Highway, Shanghai 200092, China.ORCID https://orcid.org/0000-0002-9299-3251
Jia-Chao TaoDepartment of Computer Science and Technology, Tongji University, No. 4800 Cao'an Highway, Shanghai 200092, China.ORCID https://orcid.org/0000-0003-0383-1347
Yu-Long BaiDepartment of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China.ORCID https://orcid.org/0000-0003-0461-1506
Rong-Rong LuDepartment of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China.ORCID https://orcid.org/0000-0002-3227-7472
Fudan University · CNTongji University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecently, the brain-computer interface (BCI) has seen rapid development, which may promote the recovery of motor function in chronic stroke patients.

methodsTwelve stroke patients with severe upper limb and hand motor impairment were enrolled and randomly assigned into two groups: motor imagery (MI)-based BCI training with multimodal feedback (BCI group,

resultsCompared with the baseline, the FMA-UE score increased significantly in the BCI group (

conclusionMI-based BCI combined with sensory and visual feedback might improve severe upper limb and hand impairment in chronic stroke patients, showing the potential for application in rehabilitation medicine.

Identifiers

PMID34777531
PMCPMC8580676
OpenAlexW3209714269

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.