Evidence map›Paper›PMID 41315347›Full record

ArticleScientific data2025

A multi-paradigm EEG dataset for studying upper limb rehabilitation exercises.

Wenwen Chang, Weixuan Kong, Guanghui Yan, Renjie Lv, Kaiyue Du, Muhammad Tariq Sadiq, Bin Guo, Rong Yin, Xuan Liu

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, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

9 authors.

Wenwen ChangSchool of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China. changww2013@126.com.
Weixuan KongSchool of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China.ORCID 0009-0004-5632-2575
Guanghui YanSchool of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China.
Renjie LvSchool of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China.
Kaiyue DuSchool of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China.
Muhammad Tariq SadiqSchool of Computer Science and Electronic Engineering, University of Essex, Colchester Campus, Colchester, CO4 3SQ, UK.
Bin GuoSchool of Computer Science, Northwestern Polytechnical University, Xi 'an, 710129, China.
Rong YinGansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730079, China.
Xuan LiuGansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730079, China.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 62366028, 62466032, W2421090;Natural Science Foundation of Gansu Province 24JRRA256
6 · The paper itself

Abstract

Most stroke survivors experience persistent upper limb motor dysfunction, and brain-computer interface (BCI) rehabilitation technologies have been widely explored to address this issue. However, systematic comparisons and analyses of differences among rehabilitation paradigms remain challenging due to the lack of multi-paradigm EEG datasets from the same subjects. This study aims to construct an EEG dataset that collects various rehabilitation paradigms for the same subjects. A total of 28 healthy subjects were recruited, and EEG data were collected under six types of upper limb rehabilitation paradigms. Each paradigm involves two or three actions, including grasping and releasing with the left, right, or both hands. The dataset includes both raw EEG signals and preprocessed versions with bandpass filtering and artifact removal. This resource will support studies comparing the neural mechanisms underlying different rehabilitation paradigms and aid in the development of optimized rehabilitation strategies.

Indexed as

ElectroencephalographyExercise TherapyStroke RehabilitationUpper ExtremityAdultBrain-Computer InterfacesHumansMale

Identifiers

PMID41315347
PMCPMC12663233

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.