Evidence map›Paper›PMID 42265105›Full record

ArticleScientific data2026

An Electrospinography Database of Gait-Related Tasks and Motor Imagery Exercises.

Desirée I Gracia, Eduardo Iáñez, Mario Ortiz, José M Azorín

Abstract readDataset
In one paragraph

Article in Scientific data, 2026. 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. 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

4 authors.

Desirée I GraciaBrain-Machine Interface Systems Lab, Miguel Hernandez University of Elche, Elche, 03202, Spain.ORCID http://orcid.org/0000-0002-8855-1151
Eduardo IáñezBrain-Machine Interface Systems Lab, Miguel Hernandez University of Elche, Elche, 03202, Spain. eianez@umh.es.ORCID http://orcid.org/0000-0001-8057-5952
Mario OrtizBrain-Machine Interface Systems Lab, Miguel Hernandez University of Elche, Elche, 03202, Spain.ORCID http://orcid.org/0000-0002-4269-1554
José M AzorínBrain-Machine Interface Systems Lab, Miguel Hernandez University of Elche, Elche, 03202, Spain.ORCID http://orcid.org/0000-0001-5548-9657

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study presents a dataset of electrospinography (ESG) signals recorded from the human spinal cord during gait-related activities and motor imagery tasks. The dataset was acquired as part of a broader initiative to develop a spinal-machine interface (SMI) for closed-loop control of lower limb exoskeletons. ESG signals were collected using high-density surface electromyography (HD-sEMG) electrodes from fourteen able-bodied participants performing baseline trials (2), movement execution tasks (12) and motor imagery tasks conducted both in static conditions (5) and during movement (5). The dataset encompasses multiple electrode configurations targeting the brachial and lumbar plexuses, as well as surrounding musculature, across three experimental protocols. A total of 10 sessions were recorded for Experiment 1 (one 64-electrode matrix), 10 sessions for Experiment 2 (two 32-electrode matrices) and 5 sessions for Experiment 3 (two-32 electrode matrices). Preprocessing techniques were applied to mitigate cardiac and motion artifacts. The data provides a valuable and pionneering resource for advancing neurorehabilitation research, allowing the refining of exoskeleton control strategies and improving artifact removal methods.

Indexed as

ElectromyographyGaitSpinal CordHumans

Identifiers

PMID42265105
PMCPMC13590476

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.