Evidence map›Paper›PMID 39483493›Full record

ArticleNeuroSci2024

Influence of Temporal and Frequency Selective Patterns Combined with CSP Layers on Performance in Exoskeleton-Assisted Motor Imagery Tasks.

Cristian David Guerrero-Mendez, Cristian Felipe Blanco-Diaz, Hamilton Rivera-Flor, Pedro Henrique Fabriz-Ulhoa, Eduardo Antonio Fragoso-Dias, Rafhael Milanezi de Andrade, Denis Delisle-Rodriguez, Teodiano Freire Bastos-Filho

Abstract read
In one paragraph

Article in NeuroSci, 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. 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

8 authors.

Cristian David Guerrero-MendezPostgraduate Program in Electrical Engineering, Federal University of Espírito Santo (UFES), Vitoria 29075-910, Brazil; cblanco88@uan.edu.co (C.F.B.-D.); hamriver@gmail.com (H.R.-F.); pedro.ulhoa@edu.ufes.br (P.H.F.-U.); teodiano.bastos@ufes.br (T.F.B.-F.).ORCID https://orcid.org/0000-0003-1019-9423
Cristian Felipe Blanco-DiazPostgraduate Program in Electrical Engineering, Federal University of Espírito Santo (UFES), Vitoria 29075-910, Brazil; cblanco88@uan.edu.co (C.F.B.-D.); hamriver@gmail.com (H.R.-F.); pedro.ulhoa@edu.ufes.br (P.H.F.-U.); teodiano.bastos@ufes.br (T.F.B.-F.).ORCID https://orcid.org/0000-0002-8083-7454
Hamilton Rivera-FlorPostgraduate Program in Electrical Engineering, Federal University of Espírito Santo (UFES), Vitoria 29075-910, Brazil; cblanco88@uan.edu.co (C.F.B.-D.); hamriver@gmail.com (H.R.-F.); pedro.ulhoa@edu.ufes.br (P.H.F.-U.); teodiano.bastos@ufes.br (T.F.B.-F.).ORCID https://orcid.org/0000-0001-7401-899X
Pedro Henrique Fabriz-UlhoaPostgraduate Program in Electrical Engineering, Federal University of Espírito Santo (UFES), Vitoria 29075-910, Brazil; cblanco88@uan.edu.co (C.F.B.-D.); hamriver@gmail.com (H.R.-F.); pedro.ulhoa@edu.ufes.br (P.H.F.-U.); teodiano.bastos@ufes.br (T.F.B.-F.).ORCID https://orcid.org/0000-0003-1164-8518
Eduardo Antonio Fragoso-DiasGraduate Program in Mechanical Engineering, Federal University of Espírito Santo (UFES), Vitoria 29075-910, Brazil; eduardo.a.dias@edu.ufes.br (E.A.F.-D.); rafhael.andrade@ufes.br (R.M.d.A.).
Rafhael Milanezi de AndradeGraduate Program in Mechanical Engineering, Federal University of Espírito Santo (UFES), Vitoria 29075-910, Brazil; eduardo.a.dias@edu.ufes.br (E.A.F.-D.); rafhael.andrade@ufes.br (R.M.d.A.).ORCID https://orcid.org/0000-0002-2839-3649
Denis Delisle-RodriguezPostgraduate Program in Neuroengineering, Santos Dumont Institute, Macaiba 59280-000, Brazil; denis.rodriguez@isd.org.br.ORCID https://orcid.org/0000-0002-8937-031X
Teodiano Freire Bastos-FilhoPostgraduate Program in Electrical Engineering, Federal University of Espírito Santo (UFES), Vitoria 29075-910, Brazil; cblanco88@uan.edu.co (C.F.B.-D.); hamriver@gmail.com (H.R.-F.); pedro.ulhoa@edu.ufes.br (P.H.F.-U.); teodiano.bastos@ufes.br (T.F.B.-F.).ORCID https://orcid.org/0000-0002-1185-2773

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Common Spatial Pattern (CSP) has been recognized as a standard and powerful method for the identification of Electroencephalography (EEG)-based Motor Imagery (MI) tasks when implementing brain-computer interface (BCI) systems towards the motor rehabilitation of lost movements. The combination of BCI systems with robotic systems, such as upper limb exoskeletons, has proven to be a reliable tool for neuromotor rehabilitation. Therefore, in this study, the effects of temporal and frequency segmentation combined with layer increase for spatial filtering were evaluated, using three variations of the CSP method for the identification of passive movement vs. MI+passive movement. The passive movements were generated using a left upper-limb exoskeleton to assist flexion/extension tasks at two speeds (high-85 rpm and low-30 rpm). Ten healthy subjects were evaluated in two recording sessions using Linear Discriminant Analysis (LDA) as a classifier, and accuracy (ACC) and False Positive Rate (FPR) as metrics. The results allow concluding that the use of temporal, frequency or spatial selective information does not significantly (

Indexed as

brain–computer interfacesEEGpassive movementsspatial–spectral filterupper limb

Identifiers

PMID39483493
PMCPMC11467971

What OpenQuestion holds

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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.