Evidence map›Paper›PMID 30002615›Full record

ArticleFrontiers in neuroscience2018

Evaluation of Switch and Continuous Navigation Paradigms to Command a Brain-Controlled Wheelchair.

Álvaro Fernández-Rodríguez, Francisco Velasco-Álvarez, Manon Bonnet-Save, Ricardo Ron-Angevin

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  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

4 authors.

Álvaro Fernández-RodríguezDepartmento de Tecnología Electrónica, Universidad de Málaga, Malaga, Spain.
Francisco Velasco-ÁlvarezDepartmento de Tecnología Electrónica, Universidad de Málaga, Malaga, Spain.
Manon Bonnet-SaveIMS UMR Centre National de la Recherche Scientifique 5218, Cognitique et Ingénierie Humaine, Bordeaux INP-ENSC, Bordeaux, France.
Ricardo Ron-AngevinDepartmento de Tecnología Electrónica, Universidad de Málaga, Malaga, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A brain-computer interface (BCI) is a technology allowing patients with severe motor dysfunctions to use their electroencephalographic signals to create a communication channel to control devices. The objective of this paper is to study the feasibility of continuous and switch control modes for a brain-controlled wheelchair (BCW) using sensorimotor rhythms (SMR) modulated through a right-hand motor imagery task. Previous studies, which used a continuous navigation control with SMR, have reported the difficulty of maintaining the motor imagery task for a long time, especially for the forward command. The switch control has been presented as a proposal that may help to solve this issue since this task is only used temporary for either disabling or enabling the movement. Regarding the methodology, 10 of 15 able-bodied users, who had overcome the criterion of 30% error rate in the calibration phase, controlled the BCW using both paradigms. The navigation tasks consisted of a straight path divided in five sections: in three of them the users had to move forward, and in the other two the users had to maintain their position. To assess user performance in the device management, a usability approach was adopted, measuring the factors of effectiveness, efficiency, and satisfaction. Then, variables related to the time employed and commands selected by the user or parameters related to the confusion matrix were applied. In addition, the scores in NASA-TLX and two

Indexed as

brain-computer interface (BCI)continuousnavigation controlswitchusabilitywheelchair

Identifiers

PMID30002615
PMCPMC6031925

What OpenQuestion holds

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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.