Evidence map›Paper›PMID 29952751›Full record

ArticleJournal of neural engineering2018

The performance of 9-11-year-old children using an SSVEP-based BCI for target selection.

James J S Norton, Jessica Mullins, Birgit E Alitz, Timothy Bretl

Open access · greenAbstract read
In one paragraph

Article in Journal of neural engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
1.3field-weighted citation impact, top 22% 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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.

  1. Pooled it
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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 at 2 institutions in 1 country.

James J S NortonNational Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health, PO Box 22002, Albany, NY 12201, United States of America.ORCID 0000-0002-9690-0534
Jessica MullinsDepartment of Computer Science, University of Illinois, 201 N Goodwin Ave, Urbana, IL 61801, United States of America.
Birgit E AlitzDepartment of Electrical and Computer Engineering, University of Illinois, 306 N Wright St, Urbana, IL 61801, United States of America.
Timothy BretlDepartment of Aerospace Engineering, University of Illinois, 306 Talbot Laboratory, MC-236, 104 S. Wright St, Urbana, IL 61801, United States of America.ORCID 0000-0001-7883-7300
University of Illinois Urbana-Champaign · USNew York State Department of Health · US

Funding

Training and DisseminationP41EB018783 · NIBIB · WADSWORTH CENTER · PI Jonathan Saul Carp · 2014 to 2026
$15.4M
NIBIB NIH HHS P41 EB018783
6 · The paper itself

Abstract

objectiveIn this paper, we report the performance of 9-11-year-old children using a steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) and provide control data collected from adults for comparison. Children in our study achieved a much higher performance (79% accuracy; average age 9.64 years old) than the only previous investigation of children using an SSVEP-based BCI (∼50% accuracy; average age 9.86 years old). APPROACH: Experiments were conducted in two phases, a short calibration phase and a longer experimental phase. An offline analysis of the data collected during the calibration phase was used to set two parameters for a classifier and to screen participants who did not achieve a minimum accuracy of 85%. MAIN

resultsEleven of the 14 children and all 11 of the adults who completed the calibration phase met the minimum accuracy requirement. During the experimental phase, children selected targets with a similar accuracy (79% for children versus 78% for adults), latency (2.1 s for children versus 1.9 s for adults), and bitrate (0.50 bits s SIGNIFICANCE: This study shows that children can use an SSVEP-based BCI with higher performance than previously believed and is the first to report the performance of children using an SSVEP-based BCI in terms of latency and bitrate. The results of this study imply that children with severe motor disabilities (such as locked-in syndrome) may use an SSVEP-based BCI to restore/replace the ability to communicate.

Indexed as

AdultAgedAgingBrain-Computer InterfacesCalibrationChildElectroencephalographyEvoked Potentials, SomatosensoryFemaleHumansMaleMiddle AgedPhotic StimulationPsychomotor PerformanceSignal Processing, Computer-AssistedYoung Adult

Identifiers

PMID29952751
PMCPMC6309895
OpenAlexW2810736457

What OpenQuestion holds

Textmetadata
LicenceTDM
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.