Evidence map›Paper›PMID 20347612›Full record

ArticleClinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology2010

Towards a user-friendly brain-computer interface: initial tests in ALS and PLS patients.

Ou Bai, Peter Lin, Dandan Huang, Ding-Yu Fei, Mary Kay Floeter

Abstract read
In one paragraph

Article in Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
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  5. Trial
  6. Brain-computer interface: an update for the clinicians.Frontiers in human neuroscience · 2026
    Review
  7. Review
  8. Electroacupuncture Alters BCI-Based Brain Network in Stroke Patients.Computational intelligence and neuroscience · 2022
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Creating the feedback loop: closed-loop neurostimulation.Neurosurgery clinics of North America · 2014
    Review
  17. Article
  18. Article
  19. Article
  20. 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

5 authors.

Ou BaiEEG & BCI Laboratory, Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA. obai@vcu.edu
Peter Lin
Dandan Huang
Ding-Yu Fei
Mary Kay Floeter

Funding

Spasticity and Upper Motor Neuron DisordersZIANS002976 · NINDS · NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE · PI FLOETER, MARY KAY · 2009 to 2019
$7.3M
Intramural NIH HHS ZIA NS002976
6 · The paper itself

Abstract

objectivePatients usually require long-term training for effective EEG-based brain-computer interface (BCI) control due to fatigue caused by the demands for focused attention during prolonged BCI operation. We intended to develop a user-friendly BCI requiring minimal training and less mental load.

methodsTesting of BCI performance was investigated in three patients with amyotrophic lateral sclerosis (ALS) and three patients with primary lateral sclerosis (PLS), who had no previous BCI experience. All patients performed binary control of cursor movement. One ALS patient and one PLS patient performed four-directional cursor control in a two-dimensional domain under a BCI paradigm associated with human natural motor behavior using motor execution and motor imagery. Subjects practiced for 5-10min and then participated in a multi-session study of either binary control or four-directional control including online BCI game over 1.5-2h in a single visit.

resultsEvent-related desynchronization and event-related synchronization in the beta band were observed in all patients during the production of voluntary movement either by motor execution or motor imagery. The online binary control of cursor movement was achieved with an average accuracy about 82.1+/-8.2% with motor execution and about 80% with motor imagery, whereas offline accuracy was achieved with 91.4+/-3.4% with motor execution and 83.3+/-8.9% with motor imagery after optimization. In addition, four-directional cursor control was achieved with an accuracy of 50-60% with motor execution and motor imagery.

conclusionPatients with ALS or PLS may achieve BCI control without extended training, and fatigue might be reduced during operation of a BCI associated with human natural motor behavior. SIGNIFICANCE: The development of a user-friendly BCI will promote practical BCI applications in paralyzed patients.

Indexed as

Amyotrophic Lateral SclerosisUser-Computer InterfaceAdultAgedBrainBrain MappingElectroencephalographyElectromyographyFemaleHumansImaginationMaleMiddle AgedMotor ActivityMovementPsychomotor Performance

Identifiers

PMID20347612
PMCPMC2895010

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.