Evidence map›Paper›PMID 34180188›Full record

ArticleSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2021

[Execution, assessment and improvement methods of motor imagery for brain-computer interface].

Guixin Tian, Junjie Chen, Peng Ding, Anmin Gong, Fan Wang, Jiangong Luo, Yiyang Dong, Lei Zhao, Caiping Dang, Yunfa Fu

Abstract read
In one paragraph

Article in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. [Recognition of motor imagery electroencephalogram based on flicker noise spectroscopy and weighted filter bank common spatial pattern].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023
    Article
  2. Article
  3. [Brain-computer interface: from lab to real scene].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2021
    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

10 authors.

Guixin TianSchool of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P.R.China.
Junjie ChenSchool of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P.R.China.
Peng DingSchool of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P.R.China.
Anmin GongCollege of Information Engineering, Engineering University of PAP, Xi'an 710000, P.R.China.
Fan WangSchool of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P.R.China.
Jiangong LuoSchool of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P.R.China.
Yiyang DongSchool of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P.R.China.
Lei ZhaoBrain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming 650500, P.R.China.
Caiping DangSchool of Health and Management, Guangzhou Medical University, Guangzhou 511436 P.R.China.
Yunfa FuSchool of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P.R.China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motor imagery (MI) is an important paradigm of driving brain computer interface (BCI). However, MI is not easy to control or acquire, and the performance of MI-BCI depends heavily on the performance of the subjects' MI. Therefore, the correct execution of MI mental activities, ability evaluation and improvement methods play important and even critical roles in the improvement and application of MI-BCI system's performance. However, in the research and development of MI-BCI, the existing researches mainly focus on the decoding algorithm of MI, but do not pay enough attention to the above three aspects of MI mental activities. In this paper, these problems of MI-BCI are discussed in detail, and it is pointed out that the subjects tend to use visual motor imagery as kinesthetic motor imagery. In the future, we need to develop some objective, quantitatively visualized MI ability evaluation methods, and develop some effective and less time-consumption training methods to improve MI ability. It is also necessary to solve the differences and commonness of MI problems between and within individuals and MI-BCI illiteracy to a certain extent.

Indexed as

Brain-Computer InterfacesAlgorithmsElectroencephalographyHumansImagery, PsychotherapyImaginationassessment of motor imagerybrain-computer interfaceimprovement of motor imagerykinesthetic motor imageryvisual motor imagery

Identifiers

PMID34180188
PMCPMC9927765

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.