Evidence map›Paper›PMID 34393745›Full record

ArticleFrontiers in computational neuroscience2021

Sparse Granger Causality Analysis Model Based on Sensors Correlation for Emotion Recognition Classification in Electroencephalography.

Dongwei Chen, Rui Miao, Zhaoyong Deng, Na Han, Chunjian Deng

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in computational neuroscience, 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. [Research on emotion recognition method based on IWOA-ELM algorithm for electroencephalogram].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2024
    Article
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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

5 authors.

Dongwei ChenZhuhai People's Hospital (Zhuhai Hospital Affiliated With Jinan University), Zhuhai, China.
Rui MiaoFaculty of Information Technology, Macau University of Science and Technology, Avenida Wai Long, Taipa, China.
Zhaoyong DengUniversity of Electronic Science and Technology of China, Chengdu, China.
Na HanSchool of Business, Beijing Institute of Technology, Zhuhai, China.
Chunjian DengSchool of Electronic Information Engineering, University of Electronic Science and Technology of China, Zhongshan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, affective computing based on electroencephalogram (EEG) data has attracted increased attention. As a classic EEG feature extraction model, Granger causality analysis has been widely used in emotion classification models, which construct a brain network by calculating the causal relationships between EEG sensors and select the key EEG features. Traditional EEG Granger causality analysis uses the

Indexed as

EEG sensorsgranger causality analysisL1/2-based sparse granger causality analysisL2 norm logistic regressionLASSOSC-SGA

Identifiers

PMID34393745
PMCPMC8358835

What OpenQuestion holds

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Registered trials

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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.