Evidence map›Paper›PMID 39537730›Full record

ArticleScientific reports2024

A subjective and objective fusion visual fatigue assessment system for different hardware and software parameters in SSVEP-based BCI applications.

Peiyuan Tian, Guanghua Xu, Chengcheng Han, Chenghang Du, Hui Li, Ruiquan Chen, Jieren Xie, Jiahuan Wang, Hanli Jiang, Xiaobing Guo and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

12 authors.

Peiyuan TianSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China.
Guanghua XuSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China. ghxu@xjtu.edu.cn.
Chengcheng HanSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China.
Chenghang DuSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China.
Hui LiSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China.
Ruiquan ChenSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China.
Jieren XieSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China.
Jiahuan WangSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China.
Hanli JiangSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China.
Xiaobing GuoSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China.
Sicong ZhangSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China.
Qingqiang WuSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China.

Funding

National Key Research and Development projects No.2021ZD0204300Natural Science Basic Research Program of Shaanxi Province Program No. 2023-JC-QN-0501The First Affiliated Hospital of Xi'an Jiaotong University No.20231055The First Affiliated Hospital of Xi'an Jiaotong University No.20231056
6 · The paper itself

Abstract

With the development of brain-computer interface industry, large amounts of related applications have entered people's vision. BCI applications based on steady-state visual evoked potentials (SSVEP) are widely used because they do not require pre-training and have high information transmission rates. However, in the actual use of SSVEP stimulus paradigm, the subjects will produce visual fatigue with the use, and fatigue will affect the transmission efficiency. In this experiment, an experimental environment consisting of two paradigm stimulus frequencies (7.5 Hz, 15 Hz), three resolutions (800 × 600, 1280 × 720, 1920 × 1080) and three refresh rates (120 Hz, 240 Hz, 360 Hz) is set up. The Likert scale is used to collect subjective fatigue and preference scores, and the EEG acquisition system and eye tracker are used to collect objective data. Using the proposed information entropy-CRITIC algorithm to combine subjective and objective indicators, a fatigue assessment system (display screen fitness-DSF) is innovated to score different experimental environments. The higher the DSF score, the better the visual experience. The results show that when using the 7.5 Hz SSVEP paradigm, the combination of 360 Hz and 1920 × 1080 can bring the best visual experience. When using the 15 Hz SSVEP paradigm, the combination of 240 Hz and 1280 × 720 is the best. DSF provides powerful help for hardware and software selection guidance and vision protection when using SSVEP-based BCI applications.

Indexed as

Brain-Computer InterfacesElectroencephalographyEvoked Potentials, VisualSoftwareAdultAlgorithmsAsthenopiaFatigueFemaleHumansMalePhotic StimulationYoung AdultDisplay screen fitnessRefresh ratesResolutionsSSVEPStimulus frequencies

Identifiers

PMID39537730
PMCPMC11560949

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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.