{"title":"EEG-based neural activity for decoding situation awareness at different levels.","authors":"Qianlan Wu, Na Chen, Pei-Luen Patrick Rau","doi":"10.1080/00140139.2024.2449570","DOIUrl":null,"url":null,"abstract":"<p><p>Situation awareness (SA) is the ability to perceive, comprehend and project environmental information. Neural activity is closely associated with SA. However, it remains unclear how neural activity represents SA at different levels. Here, three tasks were used to assess SA at three levels, behavioural and electroencephalogram data were collected. Relationships between SA and neural activity were explored through comparisons of EEG power between high and low SA. For each SA level, EEG power significantly differed between high and low SA. Brain region-based analyses further revealed neural activities originating from distinct brain regions were recruited to represent SA at different levels. These EEG pattern features differed between high and low SA could be used to decode SA with the KNN (k-nearest neighbour) classifier. The present study marked a significant step in augmenting our understanding of the neural mechanism that characterise SA.</p>","PeriodicalId":50503,"journal":{"name":"Ergonomics","volume":" ","pages":"1-13"},"PeriodicalIF":2.0000,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ergonomics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/00140139.2024.2449570","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
Abstract
Situation awareness (SA) is the ability to perceive, comprehend and project environmental information. Neural activity is closely associated with SA. However, it remains unclear how neural activity represents SA at different levels. Here, three tasks were used to assess SA at three levels, behavioural and electroencephalogram data were collected. Relationships between SA and neural activity were explored through comparisons of EEG power between high and low SA. For each SA level, EEG power significantly differed between high and low SA. Brain region-based analyses further revealed neural activities originating from distinct brain regions were recruited to represent SA at different levels. These EEG pattern features differed between high and low SA could be used to decode SA with the KNN (k-nearest neighbour) classifier. The present study marked a significant step in augmenting our understanding of the neural mechanism that characterise SA.
期刊介绍:
Ergonomics, also known as human factors, is the scientific discipline that seeks to understand and improve human interactions with products, equipment, environments and systems. Drawing upon human biology, psychology, engineering and design, Ergonomics aims to develop and apply knowledge and techniques to optimise system performance, whilst protecting the health, safety and well-being of individuals involved. The attention of ergonomics extends across work, leisure and other aspects of our daily lives.
The journal Ergonomics is an international refereed publication, with a 60 year tradition of disseminating high quality research. Original submissions, both theoretical and applied, are invited from across the subject, including physical, cognitive, organisational and environmental ergonomics. Papers reporting the findings of research from cognate disciplines are also welcome, where these contribute to understanding equipment, tasks, jobs, systems and environments and the corresponding needs, abilities and limitations of people.
All published research articles in this journal have undergone rigorous peer review, based on initial editor screening and anonymous refereeing by independent expert referees.