Prediction of Human Performance Using Electroencephalography under Different Indoor Room Temperatures

dc.contributor.authorNayak, Tapsya
dc.contributor.authorZhang, Tinghe
dc.contributor.authorMao, Zijing
dc.contributor.authorXu, Xiaojing
dc.contributor.authorZhang, Lin
dc.contributor.authorPack, Daniel J.
dc.contributor.authorDong, Bing
dc.contributor.authorHuang, Yufei
dc.date.accessioned2021-04-19T15:08:50Z
dc.date.available2021-04-19T15:08:50Z
dc.date.issued2018-04-23
dc.date.updated2021-04-19T15:08:51Z
dc.description.abstractVarying indoor environmental conditions is known to affect office workers' performance; wherein past research studies have reported the effects of unfavorable indoor temperature and air quality causing sick building syndrome (SBS) among office workers. Thus, investigating factors that can predict performance in changing indoor environments have become a highly important research topic bearing significant impact in our society. While past research studies have attempted to determine predictors for performance, they do not provide satisfactory prediction ability. Therefore, in this preliminary study, we attempt to predict performance during office-work tasks triggered by different indoor room temperatures (22.2 ◦C and 30 ◦C) from human brain signals recorded using electroencephalography (EEG). Seven participants were recruited, from whom EEG, skin temperature, heart rate and thermal survey questionnaires were collected. Regression analyses were carried out to investigate the effectiveness of using EEG power spectral densities (PSD) as predictors of performance. Our results indicate EEG PSDs as predictors provide the highest R2 (> 0.70), that is 17 times higher than using other physiological signals as predictors and is more robust. Finally, the paper provides insight on the selected predictors based on brain activity patterns for low- and high-performance levels under different indoor-temperatures.
dc.description.departmentElectrical and Computer Engineering
dc.description.departmentMechanical Engineering
dc.identifierdoi: 10.3390/brainsci8040074
dc.identifier.citationBrain Sciences 8 (4): 74 (2018)
dc.identifier.urihttps://hdl.handle.net/20.500.12588/407
dc.rightsAttribution 4.0 United States
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjecthuman performance
dc.subjectperformance prediction
dc.subjectindoor room temperature
dc.subjectoffice-work tasks
dc.subjectelectroencephalography (EEG)
dc.titlePrediction of Human Performance Using Electroencephalography under Different Indoor Room Temperatures
dc.typeArticle

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