Prediction of human performance using electroencephalography under different indoor room temperatures

Tapsya Nayak, Tinghe Zhang, Zijing Mao, Xiaojing Xu, Lin Zhang, Daniel J. Pack, Bing Dong, Yufei Huang

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

Varying indoor environmental conditions is known to affect office worker’s 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.

Original languageEnglish (US)
Article number74
JournalBrain Sciences
Volume8
Issue number4
DOIs
StatePublished - Apr 2018

Keywords

  • Electroencephalography (EEG)
  • Human performance
  • Indoor room temperature
  • Office-work tasks
  • Performance prediction

ASJC Scopus subject areas

  • Neuroscience(all)

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