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Brain Sci. 2018, 8(4), 74; https://doi.org/10.3390/brainsci8040074

Prediction of Human Performance Using Electroencephalography under Different Indoor Room Temperatures

1
Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX 78249, USA
2
NSF-DOE CURRENT Center, University of Tennessee, Knoxville, TN 37996, USA
3
SIEE, China University of Mining and Technology, Xuzhou 221116, China
4
College of Engineering & Computer Science, University of Tennessee, Chattanooga, TN 37403, USA
5
Department of Mechanical Engineering, University of Texas at San Antonio, San Antonio, TX 78249, USA
*
Author to whom correspondence should be addressed.
Received: 13 April 2018 / Revised: 19 April 2018 / Accepted: 19 April 2018 / Published: 23 April 2018
(This article belongs to the Special Issue Brain-Computer Interfaces for Human Augmentation)
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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. View Full-Text
Keywords: human performance; performance prediction; indoor room temperature; office-work tasks; electroencephalography (EEG) human performance; performance prediction; indoor room temperature; office-work tasks; electroencephalography (EEG)
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Nayak, T.; Zhang, T.; Mao, Z.; Xu, X.; Zhang, L.; Pack, D.J.; Dong, B.; Huang, Y. Prediction of Human Performance Using Electroencephalography under Different Indoor Room Temperatures. Brain Sci. 2018, 8, 74.

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