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Prediction of temperature induced office worker's performance during typing task using EEG.

Tapsya Nayak, Tinghe Zhang, Zijing Mao

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |October 25, 2017
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    This study shows electroencephalogram (EEG) brain signals can accurately predict office worker performance. Brain power spectral densities from EEG offer more robust and reliable predictions than traditional physiological measures.

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    Area of Science:

    • Neuroscience
    • Environmental Psychology
    • Human-Computer Interaction

    Background:

    • Office worker performance is significantly impacted by indoor environmental factors.
    • Existing methods for predicting human performance lack satisfactory accuracy.
    • Predicting performance is crucial for economic and sociological reasons.

    Purpose of the Study:

    • To develop a predictive model for human performance using neurophysiological signals.
    • To investigate the efficacy of electroencephalogram (EEG) signals in predicting performance under varying indoor temperatures.
    • To compare EEG-based predictors with traditional physiological measures.

    Main Methods:

    • Collected electroencephalogram (EEG) data from participants during simulated office tasks.
    • Exposed participants to different indoor room temperatures (22°C and 30°C).
    • Developed regression models using EEG power spectral densities (PSD), skin temperature, and heart rate as predictors.

    Main Results:

    • EEG-derived brain power spectral densities (PSD) yielded a significantly higher R-squared value (over 3-fold increase) compared to skin temperature or heart rate predictors.
    • The predictive model utilizing EEG signals demonstrated greater robustness than models based on skin temperature and heart rate.
    • Demonstrated the potential of neurophysiological signals for accurate performance prediction.

    Conclusions:

    • Brain signals, specifically EEG-derived PSD, are highly effective predictors of human office work performance.
    • Neurophysiological monitoring offers a more reliable approach to performance prediction in dynamic indoor environments.
    • This research highlights a novel pathway for optimizing workplace productivity through understanding brain activity.