Prediction of human performance using EEG data to improve safety and productivity in the mines
Gunda Yuga Raju,
Suprakash Gupta and
Lalit Kumar Singh
International Journal of Reliability and Safety, 2023, vol. 17, issue 1, 40-54
Abstract:
Dynamic cognitive performance has an impact on the safety and productivity of mine workers. Previous studies show that physiological measures have a good correlation with cognition during task execution. Observing the escalating demand for safe production in mines, it is now a crucial research area to examine the physiological variables that can predict cognitive performance prior to task allocation. In this experimental work, we have tried to predict how well participants will do on upcoming tasks using brain signals captured by electroencephalography. An Electroencephalogram (EEG) was recorded from 40 participants who subsequently took a cognitive test. After data analysis, our results show that EEG features can predict cognitive performance, with R = 0.48, p = 0.002, for the memory task and R = 0.546, p<0.001 for the attention task. This study also discussed the potential area of applicability in mining and some management strategies for dealing with workload and fatigue-related issues.
Keywords: safety; productivity; cognitive performance; data analysis; EEG; electroencephalogram; mining industry. (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=132946 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijrsaf:v:17:y:2023:i:1:p:40-54
Access Statistics for this article
More articles in International Journal of Reliability and Safety from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().