Title: Prediction of human performance using EEG data to improve safety and productivity in the mines

Authors: Gunda Yuga Raju; Suprakash Gupta; Lalit Kumar Singh

Addresses: Department of Mining Engineering, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh, India ' Department of Mining Engineering, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh, India ' Department of Atomic Energy, The Nuclear Power Corporation of India Limited (NPCIL), Mumbai, Maharashtra, India

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.

DOI: 10.1504/IJRS.2023.132946

International Journal of Reliability and Safety, 2023 Vol.17 No.1, pp.40 - 54

Received: 01 Feb 2023
Accepted: 16 May 2023
Published online: 20 Aug 2023 *