High Cognitive Load Assessment in Drivers Through Wireless Electroencephalography and the Validation of a Modified N-Back Task

Dengbo He · Birsen Donmez · Cheng Chen Liu · Konstantinos N. Plataniotis

79 citations0/0 files storedIEEE Transactions on Human-Machine Systems

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Abstract

This paper explores the influence of high cognitive load on vehicle driver's electroencephalography (EEG) signals collected from two channels (Fp1, Fp2) using a wireless consumer-grade system. Although EEG has been used in driving-related research to assess cognitive load, only a few studies focused on high load, and they used research-grade systems. Recent advancements allow for less intrusive and more affordable systems. As an exploration, we tested the feasibility of one such system to differentiate among three levels of cognitive taskload in a simulator study. Thirty-seven participants completed a baseline drive with no secondary task and two drives with a modified version of the n-back task (1-back and 2-back). The modification removed the verbal response required during task presentation to prevent EEG-signal degradation, with the 2-back task expected to impose higher load than that by the 1-back task. Another objective of this study is to validate that this modified task increased the cognitive load in the expected manner. The modified task led to significant trends from baseline to 1-back, and from 1-back to 2-back in participants' heart rate, galvanic skin response, respiration, horizontal gaze position variability, and pupil diameter, all in line with the previous driving-related studies on cognitive load. Furthermore, the EEG system was observed to be sensitive to the modified task, with the power of alpha band decreasing significantly with increasing n-back levels (baseline versus 1-back: 0.092 Bels on Fp1, 0.179 on Fp2; 1-back versus 2-back: 0.209 on Fp1, 0.147 on Fp2). Thus, a consumer-grade EEG system has the potential to capture high levels of cognitive load experienced by drivers.

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References

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