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Assessing the driver’s current level of working Memory load with high density functional near-infrared spectroscopy: a realistic driving simulator study

Unni, Anirudh and Ihme, Klas and Jipp, Meike and Rieger, Jochem (2017) Assessing the driver’s current level of working Memory load with high density functional near-infrared spectroscopy: a realistic driving simulator study. Frontiers in Human Neuroscience, 11, p. 167. Frontiers Media S.A.. DOI: doi: 10.3389/fnhum.2017.00167 ISSN 1662-5161

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Official URL: http://journal.frontiersin.org/article/10.3389/fnhum.2017.00167/abstract

Abstract

Cognitive overload or underload results in a decrease in human performance which may result in fatal incidents while driving. We envision that driver assistive systems which adapt their functionality to the driver’s cognitive state could be a promising approach to reduce road accidents due to human errors. This research attempts to predict variations of cognitive working memory load levels in a natural driving scenario with multiple parallel tasks and to reveal predictive brain areas. We used a modified version of the n-back task to induce five different working memory load levels (from 0-back up to 4-back) forcing the participants to continuously update, memorize, and recall the previous ‘n’ speed sequences and adjust their speed accordingly while they drove for approximately 60 minutes on a highway with concurrent traffic in a virtual reality driving simulator. We measured brain activation using multichannel whole head, high density functional near-infrared spectroscopy (fNIRS) and predicted working memory load level from the fNIRS data by combining multivariate lasso regression and cross-validation. This allowed us to predict variations in working memory load in a continuous time-resolved manner with mean Pearson correlations between induced and predicted working memory load over 15 participants of 0.61 (standard error (SE) 0.04) and a maximum of 0.8. Restricting the analysis to prefrontal sensors placed over the forehead reduced the mean correlation to 0.38 (SE 0.04), indicating additional information gained through whole head coverage. Moreover, working memory load predictions derived from peripheral heart rate parameters achieved much lower correlations (mean 0.21, SE 0.1). Importantly, whole head fNIRS sampling revealed increasing brain activation in bilateral inferior frontal and bilateral temporo-occipital brain areas with increasing working memory load levels suggesting that these areas are specifically involved in workload-related processing.

Item URL in elib:https://elib.dlr.de/106448/
Document Type:Article
Title:Assessing the driver’s current level of working Memory load with high density functional near-infrared spectroscopy: a realistic driving simulator study
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Unni, AnirudhUniversität OldenburgUNSPECIFIED
Ihme, KlasKlas.Ihme (at) dlr.dehttps://orcid.org/0000-0002-7911-3512
Jipp, MeikeMeike.Jipp (at) dlr.deUNSPECIFIED
Rieger, JochemUniversität OldenburgUNSPECIFIED
Date:March 2017
Journal or Publication Title:Frontiers in Human Neuroscience
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:11
DOI :doi: 10.3389/fnhum.2017.00167
Page Range:p. 167
Publisher:Frontiers Media S.A.
ISSN:1662-5161
Status:Published
Keywords:cognitive workload, driving scenario, fNIRS, ECG, GSR, n-back, prefrontal cortex, fronto-parietal/ fronto-temporal network
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Terrestrial Vehicles (old)
DLR - Research area:Transport
DLR - Program:V BF - Bodengebundene Fahrzeuge
DLR - Research theme (Project):V - Fahrzeugintelligenz (old)
Location: Braunschweig
Institutes and Institutions:Institute of Transportation Systems > Human Factors
Deposited By: Ihme, Klas
Deposited On:24 Apr 2017 09:30
Last Modified:08 Mar 2018 18:40

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