Literature DB >> 22768642

Sensitivity of physiological measures for detecting systematic variations in cognitive demand from a working memory task: an on-road study across three age groups.

Bruce Mehler1, Bryan Reimer, Joseph F Coughlin.   

Abstract

OBJECTIVE: To assess the sensitivity of two physiological measures for discriminating between levels of cognitive demand under driving conditions across different age groups.
BACKGROUND: Previous driving research presents a mixed picture concerning the sensitivity of physiological measures for differentiating tasks with presumed differences in mental workload.
METHOD: A total of 108 relatively healthy drivers balanced by gender and across three age groups (20-29, 40-49, 60-69) engaged in three difficulty levels of an auditory presentation-verbal response working memory task.
RESULTS: Heart rate and skin conductance level (SCL) both increased in a statistically significant fashion with each incremental increase in cognitive demand, whereas driving performance measures did not provide incremental discrimination. SCL was lower in the 40s and 60s age groups; however, the pattern of incremental increase with higher demand was consistent for heart rate and SCL across all age groups. Although each measure was quite sensitive at the group level, considering both SCL and heart rate improved detection of periods of heightened cognitive demand at the individual level.
CONCLUSION: The data provide clear evidence that two basic physiological measures can be utilized under field conditions to differentiate multiple levels of objectively defined changes in cognitive demand. Methodological considerations, including task engagement, may account for some of the inconsistencies in previous research. APPLICATION: These findings increase the confidence with which these measures may be applied to assess relative differences in mental workload when developing and optimizing human machine interface (HMI) designs and in exploring their potential role in advanced workload detection and augmented cognition systems.

Entities:  

Mesh:

Year:  2012        PMID: 22768642     DOI: 10.1177/0018720812442086

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  19 in total

1.  Effect of Electronic Device Use While Driving on Cardiovascular Reactivity.

Authors:  Sharon C Welburn; Ayushi Amin; Despina Stavrinos
Journal:  Transp Res Part F Traffic Psychol Behav       Date:  2018-02-23

2.  Efficacy of personalized models in discriminating high cognitive demand conditions using text-based interactions.

Authors:  Lisa M Vizer; Andrew Sears
Journal:  Int J Hum Comput Stud       Date:  2017-03-02       Impact factor: 3.632

3.  Brief report: examining driving behavior in young adults with high functioning autism spectrum disorders: a pilot study using a driving simulation paradigm.

Authors:  Bryan Reimer; Ronna Fried; Bruce Mehler; Gagan Joshi; Anela Bolfek; Kathryn M Godfrey; Nan Zhao; Rachel Goldin; Joseph Biederman
Journal:  J Autism Dev Disord       Date:  2013-09

4.  Using Psychophysiological Sensors to Assess Mental Workload During Web Browsing.

Authors:  Angel Jimenez-Molina; Cristian Retamal; Hernan Lira
Journal:  Sensors (Basel)       Date:  2018-02-03       Impact factor: 3.576

5.  A Novel Method for Classifying Driver Mental Workload Under Naturalistic Conditions With Information From Near-Infrared Spectroscopy.

Authors:  Anh Son Le; Hirofumi Aoki; Fumihiko Murase; Kenji Ishida
Journal:  Front Hum Neurosci       Date:  2018-10-26       Impact factor: 3.169

6.  Using Smartbands, Pupillometry and Body Motion to Detect Discomfort in Automated Driving.

Authors:  Matthias Beggiato; Franziska Hartwich; Josef Krems
Journal:  Front Hum Neurosci       Date:  2018-09-24       Impact factor: 3.169

7.  Demonstrating Brain-Level Interactions Between Visuospatial Attentional Demands and Working Memory Load While Driving Using Functional Near-Infrared Spectroscopy.

Authors:  Jakob Scheunemann; Anirudh Unni; Klas Ihme; Meike Jipp; Jochem W Rieger
Journal:  Front Hum Neurosci       Date:  2019-01-23       Impact factor: 3.169

8.  Multi-modal assessment of on-road demand of voice and manual phone calling and voice navigation entry across two embedded vehicle systems.

Authors:  Bruce Mehler; David Kidd; Bryan Reimer; Ian Reagan; Jonathan Dobres; Anne McCartt
Journal:  Ergonomics       Date:  2015-10-12       Impact factor: 2.778

9.  Multi-modal demands of a smartphone used to place calls and enter addresses during highway driving relative to two embedded systems.

Authors:  Bryan Reimer; Bruce Mehler; Ian Reagan; David Kidd; Jonathan Dobres
Journal:  Ergonomics       Date:  2016-04-25       Impact factor: 2.778

10.  A comprehensive prediction and evaluation method of pilot workload.

Authors:  Chuanyan Feng; Xiaoru Wanyan; Kun Yang; Damin Zhuang; Xu Wu
Journal:  Technol Health Care       Date:  2018       Impact factor: 1.285

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