Selecting Workload and Stress Measures for Performance Prediction

The study of performance, workload, and stress have become a mainstay in the field of Human Factors. These constructs are multi-faceted and are assessed by a variety of measures. In seeking to enhance performance by managing mental workload and stress, it is important for measures to be anchored to meaningful criteria. Workload and stress must be considered with respect to the performance measures that address the most central objectives. While workload and stress research has progressed over the years and includes research across different levels and domains, there has been less effort to link measures to specific performance outcomes. The present study examined four performance metrics from the same task in terms of the workload and stress measures that are most closely associated with, and predictive of them. Results indicated that different sets of workload and stress measures predicted different performance measures, suggesting that measures should also be selected based on the performance criteria of interest.

[1]  Arnaud Delorme,et al.  Frontal midline EEG dynamics during working memory , 2005, NeuroImage.

[2]  Rebecca A. Grier,et al.  Fundamental dimensions of subjective state in performance settings: task engagement, distress, and worry. , 2002, Emotion.

[3]  G. Krueger Sustained work, fatigue, sleep loss and performance: A review of the issues , 1989 .

[4]  Scott Makeig,et al.  Eye Activity Correlates of Workload during a Visuospatial Memory Task , 2001, Hum. Factors.

[5]  B. Tabachnick,et al.  Using multivariate statistics, 5th ed. , 2007 .

[6]  B. Chance,et al.  Cognition-activated low-frequency modulation of light absorption in human brain. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[7]  Christopher D. Wickens,et al.  Workload Assessment and Prediction , 1990 .

[8]  Mansour Rahimi,et al.  Techniques in mental workload assessment. , 1995 .

[9]  R. Schandry,et al.  Functional transcranial Doppler sonography as a tool in psychophysiological research. , 2003, Psychophysiology.

[10]  Meltem Izzetoglu Functional Optical Brain Imaging , 2012 .

[11]  Diana Adler,et al.  Using Multivariate Statistics , 2016 .

[12]  D. M. Green,et al.  Signal detection theory and psychophysics , 1966 .

[13]  Andreas Henelius,et al.  Mental workload classification using heart rate metrics , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[14]  Lauren Reinerman-Jones,et al.  Developing Methods for Utilizing Physiological Measures , 2010 .

[15]  Peter A. Hancock Whither Workload? Mapping a Path for Its Future Development , 2017, H-WORKLOAD.

[16]  K. Izzetoglu,et al.  Monitoring expertise development during simulated UAV piloting tasks using optical brain imaging , 2012, 2012 IEEE Aerospace Conference.

[17]  L. Walrath,et al.  Eye movement and pupillary response indices of mental workload during visual search of symbolic displays. , 1992, Applied ergonomics.

[18]  G. Robert J. Hockey,et al.  Level of Operator Control and Changes in Heart Rate Variability during Simulated Flight Maintenance , 1995, Hum. Factors.

[19]  Hankins Tc,et al.  A comparison of heart rate, eye activity, EEG and subjective measures of pilot mental workload during flight. , 1998, Aviation, space, and environmental medicine.

[20]  Harold R. Booher,et al.  Manprint: An Approach to Systems Integration , 1990 .

[21]  J. Abich Investigating The Universality And Comprehensive Ability Of Measures To Assess The State Of Workload , 2013 .

[22]  Rob Miles,et al.  “ KEY PERFORMANCE MEASURES FOR HUMAN FACTORS IN MAJOR HAZARD INDUSTRIES ” , 2011 .

[23]  Britton Chance,et al.  Functional Optical Brain Imaging Using Near-Infrared During Cognitive Tasks , 2004, Int. J. Hum. Comput. Interact..

[24]  S. Hart,et al.  Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research , 1988 .

[25]  Lauren Reinerman-Jones,et al.  Workload Is Multidimensional, Not Unitary: What Now? , 2015, HCI.

[26]  R. Parasuraman,et al.  Psychophysiology and adaptive automation , 1996, Biological Psychology.

[27]  B. Cain A Review of the Mental Workload Literature , 2007 .

[28]  Christopher D. Wickens,et al.  Automation Reliability in Unmanned Aerial Vehicle Control: A Reliance-Compliance Model of Automation Dependence in High Workload , 2006, Hum. Factors.