Stationarity of a User’s Pupil Size Signal as a Precondition of Pupillary-Based Mental Workload Evaluation

We discuss the concept of stationarity as a precondition of pupillary-based assessments of a user’s mental workload and report results from an experiment differentiating stationarity and non-stationarity pupillary size signals.

[1]  Ting-Peng Liang,et al.  Guidelines for Neuroscience Studies in Information Systems Research , 2014, J. Manag. Inf. Syst..

[2]  Peter Dalgaard,et al.  R Development Core Team (2010): R: A language and environment for statistical computing , 2010 .

[3]  Angelika Dimoka,et al.  On the Use of Neuropyhsiological Tools in IS Research: Developing a Research Agenda for NeuroIS , 2012, MIS Q..

[4]  E. Hess,et al.  Pupil Size in Relation to Mental Activity during Simple Problem-Solving , 1964, Science.

[5]  Angelika Dimoka,et al.  On the Foundations of NeuroIS: Reflections on the Gmunden Retreat 2009 , 2010, Commun. Assoc. Inf. Syst..

[6]  Andrew T. Duchowski,et al.  Eye Tracking Methodology: Theory and Practice , 2003, Springer London.

[7]  Andreas Eckhardt,et al.  Cognitive Workload Induced by Information Systems: Introducing an Objective Way of Measuring based on Pupillary Diameter Responses , 2013 .

[8]  J. Bradshaw,et al.  Pupil Size as a Measure of Arousal during Information Processing , 1967, Nature.

[9]  Jan Theeuwes,et al.  Cognitive and Ocular Factors Jointly Determine Pupil Responses under Equiluminance , 2016, PloS one.

[10]  Sandra P Marshall,et al.  Identifying cognitive state from eye metrics. , 2007, Aviation, space, and environmental medicine.

[11]  J. Beatty.  Task-evoked pupillary responses, processing load, and the structure of processing resources. , 1982, Psychological bulletin.

[12]  Ricardo Buettner,et al.  Mental Workload States on the Basis of the Pupillary Hippus , 2022 .

[13]  Ricardo Buettner,et al.  Cognitive Workload of Humans Using Artificial Intelligence Systems: Towards Objective Measurement Applying Eye-Tracking Technology , 2013, KI.

[14]  S. Sirois,et al.  Pupillometry , 2012, Perspectives on psychological science : a journal of the Association for Psychological Science.

[15]  S. P. Marshall,et al.  The Index of Cognitive Activity: measuring cognitive workload , 2002, Proceedings of the IEEE 7th Conference on Human Factors and Power Plants.

[16]  Ricardo Buettner,et al.  A User's Cognitive Workload Perspective in Negotiation Support Systems: an eye-tracking Experiment , 2016, PACIS.

[17]  S. Steinhauer,et al.  Sympathetic and parasympathetic innervation of pupillary dilation during sustained processing. , 2004, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[18]  Björn Niehaves,et al.  Standing on the Shoulders of Giants: Challenges and Recommendations of Literature Search in Information Systems Research , 2015, Commun. Assoc. Inf. Syst..

[19]  Angelika Dimoka,et al.  THE POTENTIAL OF COGNITIVE NEUROSCIENCE FOR INFORMATION SYSTEMS RESEARCH , 2008 .

[20]  Christian Maier,et al.  Towards Ex Ante Prediction of User Performance: A Novel NeuroIS Methodology Based on Real-Time Measurement of Mental Effort , 2015, 2015 48th Hawaii International Conference on System Sciences.

[21]  Megan H. Papesh,et al.  Pupil Dilation Reflects the Creation and Retrieval of Memories , 2012 .

[22]  Angelika Dimoka,et al.  Research Commentary - NeuroIS: The Potential of Cognitive Neuroscience for Information Systems Research , 2011, Inf. Syst. Res..

[23]  Ricardo Buettner,et al.  The Relationship Between Visual Website Complexity and a User’s Mental Workload: A NeuroIS Perspective , 2017 .