Robust Multimodal Cognitive Load Measurement

This book explores robust multimodal cognitive load measurement with physiological and behavioural modalities, which involve the eye, Galvanic Skin Response, speech, language, pen input, mouse movement and multimodality fusions. Factors including stress, trust, and environmental factors such as illumination are discussed regarding their implications for cognitive load measurement. Furthermore, dynamic workload adjustment and real-time cognitive load measurement with data streaming are presented in order to make cognitive load measurement accessible by more widespread applications and users. Finally, application examples are reviewed demonstrating the feasibility of multimodal cognitive load measurement in practical applications. This is the first book of its kind to systematically introduce various computational methods for automatic and real-time cognitive load measurement and by doing so moves the practical application of cognitive load measurement from the domain of the computer scientist and psychologist to more general end-users, ready for widespread implementation. Robust Multimodal Cognitive Load Measurement is intended for researchers and practitioners involved with cognitive load studies and communities within the computer, cognitive, and social sciences. The book will especially benefit researchers in areas like behaviour analysis, social analytics, human-computer interaction (HCI), intelligent information processing, and decision support systems.

[1]  F. Paas,et al.  Cognitive Architecture and Instructional Design , 1998 .

[2]  Fang Chen,et al.  Analysis of Collaborative Communication for Linguistic Cues of Cognitive Load , 2012, Hum. Factors.

[3]  R. Flesch.  A new readability yardstick. , 1948, The Journal of applied psychology.

[4]  Robert F. Stanners,et al.  The pupillary response as an indicator of arousal and cognition , 1979 .

[5]  Joost Schilperoord,et al.  On the Cognitive Status of Pauses in Discourse Production , 2002 .

[6]  Siyuan Chen,et al.  Eye activity as a measure of human mental effort in HCI , 2011, IUI '11.

[7]  Fang Chen,et al.  Pupillary Response Based Cognitive Workload Measurement under Luminance Changes , 2011, INTERACT.

[8]  Yang Wang,et al.  Indexing cognitive workload based on pupillary response under luminance and emotional changes , 2013, IUI '13.

[9]  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.

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

[11]  Matti Airas,et al.  TKK Aparat: An environment for voice inverse filtering and parameterization , 2008, Logopedics, phoniatrics, vocology.

[12]  Fang Chen,et al.  Trust and cognitive load in the text-chat environment: the role of mouse movement , 2014, OZCHI.

[13]  Joost Schilperoord,et al.  It's about time: Temporal aspects of cognitive processes in text production , 1996 .

[14]  Siyuan Chen,et al.  Pupillary response based cognitive workload index under luminance and emotional changes , 2011, CHI Extended Abstracts.

[15]  John K. Butler.  Toward Understanding and Measuring Conditions of Trust: Evolution of a Conditions of Trust Inventory , 1991 .

[16]  Sridha Sridharan,et al.  Feature warping for robust speaker verification , 2001, Odyssey.

[17]  Hans W. Dechert,et al.  Towards a cross-linguistic assessment of speech production , 1980 .

[18]  Pat Hanrahan,et al.  Measuring the task-evoked pupillary response with a remote eye tracker , 2008, ETRA.

[19]  A. Kramer,et al.  Physiological metrics of mental workload: A review of recent progress , 1990, Multiple-task performance.

[20]  Andrew L. Kun,et al.  Utilizing Pupil Diameter to Estimate Cognitive Load Changes During Human Dialogue : A Preliminary Study , 2011 .

[21]  Charles K. Chui,et al.  An Introduction to Wavelets , 1992 .

[22]  Cindy K. Chung,et al.  The development and psychometric properties of LIWC2007 , 2007 .

[23]  Andrew L. Kun,et al.  Estimating cognitive load using remote eye tracking in a driving simulator , 2010, ETRA.

[24]  Fang Chen,et al.  Using language complexity to measure cognitive load for adaptive interaction design , 2010, IUI '10.

[25]  Shun'ichi Tano,et al.  Information presentation based on estimation of human multimodal cognitive load , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[26]  Yoav Freund,et al.  Boosting a weak learning algorithm by majority , 1990, COLT '90.

[27]  M. Pomplun,et al.  Pupil Dilation as an Indicator of Cognitive Workload in Human-Computer Interaction , 2003 .

[28]  Robert E. Schlegel,et al.  Operator Functional State Assessment , 2004 .

[29]  Fang Chen,et al.  Galvanic skin response (GSR) as an index of cognitive load , 2007, CHI Extended Abstracts.