The Effect of Embodied Interaction in Visual-Spatial Navigation

This article aims to assess the effect of embodied interaction on attention during the process of solving spatio-visual navigation problems. It presents a method that links operator's physical interaction, feedback, and attention. Attention is inferred through networks called Bayesian Attentional Networks (BANs). BANs are structures that describe cause-effect relationship between attention and physical action. Then, a utility function is used to determine the best combination of interaction modalities and feedback. Experiments involving five physical interaction modalities (vision-based gesture interaction, glove-based gesture interaction, speech, feet, and body stance) and two feedback modalities (visual and sound) are described. The main findings are: (i) physical expressions have an effect in the quality of the solutions to spatial navigation problems; (ii) the combination of feet gestures with visual feedback provides the best task performance.

[1]  Galina B. Bolden Streeck, Goodwin & LeBaron (eds.), Embodied interaction: Language and body in the material world . Cambridge: Cambridge University Press, 2011. Pp. xii, 308. Hb. $99. , 2012, Language in Society.

[2]  Rolf Pfeifer,et al.  How the Body Shapes the Way We Think: A New View of Intelligence (Bradford Books) , 2006 .

[3]  Paul Dourish,et al.  Where the action is , 2001 .

[4]  Josef F. Krems,et al.  Situation Awareness and Secondary Task Performance While Driving , 2007, HCI.

[5]  P. Venkataraman,et al.  Applied Optimization with MATLAB Programming , 2001 .

[6]  V. Barnett,et al.  Applied Linear Statistical Models , 1975 .

[7]  J. Jaffray Linear utility theory for belief functions , 1989 .

[8]  Luis M. de Campos,et al.  A Scoring Function for Learning Bayesian Networks based on Mutual Information and Conditional Independence Tests , 2006, J. Mach. Learn. Res..

[9]  Robert A. Wilson,et al.  Embodied cognition. , 2013, Wiley interdisciplinary reviews. Cognitive science.

[10]  M. Lee,et al.  The aesthetic appeal of minimal structures: Judging the attractiveness of solutions to traveling salesperson problems , 2006, Perception & psychophysics.

[11]  S. Kita,et al.  The nature of gestures ' beneficial role in spatial problem solving , 2013 .

[12]  Autumn B. Hostetter,et al.  Visible embodiment: Gestures as simulated action , 2008, Psychonomic bulletin & review.

[13]  Kara A. Latorella,et al.  The Scope and Importance of Human Interruption in Human-Computer Interaction Design , 2002, Hum. Comput. Interact..

[14]  Juan P. Wachs,et al.  A Bayesian Approach to Determine Focus of Attention in Spatial and Time-Sensitive Decision Making Scenarios , 2014, AAAI 2014.

[15]  Risto Lahdelma,et al.  Pseudo-criteria versus linear utility function in stochastic multi-criteria acceptability analysis , 2002, Eur. J. Oper. Res..

[16]  J. B. Black An Embodied/Grounded Cognition Perspective on Educational Technology , 2010 .

[17]  M. Sheelagh T. Carpendale,et al.  Beyond Mouse and Keyboard: Expanding Design Considerations for Information Visualization Interactions , 2012, IEEE Transactions on Visualization and Computer Graphics.

[18]  Mica R. Endsley,et al.  Measurement of Situation Awareness in Dynamic Systems , 1995, Hum. Factors.

[19]  Rolf Pfeifer,et al.  How the body shapes the way we think - a new view on intelligence , 2006 .

[20]  Juan Pablo Wachs,et al.  Linking attention to physical action in complex decision making problems , 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[21]  Margaret Wilson,et al.  Six views of embodied cognition , 2002, Psychonomic bulletin & review.

[22]  R. J. Seitz,et al.  A fronto‐parietal circuit for object manipulation in man: evidence from an fMRI‐study , 1999, The European journal of neuroscience.

[23]  Mandy Ryan,et al.  Specification of the utility function in discrete choice experiments. , 2014, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[24]  Sabine U. König,et al.  Embodied cognition , 2018, 2018 6th International Conference on Brain-Computer Interface (BCI).

[25]  Eric Horvitz,et al.  Attention-Sensitive Alerting , 1999, UAI.

[26]  Andrew P. Robinson,et al.  Model validation using equivalence tests , 2004 .

[27]  R. Proctor,et al.  Attention: Theory and Practice , 2003 .

[28]  Changhe Yuan,et al.  Empirical evaluation of scoring functions for Bayesian network model selection , 2012, BMC Bioinformatics.

[29]  H. Pashler,et al.  The Psychology of Attention , 2000 .

[30]  Julie Thomas,et al.  Attention aware systems: Theories, applications, and research agenda , 2006, Comput. Hum. Behav..

[31]  Roel Vertegaal,et al.  Attentive User Interfaces , 2003 .

[32]  Joseph S. Valacich,et al.  The Effects of Interruptions, Task Complexity, and Information Presentation on Computer-Supported Decision-Making Performance , 2003, Decis. Sci..

[33]  Sheikh Iqbal Ahamed,et al.  A Mobile Intelligent Interruption Management System , 2010, J. Univers. Comput. Sci..

[34]  Larry Ambrose,et al.  The power of feedback. , 2002, Healthcare executive.

[35]  C. L. M. The Psychology of Attention , 1890, Nature.

[36]  Scott R. Klemmer,et al.  How bodies matter: five themes for interaction design , 2006, DIS '06.

[37]  Johannes Schöning,et al.  Using hands and feet to navigate and manipulate spatial data , 2009, CHI Extended Abstracts.

[38]  Mica R. Endsley,et al.  Toward a Theory of Situation Awareness in Dynamic Systems , 1995, Hum. Factors.

[39]  Yvonne Rogers,et al.  Introduction to the special issue on the theory and practice of embodied interaction in HCI and interaction design , 2013, TCHI.

[40]  Lawrence A. Shapiro Embodied Cognition , 2010 .

[41]  Gregory R. Grant,et al.  Bioinformatics - The Machine Learning Approach , 2000, Comput. Chem..

[42]  Caroline Hummels,et al.  Move to get moved: a search for methods, tools and knowledge to design for expressive and rich movement-based interaction , 2007, Personal and Ubiquitous Computing.

[43]  Nir Friedman,et al.  Learning Belief Networks in the Presence of Missing Values and Hidden Variables , 1997, ICML.

[44]  Johannes Schöning,et al.  Whole Body Interaction with Geospatial Data , 2009, Smart Graphics.

[45]  H. Sakata,et al.  Parietal control of hand action , 1994, Current Opinion in Neurobiology.

[46]  G. Lakoff,et al.  Where mathematics comes from : how the embodied mind brings mathematics into being , 2002 .

[47]  Angelo Cangelosi,et al.  ACM Transactions on Interactive Intelligent Systems (TiiS) Special Issue on Trust and Influence in Intelligent Human-Machine Interaction , 2018, ACM Trans. Interact. Intell. Syst..

[48]  Eric Horvitz,et al.  Models of attention in computing and communication , 2003, Commun. ACM.

[49]  S P Tipper,et al.  Action-based mechanisms of attention. , 1998, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[50]  L. Barsalou Grounded cognition. , 2008, Annual review of psychology.

[51]  Andrew D. Wilson,et al.  Embodied Cognition is Not What you Think it is , 2013, Front. Psychology.

[52]  Charles Goodwin,et al.  Embodied Interaction: Language And Body In The Material World , 2014 .

[53]  Michael H. Kutner Applied Linear Statistical Models , 1974 .

[54]  J. Rissanen A UNIVERSAL PRIOR FOR INTEGERS AND ESTIMATION BY MINIMUM DESCRIPTION LENGTH , 1983 .

[55]  David R. Karger,et al.  Approximation algorithms for orienteering and discounted-reward TSP , 2003, 44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings..

[56]  M. Buchholz Review: George Lakoff & Rafael E. Núnez (2000). Where Mathematics Comes From—How the Embodied Mind brings Mathematics into Being , 2002 .

[57]  Pedro Larrañaga,et al.  Structure Learning of Bayesian Networks by Genetic Algorithms: A Performance Analysis of Control Parameters , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[58]  Eric Horvitz,et al.  Learning and reasoning about interruption , 2003, ICMI '03.

[59]  Catherine L Reed,et al.  Implied body action directs spatial attention , 2010, Attention, perception & psychophysics.

[60]  Matthew Rizzo,et al.  Spatial attention: normal processes and their breakdown. , 2003, Neurologic clinics.

[61]  Richard E. Neapolitan,et al.  Learning Bayesian networks , 2007, KDD '07.

[62]  Daniel Zelterman,et al.  Bayesian Artificial Intelligence , 2005, Technometrics.

[63]  Eric Horvitz,et al.  Coordinates: Probabilistic Forecasting of Presence and Availability , 2002, UAI.

[64]  Pierre Baldi,et al.  A Bayesian framework for the analysis of microarray expression data: regularized t -test and statistical inferences of gene changes , 2001, Bioinform..

[65]  Jami J. Shah,et al.  A Normative DFM Framework Based on Benefit-Cost Analysis , 2002 .

[66]  G. Rizzolatti,et al.  Congruent Embodied Representations for Visually Presented Actions and Linguistic Phrases Describing Actions , 2006, Current Biology.

[67]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[68]  G. Lakoff,et al.  Metaphors We Live by , 1982 .

[69]  Firat Soylu,et al.  Mathematical Cognition as Embodied Simulation , 2011, CogSci.

[70]  Ludwig Weschke,et al.  Pushing Towards Embodied Interactions , 2010 .

[71]  A. Segal,et al.  Do Gestural Interfaces Promote Thinking? Embodied Interaction: Congruent Gestures and Direct Touch Promote Performance in Math , 2011 .