Modeling the Effect of Force Feedback for 3D Steering Tasks

Path steering is an interaction task of how quickly one may navigate through a path. The steering law, proposed by Accot and Zhai [AZ97], is a predictive model which describes the time to accomplish a 2D steering task as a function of the path length and width. In this paper, we study a 3D steering task in the presence of force feedback. Our goal is to extend the application of the steering law in such a task and find out, if possible, additional predictors for users' temporal performance. In particular, we quantitatively examine how the amount of force feedback influences the movement time. We have carried out a repeated-measures-design experiment with varying path length, width and force magnitude. The results indicate that the movement time can be successfully modeled by path length, width and force magnitude. The relationship evidences that the efficiency of the tasks can be improved once an appropriate force magnitude is applied. Additionally, we have compared the capacity of our model to the steering law. According to Akaike Information Criterion (AIC), our model provides a better description for the movement time when the force magnitude can vary. The new model can be utilized as a guideline for designing the experiments with a haptic device.

[1]  Daniel Vogel,et al.  The Impact of Control-Display Gain on User Performance in Pointing Tasks , 2008, Hum. Comput. Interact..

[2]  Shumin Zhai,et al.  Beyond Fitts' law: models for trajectory-based HCI tasks , 1997, CHI Extended Abstracts.

[3]  Nariman Sepehri,et al.  Evaluating Factors that Influence Path Tracing with Passive Haptic Guidance , 2009, HAID.

[4]  David Ahlström,et al.  Modeling and improving selection in cascading pull-down menus using Fitts' law, the steering law and force fields , 2005, CHI.

[5]  Lei Liu,et al.  Revisiting path steering for 3D manipulation tasks , 2011, Int. J. Hum. Comput. Stud..

[6]  Yoshifumi Kitamura,et al.  Steering Law in an Environment of Spatially Coupled Style with Matters of Pointer Size and Trajectory Width , 2004, APCHI.

[7]  Patrick Baudisch,et al.  Hover widgets: using the tracking state to extend the capabilities of pen-operated devices , 2006, CHI.

[8]  P. Fitts.  The information capacity of the human motor system in controlling the amplitude of movement. , 1954, Journal of experimental psychology.

[9]  Wijnand A. IJsselsteijn,et al.  The Form of Augmented Force-Feedback Fields and the Efficiency and Satisfaction in Computer-Aided Pointing Tasks , 2005, Hum. Factors.

[10]  Xing-Dong Yang,et al.  A Model for Steering with Haptic-Force Guidance , 2009, INTERACT.

[11]  Clifford M. Hurvich,et al.  Regression and time series model selection in small samples , 1989 .

[12]  Jack Tigh Dennerlein,et al.  Force-feedback improves performance for steering and combined steering-targeting tasks , 2000, CHI.

[13]  Robert Pastel,et al.  Measuring the difficulty of steering through corners , 2006, CHI.

[14]  David H. Laidlaw,et al.  Interactive 3d drawing for free-form modeling in scientific visualization and art: tools, methodologies, and theoretical foundations , 2007 .

[15]  Sriram Subramanian,et al.  Modeling steering within above-the-surface interaction layers , 2007, CHI.

[16]  Maria C. Yang,et al.  Haptic Force-Feedback Devices for the Office Computer: Performance and Musculoskeletal Loading Issues , 2001, Hum. Factors.

[17]  Mindy F. Levin,et al.  Effect of Tactile Feedback on Movement Speed and Precision During Work-Related Tasks Using a Computer Mouse , 2005, Hum. Factors.

[18]  Shumin Zhai,et al.  Human Action Laws in Electronic Virtual Worlds: An Empirical Study of Path Steering Performance in VR , 2004, Presence: Teleoperators & Virtual Environments.