skip to main content
article

A feedback-controlled interface for treadmill locomotion in virtual environments

Authors Info & Claims
Published:01 January 2007Publication History
Skip Abstract Section

Abstract

Virtual environments (VEs) allow safe, repeatable, and controlled evaluations of obstacle avoidance and navigation performance of people with visual impairments using visual aids. Proper simulation of mobility in a VE requires an interface, which allows subjects to set their walking pace. Using conventional treadmills, the subject can change their walking speed by pushing the tread with their feet, while leveraging handrails or ropes (self-propelled mode). We developed a feedback-controlled locomotion interface that allows the VE workstation to control the speed of the treadmill, based on the position of the user. The position and speed information is also used to implement automated safety measures, so that the treadmill can be halted in case of erratic behavior.

We compared the feedback-controlled to the self-propelled mode by using speed-matching tasks (follow a moving object or match the speed of an independently moving scene) to measure the efficacy of each mode in maintaining constant subject position, subject control of the treadmill, and subject pulse rates. In addition, we measured the perception of speed in the VE on each mode.

The feedback-controlled mode required less physical exertion than self-propelled. The average position of subjects on the feedback-controlled treadmill was always within a centimeter of the desired position. There was a smaller standard deviation in subject position when using the self-propelled mode than when using the feedback-controlled mode, but the difference averaged less than 6 cm across all subjects walking at a constant speed. Although all subjects underestimated the speed of an independently moving scene at higher speeds, their estimates were more accurate when using the feedback-controlled treadmill than the self-propelled.

References

  1. Apfelbaum, H., Pelah, A., and Peli, E. 2007. Heading assessment by “tunnel vision” patients and control subjects standing or walking in a virtual reality environment. ACM Transactions on Applied Perception 4, 1, Article 8, 1--16. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Bakdash, J. Z., Augustyn, J. S., and Proffitt, D. R. 2005. Effects of effort and reduced visual cue information on perceived walking speed (abstract). Journal of Vision 5, 8, 747a.Google ScholarGoogle ScholarCross RefCross Ref
  3. Banton, T., Stefanucci, J., Durgin, F. H., Fass, A. M., and Profitt, D. 2005. The perception of walking speed in virtual environments. Presence 14, 4, 394--406. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Barabas, J., Woods, R. L., Goldstein, R. B., and Peli, E. 2004a. Perception of collisions while walking in a virtual environment with simulated peripheral vision loss (abstract). Journal of Vision 4, 8, 806a.Google ScholarGoogle ScholarCross RefCross Ref
  5. Barabas, J., Goldstein, R., Apfelbaum, H., Woods, R. L., Giorgi, R., and Peli, E. 2004b. Tracking the line of primary gaze in a walking simulator: modeling and calibration. Behavior Research Methods, Instruments, & Computers 36, 4, 757--770.Google ScholarGoogle ScholarCross RefCross Ref
  6. Bardy, B. G., Warren, W. H., Jr., and Kay, B. A. 1999. The role of central and peripheral vision in postural control during walking. Percept. Psychophy 61, 7, 1356--1368.Google ScholarGoogle ScholarCross RefCross Ref
  7. Chaudhury, S., Eisinger, J. M., Hao, L., Hicks, J., Chivukula, R., and Turano, K. A. 2004. Visual illusion in virtual world alters women's target-directed walking. Expe. Brain Res. 159, 360--369.Google ScholarGoogle ScholarCross RefCross Ref
  8. Cutting, J. E., Vishton, P. M., and Braren, P. A. 1995. How we avoid collisions with stationary and moving obstacles. Psychol. Rev. 102, 4, 627--651.Google ScholarGoogle ScholarCross RefCross Ref
  9. Cutting, J. E., Readinger, W. O., and Wang, R. F. 2002. Walking, looking to the side, and taking curved paths. Percept Psychophys 64, 3, 415--425.Google ScholarGoogle ScholarCross RefCross Ref
  10. Darken, R. P., Cockayne, W. R., and Carmein, D. 1997. The Omni-Directional Treadmill: a locomotion device for virtual worlds. in User Interface Software and Technology '97, Banff, Canada. 213--221. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Distler, H. K., Pelah, A., Bell, A. G., and Thurrell, A. E. I. 1998. The perception of absolute speed during self-motion (abstract). Perception 27s, 139.Google ScholarGoogle Scholar
  12. Durgin, F. H., Gigone, K., and Scott, R. 2005a. Perception of visual speed while moving. J. Exp. Psychol. Hum Percept. Perform. 31, 339--353.Google ScholarGoogle ScholarCross RefCross Ref
  13. Durgin, F. H., Pelah, A., Fox, L. F., Lewis, J., Kane, R., and Walley, K. A. 2005b. Self-motion perception during locomotor recalibration: More than meets the eye. J. Exp. Psychol. Hum Percept. Perform. 31, 398--419.Google ScholarGoogle ScholarCross RefCross Ref
  14. Fajen, B. R. and Warren, W. H. 2003. Behavioral dynamics of steering, obstacle avoidance, and route selection. J. Exp. Psychol. Hum. Percept. Perform. 29, 2, 343--362.Google ScholarGoogle ScholarCross RefCross Ref
  15. Fajen, B. R. and Warren, W. H. 2004. Visual guidance of intercepting a moving target on foot. Perception 33, 689--715.Google ScholarGoogle ScholarCross RefCross Ref
  16. Foo, P., Warren, W. H., Duchon, A., and Tarr, M. J. 2005. Do humans integrate routes into a cognitive map? Map-versus landmark-based navigation of novel shortcuts. J. Exp. Psychol. Hum. Percept. Perform. 31, 2, 195--215.Google ScholarGoogle Scholar
  17. Gottlieb, D. D., Freeman, P., and Williams, M. 1992. Clinical research and statistical analysis of a visual field awareness system. J. Am. Optom. Assoc. 63, 8, 581--588.Google ScholarGoogle Scholar
  18. Harris, L. R., Jenkin, M., and Zikovitz, D. C. 2000. Visual and non-visual cues in the perception of linear self motion. Exp. Brain. Res. 2000, 135, 12--21.Google ScholarGoogle Scholar
  19. Hollerbach, J. M., Xu, Y., Christensen, R., and Jacobsen, S. C. 2000. Design specifications for the second generation Sarcos Treadport locomotion interface. In Haptics Symposium, Proc ASME Dynamic Systems and Control Division, Orlando, DSC-Vol. 69--72, 1293--1298.Google ScholarGoogle Scholar
  20. Iwata, H. 1999a. Locomotion interface for virtual environments. In Robotics Research: The 9th International Symposium, Snowbird, UT, Springer-Verlag, New York. 220--226.Google ScholarGoogle Scholar
  21. Iwata, H. 1999b. Walking about virtual environments on an infinite floor. In Proceedings IEEE Virtual Reality '99, Houston, TX. 286--293. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Knapp, C. H. and Carter, G. C. 1976. The generalized correlation method for estimation of time delay. IEEE Transactions on Acoustics, Speech and Signal Processing 24, 4, 320--327.Google ScholarGoogle ScholarCross RefCross Ref
  23. Li, L. and Warren, W. H. 2000. Perception of heading during rotation: sufficiency of dense motion parallax and reference objects. Vision Research 40, 28, 3873--3894.Google ScholarGoogle ScholarCross RefCross Ref
  24. Lichtenstein, L., Barabas, J., Woods, R. L., and Peli, E. 2006. Maintaining position and display perspective in a walking simulator while self-pacing on a treadmill. In SID International Symposium, San Francisco, CA. vol. 37. 295--298.Google ScholarGoogle Scholar
  25. Loomis, J. M. 1992. Presence and distal attribution: phenomenology, determinants, and assessment. In Human Vision, Visual Processing, and Digital Display III/Human Perception, Performance, and Presence in Virtual Environments, San Jose, CA, The International Society for Optical Engineering (SPIE), 1666. 590--595.Google ScholarGoogle Scholar
  26. Loomis, J. M. and Knapp, J. M. 2003. Visual perception of egocentric distance in real and virtual environments. In Virtual and Adaptive Environments, J. Hettinger, and M. W. Haas, Eds. Erlbaum, Hillsdale, NJ. 21--46.Google ScholarGoogle Scholar
  27. Loomis, J. M., Da Silva, J. A., Fujita, N., and Fukusima, S. S. 1992. Visual space perception and visually directed action. J. Exp. Psychol. Hum. Percept. Perform. 18, 4, 906--921.Google ScholarGoogle ScholarCross RefCross Ref
  28. Minetti, A. E., Boldrini, L., Brusamolin, L., Zamparo, P., and Mckee, T. 2003. A feedback-controlled treadmill (treadmill-on-demand) and the spontaneous speed of walking and running in humans. Journal of Applied Physiology 95, 2, 838--843.Google ScholarGoogle ScholarCross RefCross Ref
  29. Moore, D. S. and Mccabe, G. P. 1999. Introduction to the Practice of Statistics. Freeman, San Francisco, CA.Google ScholarGoogle Scholar
  30. Murray, M. P., Spurr, G. B., Sepic, S. B., Gardner, G. M., and Mollinger, L. A. 1985. Treadmill vs. floor walking: kinematics, electromyogram, and heart rate. J. Appl. Physiol. 59, 1, 87--91.Google ScholarGoogle ScholarCross RefCross Ref
  31. Nise, N. S. 2004. Control Systems Engineering. Wiley, New York. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Peli, E. 2000a. Field expansion for homonymous hemianopia by optically-induced peripheral exotropia. Optometry and Visual Science 77, 9, 453--464.Google ScholarGoogle ScholarCross RefCross Ref
  33. Peli, E. 2000b. Augmented vision for central scotoma and peripheral field loss. In C., Stuen, A., Arditi, A., Horowitz, M. A., Lang, B., Rosenthal, and K. Seidman, Eds. Vision Rehabilitation: Assessment, Intervention and Outcomes. Swets & Zeitlinger, Lisse. 70--74.Google ScholarGoogle Scholar
  34. Proffitt, D. R., Stefanucci, J., Banton, T., and Epstein, W. 2003. The role of effort in perceiving distance. Psychol. Sci. 14, 2, 106--112.Google ScholarGoogle ScholarCross RefCross Ref
  35. Prokop, T., Schubert, M., and Berger, W. 1997. Visual influence on human locomotion. Exp. Brain. Res. 1997, 114, 63--70.Google ScholarGoogle Scholar
  36. Rizzo, M., Fisher, D., Andersen, J., and Van Winsum, W. 2005. CARSS Coordinated Assessment of Roadway Simulator Scenarios, Simulator Users Group, Division of Neuroergonomics, Department of Neurology, University of Iowa, Retrieved August 31, 2006 from http://www.uiowa.edu/~neuroerg/Simulator%20Users%20Group/carss%20scenarios%205%2018%2005.pdf.Google ScholarGoogle Scholar
  37. Schubert, M., Prokop, T., Brocke, F., and Berger, W. 2005. Visual kinesthesia and locomotion in Parkinson's Disease. Movement Disorders 20, 2, 141--150.Google ScholarGoogle ScholarCross RefCross Ref
  38. Soong, G. P., Lovie-Kitchin, J. E., and Brown, B. 2004. Measurements of preferred walking speed in subjects with central and peripheral vision loss. Ophthal. Physiol. Opt. 24, 291--295.Google ScholarGoogle ScholarCross RefCross Ref
  39. Thurrell, A. E. I., Pelah, A., and Distler, H. K. 1998. The influence of non-visual signals of walking on the perceived speed of optic flow (abstract). Perception 27s, 147.Google ScholarGoogle Scholar
  40. Wann, J. P., Swapp, D., and Rushton, S. K. 2000. Heading perception and the allocation of attention. Vision Research 40, 2533--2543.Google ScholarGoogle ScholarCross RefCross Ref
  41. Wells, M., Peterson, B., and Aten, J. 1996. The virtual motion controller: a sufficient-motion walking simulator. In Virtual Reality Annual International Symposium (IEEE '97), Albuquerque, NM. 1--8.Google ScholarGoogle Scholar
  42. Willemsen, P. and Gooch, A. A. 2002. An experimental comparison of perceived egocentric distance in real, image-based, and traditional virtual environments using direct walking tasks. In Proceedings of the IEEE Virtual Reality 2002 (VR '02). 1--6. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Witmer, B. G. and Kline, P. B. 1998. Judging perceived and traversed distance in virtual environments. Presence 7, 2, 144--167. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Woods, R., Shieh, J., Bobrow, L., Vora, A., Barabas, J., Goldstein, R., and Peli, E. 2003. Perceived collision with an obstacle in a virtual environment (abstract). Association for Research in Vision and Ophthalmology (ARVO CD). Item 4321Google ScholarGoogle Scholar
  45. Woods, R. L., Mandel, A. J., Barabas, J., Goldstein, R. B., and Peli, E. 2005. Making virtual reality more real and the perception of potential collisions (abstract). Journal of Vision 4, 8, 814--814.Google ScholarGoogle ScholarCross RefCross Ref
  46. Woodway. 2004. Woodway USA Treadmill Control Protocol (RS-232 Protocol, RS-232 port on the Display Board), Waukesha.Google ScholarGoogle Scholar

Index Terms

  1. A feedback-controlled interface for treadmill locomotion in virtual environments

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in

        Full Access

        • Published in

          cover image ACM Transactions on Applied Perception
          ACM Transactions on Applied Perception  Volume 4, Issue 1
          January 2007
          129 pages
          ISSN:1544-3558
          EISSN:1544-3965
          DOI:10.1145/1227134
          Issue’s Table of Contents

          Copyright © 2007 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 1 January 2007
          Published in tap Volume 4, Issue 1

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • article

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader