Enabling Unconstrained Omnidirectional Walking Through Virtual Environments: An Overview of the CyberWalk Project

  • Ilja Frissen
  • Jennifer L. Campos
  • Manish Sreenivasa
  • Marc O. Ernst
Chapter

Abstract

The CyberWalk treadmill is the first truly omnidirectional treadmill of its size that allows for near natural walking through arbitrarily large Virtual Environments. The platform represents advances in treadmill and virtual reality technology and engineering, but it is also a major step towards having a single setup that allows the study of human locomotion and its many facets. This chapter focuses on the human behavioral research that was conducted to understand human locomotion from the perspective of specifying design criteria for the CyberWalk. The first part of this chapter describes research on the biomechanics of human walking, in particular, the nature of natural unconstrained walking and the effects of treadmill walking on characteristics of gait. The second part of this chapter describes the multisensory nature of walking, with a focus on the integration of vestibular and proprioceptive information during walking. The third part of this chapter describes research on large-scale human navigation and identifies possible causes for the human tendency to veer from a straight path, and even walk in circles when no external references are made available. The chapter concludes with a summary description of the features of the CyberWalk platform that were informed by this collection of research findings and briefly highlights the current and future scientific potential for this platform.

Keywords

Human locomotion Omnidirectional treadmill Gait Biomechanics Multisensory integration Navigation Cognition 

References

  1. 1.
    Aggarwal JK, Cai Q (1999) Human motion analysis: a review. Comp Vis Image Underst 73(3):428–440CrossRefGoogle Scholar
  2. 2.
    Alais D, Burr D (2004) The ventriloquist effect results from near-optimal bimodal integration. Curr Biol 14(3):257–262Google Scholar
  3. 3.
    Alton F, Baldey L, Caplan S, Morrissey MC (1998) A kinematic comparison of overground and treadmill walking. Clin Biomech 13(6):434–440CrossRefGoogle Scholar
  4. 4.
    Battaglia PW, Jacobs RA, Aslin RN (2003) Bayesian integration of visual and auditory signals for spatial localization. J Opt Soc Am A 20(7):1391–1397CrossRefGoogle Scholar
  5. 5.
    Becker W, Nasios G, Raab S, Jürgens R (2002) Fusion of vestibular and podokinesthetic information during self-turning towards instructed targets. Exp Brain Res 144(4):458–474CrossRefGoogle Scholar
  6. 6.
    Bent LR, Inglis JT, McFadyen BJ (2004) When is vestibular information important during walking? J Neurophysiol 92(3):1269–1275CrossRefGoogle Scholar
  7. 7.
    Berthoz A, Israël I, Georges-François P, Grasso R, Tsuzuku T (1995) Spatial memory of body linear displacement: what is being stored? Science 269(5220):95–98CrossRefGoogle Scholar
  8. 8.
    Bles W (1981) Stepping around: circular vection and coriolis effects. In: Long J, Baddeley A (eds) Attention and performance IX. Lawrence Erlbaum, Hillsdale, NJGoogle Scholar
  9. 9.
    Bles W, Kapteyn TS (1977) Circular vection and human posture: I. Does the proprioceptive system play a role? Aggressologie 18(6): 325–328.Google Scholar
  10. 10.
    Bles W, de Wit G (1978) La sensation de rotation et la marche circulaire (Sensation of rotation and circular walking). Aggressologie 19(A): 29–30Google Scholar
  11. 11.
    Breniere Y, Do MC (1986) When and how does steady state gait movement induced from upright posture begin? J Biomech 19(12):1035–1040CrossRefGoogle Scholar
  12. 12.
    Bresciani J-P, Dammeier F, Ernst MO (2006) Vision and touch are automatically integrated for the perception of sequences of events. J Vis 6(5):554–564CrossRefGoogle Scholar
  13. 13.
    Bril B, Ledebt A (1998) Head coordination as a means to assist sensory integration in learning to walk. Neurosci Biobehav Rev 22(4):555–563CrossRefGoogle Scholar
  14. 14.
    Bruggeman H, Piuneu VS, Rieser JJ, Pick HL Jr (2009) Biomechanical versus inertial information: stable individual differences in perception of self-rotation. J Exp Psychol: Hum Percept Perform 35(5):1472–1480CrossRefGoogle Scholar
  15. 15.
    Bülthoff HH, Mallot HA (1988) Integration of depth modules: stereo and shading. J Opt Soc Am 5(10):1749–1758CrossRefGoogle Scholar
  16. 16.
    Bülthoff HH, van Veen HJ (2001) Vision and action in virtual environments: Modern psychophysics. In: Jenkin ML and Harris L (eds.), Spatial cognition research. Vision and attention, 233–252. Springer Verlag, New York.Google Scholar
  17. 17.
    Bülthoff HH, Yuille A (1991) Bayesian models for seeing shapes and depth. Comments on Theor Biol 2(4):283–314Google Scholar
  18. 18.
    Butler JS, Smith ST, Campos JL, Bülthoff HH (2010) Bayesian integration of visual and vestibular signals for heading. J Vis 10(11):Article 23Google Scholar
  19. 19.
    Butler JS, Campos JL, Bülthoff HH, Smith ST (2011) The role of stereo vision in visual-vestibular integration. Seeing Perceiving 24(5):453–470CrossRefGoogle Scholar
  20. 20.
    Calvert GA, Spence C, Stein BE (2004) The handbook of multisensory processes. MIT Press, BostonGoogle Scholar
  21. 21.
    Campos JL, Butler JS, Bülthoff HH (2012) Multisensory integration in the estimation of walked distance. Exp Brain Res 218(4):551–565Google Scholar
  22. 22.
    Campos JL, Siegle J, Mohler BJ, Loomis JM, Bülthoff HH (2009) Imagined self-motion differs from perceived self-motion: Evidence from a novel continuous pointing method. PLoS ONE 4(11):e7793. doi:10.1371/journal.pone.0007793
  23. 23.
    Campos JL, Byrne P, Sun H-J (2010) The brain weights body-based cues higher than vision when estimating walked distances. Eur J Neurosci 31(10):1889–1898Google Scholar
  24. 24.
    Campos JL, Bülthoff HH (2011) Multisensory Integration during self-motion in virtual reality. In: Wallace M, Murray M (eds) Frontiers in the Neural Bases of Multisensory Processes. Taylor and Francis Group, LondonGoogle Scholar
  25. 25.
    Cheng K, Shettleworth SJ, Huttenlocher J, Rieser JJ (2007) Bayesian integration of spatial information. Psychol Bull 133(4):625–637CrossRefGoogle Scholar
  26. 26.
    Cooper AR, Page AS, Wheeler BW, Griew P, Davis L, Hillsdon M, Jago R (2010) Mapping the walk to school using accelerometry combined with a global positioning system. Am J Prev Med 38(2):178–183CrossRefGoogle Scholar
  27. 27.
    Courtine G, Schieppati M (2003) Human walking along a curved path. I. Body trajectory, segment orientation and the effect of vision. Eur J Neurosci 18(3):177–190CrossRefGoogle Scholar
  28. 28.
    Cutting JE, Readinger WO, Wang RF (2002) Walking, looking to the side, and taking curved paths. Percept Psychophys 64(3):415–425Google Scholar
  29. 29.
    De Luca A, Mattone R, Robuffo Giordano P, Bülthoff HH (2009) Control design and experimental evaluation of the 2D CyberWalk platform. IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, pp 5051–5058Google Scholar
  30. 30.
    Dingwell JB, Cusumano JP, Cavanagh PR, Sternad D (2001) Local dynamic stability versus kinematic variability of continuous overground and treadmill walking. J Biomech Eng 123(1):27–32CrossRefGoogle Scholar
  31. 31.
    Dufek JS, Mercer JA, Griffin JR (2009) The effects of speed and surface compliance on shock attenuation characteristics for male and female runners. J Appl Biomech 25(3):219–228Google Scholar
  32. 32.
    Duncan MJ, Mummery WK, Dascombe BJ (2007) Utility of global positioning system to measure active transport in urban areas. Med Sci Sports Exerc 39(10):1851–1857CrossRefGoogle Scholar
  33. 33.
    Eils E, Nolte S, Tewes M, Thorwesten L, Völker K, Rosenbaum D (2002) Modified pressure distribution patterns in walking following reduction of plantar sensation. J Biomech 35(10):1307–1313CrossRefGoogle Scholar
  34. 34.
    Elliott D (1986) Continuous visual information may be important after all: A failure to replicate Thomson. J Exp Psychol: Human Percept Perform 12(3):388–391Google Scholar
  35. 35.
    Ernst MO (2006) A Bayesian view on multimodal cue integration. In: Knoblich G, Thornton IM, Grosjean M, Shiffrar M (eds) Perception of the human body from the inside out. Oxford University Press, New York, USA, pp 105–131Google Scholar
  36. 36.
    Ernst MO, Banks MS (2002) Humans integrate visual and haptic information in a statistically optimal fashion. Nature 415(6870):429–433CrossRefGoogle Scholar
  37. 37.
    Ernst MO, Bülthoff HH (2004) Merging the senses into a robust percept. Trends Cogn Sci 8(4):162–169CrossRefGoogle Scholar
  38. 38.
    Faisal A, Selen LPJ, Wolpert DM (2008) Noise in the nervous system. Nat Rev Neurosci 9(4):292–303CrossRefGoogle Scholar
  39. 39.
    Fetsch CR, Turner AH, DeAngelis GC, Angelaki DE (2009) Dynamic reweighting of visual and vestibular cues during self-motion perception. J Neurosci 29(49):15601–15612CrossRefGoogle Scholar
  40. 40.
    Fetsch CR, DeAngelis GC, Angelaki DE (2010) Visual-vestibular cue integration for heading perception: applications of optimal cue integration theory. Eur J Neurosci 31(10):1721–1729CrossRefGoogle Scholar
  41. 41.
    Finnis KK, Walton D (2008) Field observations to determine the influence of population size, location, and individual factors on pedestrian walking speeds. Ergonomics 51(6):827–842CrossRefGoogle Scholar
  42. 42.
    Frissen I, Campos JL, Souman JL, Ernst MO (2011) Integration of vestibular and proprioceptive signals for spatial updating. Exp Brain Res 212(2):163–176CrossRefGoogle Scholar
  43. 43.
    Fukusima SS, Loomis JM, Da Silva JA (1997) Visual perception of egocentric distance as assessed by triangulation. J Exp Psychol: Human Percept Perform 23(1):86–100Google Scholar
  44. 44.
    Fung J, Malouin F, McFadyen BJ, Comeau F, Lamontagne A, Chapdelaine S, Beaudoin C, Laurendeau D, Hugheyh L, Richards CL (2004) Locomotor rehabilitation in a complex virtual environment. Proceedings of the 36th annual international conference of the IEEE-EMBS, San Francisco, Sept 1–5, pp 4859–4862Google Scholar
  45. 45.
    Gescheider GA (1997) Psychophysics: The fundamentals, 3rd edn. Lawrence Erlbaum, Mahwah, NJGoogle Scholar
  46. 46.
    Gibson JJ (1950) Perception of the visual world. Houghton Mifflin, BostonGoogle Scholar
  47. 47.
    Grasso R, Glasauer S, Takei Y, Berthoz A (1996) The predictive brain: anticipatory control of head direction for the steering of control. NeuroReport 7(6):1170–1174Google Scholar
  48. 48.
    Grieve DW, Gear RJ (1966) The relationships between length of stride, step frequency, time of swing and speed of walking for children and adults. Ergonomics 9(5):379–399CrossRefGoogle Scholar
  49. 49.
    Gu Y, Angelaki DE, DeAngelis GC (2008) Neural correlates of multisensory cue integration in macaque MSTd. Nat Neurosci 11(10):1201–1210CrossRefGoogle Scholar
  50. 50.
    Hallemans A, Ortibus E, Meire F, Aerts P (2010) Low vision affects dynamic stability of gait. Gait Posture 32(4):547–551CrossRefGoogle Scholar
  51. 51.
    Harris LR, Jenkin M, Zikovitz DC (2000) Visual and non-visual cues in the perception of linear self-motion. Exp Brain Res 135(1):12–21CrossRefGoogle Scholar
  52. 52.
    Hicheur H, Vieilledent S, Berthoz A (2005a) Head motion in humans alternating between straight and curved walking path: Combination of stabilizing and anticipatory orienting mechanisms. Neurosci Lett 383(1–2):87–92CrossRefGoogle Scholar
  53. 53.
    Hicheur H, Vieilledent S, Richardson MJE, Flash T, Berthoz A (2005b) Velocity and curvature in human locomotion along complex curved paths: a comparison with hand movements. Exp Brain Res 162(2):145–154CrossRefGoogle Scholar
  54. 54.
    Hollands MA, Marple-Horvat DE (1996) Visually guided stepping under conditions of step cycle-related denial of visual information. Exp Brain Res 109(2):343–356CrossRefGoogle Scholar
  55. 55.
    Hölscher C, Büchner SJ, Meilinger T, Strube G (2009) Adaptivity of wayfinding strategies in a multi-building ensemble: The effects of spatial structure, task requirements, and metric information. J Environ Psychol 29(2):208–219CrossRefGoogle Scholar
  56. 56.
    Holt KG, Jeng SF, Ratcliffe R (1995) Energetic cost and stability during human walking at the preferred stride frequency. J Motor Behav 27(2):164–178CrossRefGoogle Scholar
  57. 57.
    Imai T, Moore ST, Raphan T, Cohen B (2001) Interaction of the body, head, and eyes during walking and turning. Exp Brain Res 136(1):1–18CrossRefGoogle Scholar
  58. 58.
    Israël I, Berthoz A (1989) Contributions of the otoliths to the calculation of linear displacement. J Neurophysiol 62(1):247–263Google Scholar
  59. 59.
    Jahn K, Kalla R, Karg S, Strupp M, Brandt T (2006) Eccentric eye and head positions in darkness induce deviation from the intended path. Exp Brain Res 174(1):152–157CrossRefGoogle Scholar
  60. 60.
    Jian Y, Winter DA, Ishac MG, Gilchrist L (1993) Trajectory of the body COG and COP during initiation and termination of gait. Gait Posture 1(1):9–22CrossRefGoogle Scholar
  61. 61.
    Jürgens R, Becker W (2006) Perception of angular displacement without landmarks: evidence for Bayesian fusion of vestibular, optokinetic, podokinesthetic and cognitive information. Exp Brain Res 174(3):528–543CrossRefGoogle Scholar
  62. 62.
    Kerrigan DC, Viramontes BE, Corcoran PJ, LaRaia PJ (1995) Measured versus predicted vertical displacement of the sacrum during gait as a tool to measure biomechanical gait performance. Am J Phys Med Rehabil 74(1):3–8CrossRefGoogle Scholar
  63. 63.
    Knill DC (2005) Reaching for visual cues to depth: The brain combines depth cues differently for motor control and perception. J Vis 5(2):103–115CrossRefGoogle Scholar
  64. 64.
    Knill DC, Richards W (1996) Perception as Bayesian Inference. Cambridge University Press, CambridgeMATHCrossRefGoogle Scholar
  65. 65.
    Knoblauch RL, Pietrucha MT, Nitzburg M (1996) Field studies of pedestrian walking speed and start-up time. Transp Res Record 1538:27–38CrossRefGoogle Scholar
  66. 66.
    Körding KP, Wolpert DM (2004) Bayesian integration in sensorimotor learning. Nature 427(6971):244–247CrossRefGoogle Scholar
  67. 67.
    Loomis JM, Da Silva JA, Fujita N, Fukusima SS (1992) Visual space perception and visually directed action. J Exp Psychol: Hum Percept Perform 18(4):906–921Google Scholar
  68. 68.
    Loomis JM, Blascovich JJ, Beall AC (1999) Immersive virtual environment technology as a basic research tool in psychology. Behav Res Methods Instrum Comp 31(4):557–564CrossRefGoogle Scholar
  69. 69.
    MacNeilage PR, Banks MS, Berger DR, Bülthoff HH (2007) A Bayesian model of the disambiguation of gravitoinertial force by visual cues. Exp Brain Res 179(2):263–290CrossRefGoogle Scholar
  70. 70.
    Maddison R, Mhurchu CN (2009). Global positioning system: a new opportunity in physical activity measurement. Int J Behav Nutr Phys Act 6:Article 73. doi:10.1186/1479-5868-6-73
  71. 71.
    Mann RA, Hagy JL, White V, Liddell D (1979) The initiation of gait. J Bone Jt Surg 61(2):232–239Google Scholar
  72. 72.
    Menz HB, Lord SR, Fitzpatrick RC (2003) Acceleration patterns of the head and pelvis when walking on level and irregular surfaces. Gait Posture 18(1):35–46CrossRefGoogle Scholar
  73. 73.
    Mittelstaedt ML, Mittelstaedt H (2001) Idiothetic navigation in humans: Estimation of path length. Exp Brain Res 139(3):318–332CrossRefGoogle Scholar
  74. 74.
    Mohler BJ, Campos JL, Weyel M, Bülthoff HH (2007) Gait parameters while walking in a head-mounted display virtual environment and the real world. 13th Eurographics symposium on virtual environments and 10th immersive projection technology workshop (IPT-EGVE 2007), Aire-la-Ville, Switzerland, 85–88Google Scholar
  75. 75.
    Murray MP, Spurr GB, Sepic SB, Gardner GM, Mollinger LA (1985) Treadmill versus floor walking: kinematics, electromyogram, and heart rate. J Appl Physiol 59(1):87–91Google Scholar
  76. 76.
    Oliver M, Badland H, Mavoa S, Duncan MJ, Duncan S (2010) Combining GPS, GIS, and accelerometry: Methodological issues in the assessment of location and intensity of travel behaviors. J Phys Act Health 7(1):102–108Google Scholar
  77. 77.
    Patla AE (1997) Understanding the roles of vision in the control of human locomotion. Gait Posture 5(1):54–69CrossRefGoogle Scholar
  78. 78.
    Pearce ME, Cunningham DA, Donner AP, Rechnitzer PA, Fullerton GM, Howard JH (1983) Energy cost of treadmill and floor walking at self-selected paces. Eur J Appl Physiol 52(1):115–119CrossRefGoogle Scholar
  79. 79.
    Pick HL, Wagner D, Rieser JJ, Garing AE (1999) The recalibration of rotational locomotion. J Exp Psychol: Hum Percept Perform 25(5):1179–1188Google Scholar
  80. 80.
    Pozzo T, Berthoz A, Lefort L (1989) Head kinematic during various motor tasks in humans. Prog Brain Res 80:377–383CrossRefGoogle Scholar
  81. 81.
    Prévost P, Ivanenko Y, Grasso R, Berthoz A (2002) Spatial invariance in anticipatory orienting behaviour during human navigation. Neurosci Lett 339(3):243–247CrossRefGoogle Scholar
  82. 82.
    Readinger WO, Chatziastros A, Cunningham DW, Bülthoff HH, Cutting JE (2002) Gaze-Eccentricity Effects on Road Position and Steering. J Exp Psychol: Appl 8(4):247–258CrossRefGoogle Scholar
  83. 83.
    Rieser JJ, Ashmead DH, Talor CR, Youngquist GA (1990) Visual perception and the guidance of locomotion without vision to previously seen targets. Perception 19(5):675–689CrossRefGoogle Scholar
  84. 84.
    Riley PO, Paolini G, Della Croce U, Paylo KW, Kerrigan DC (2007) A kinematic and kinetic comparison of overground and treadmill walking in healthy subjects. Gait Posture 26(1):17–24Google Scholar
  85. 85.
    Rodriguez DA, Brown AL, Troped PJ (2005) Portable global positioning units to complement accelerometry-based physical activity monitors. Med Sci Sports Exerc 37(11 Suppl):S572–S581Google Scholar
  86. 86.
    Schutz Y, Herren R (2000) Assessment of speed of human locomotion using a differential satellite global positioning system. Med Sci Sports Exerc 32(2):642–646Google Scholar
  87. 87.
    Schwaiger M, Thümmel T, Ulbrich H (2007a) Cyberwalk: An advanced prototype of a belt array platform. Proceedings of IEEE International Workshop on Haptic Audio Visual Environments and their Applications, Ottawa, CanadaGoogle Scholar
  88. 88.
    Schwaiger M, Thümmel T, Ulbrich H (2007b) Cyberwalk: Implementation of a ball bearing platform for humans. Proceedings of Conference on Human Computer Interaction, Beijing, ChinaGoogle Scholar
  89. 89.
    Schwaiger M, Thümmel T, Ulbrich H (2007c) A 2D-motion platform: the cybercarpet. Proceedings of world haptics conference 2007, pp 415–420 Tsukuba, JapanGoogle Scholar
  90. 90.
    Sekiya N, Nagasaki H, Ito H, Furuna T (1996) The invariant relationship between step length and step rate during free walking. J Hum Mov Stud 30(6):241–257Google Scholar
  91. 91.
    Sheik-Nainar MA, Kaber DB (2007) The utility of a Virtual Reality locomotion interface for studying gait behavior. Hum Factors 49(4):696–709CrossRefGoogle Scholar
  92. 92.
    Siegle J, Campos JL, Mohler BJ, Loomis JM, Bülthoff HH (2009) Measurement of instantaneous perceived self-motion using continuous pointing. Exp Brain Res 195(3):429–444CrossRefGoogle Scholar
  93. 93.
    Souman JL, Frissen I, Sreenivasa MN, Ernst MO (2009) Walking straight into circles. Curr Biol 19(18):1538–1542CrossRefGoogle Scholar
  94. 94.
    Souman JL, Robuffo Giordano P, Frissen I, De Luca A, Ernst MO (2010) Making virtual walking real: perceptual evaluation of a new treadmill control algorithm. ACM Trans Appl Percept 7(2):1–14 Article 11Google Scholar
  95. 95.
    Souman JL, Robuffo Giordano P, Schwaiger M, Frissen I, Thümmel T, Ulbrich H, De Luca A, Bülthoff HH, Ernst MO (2011) CyberWalk: enabling unconstrained omnidirectional walking through virtual environments. ACM Trans Appl Percept 8(4):Article 24.Google Scholar
  96. 96.
    Sparrow WA, Tirosh O (2005) Gait termination: a review of experimental methods and the effects of ageing and gait pathologies. Gait Posture 22(4):362–371CrossRefGoogle Scholar
  97. 97.
    Sreenivasa M (2007) Statistics of natural walking (Master’s thesis). Universität Duisberg-Essen, Duisberg, GermanyGoogle Scholar
  98. 98.
    Sreenivasa M, Frissen I, Souman J, Ernst MO (2008) Walking along curved paths of different angles: the relationship between head and trunk turning. Exp Brain Res 191(3):313–320CrossRefGoogle Scholar
  99. 99.
    Stoffregen TA, Pittenger JB (1995) Human echolocation as a basic form of perception and action. Ecol Psychol 7(3):181–216CrossRefGoogle Scholar
  100. 100.
    Stolze H, Kuhtz-Buschbeck JP, Mondwurf C, Boczek-Funcke A, Jöhnk K, Deuschl G, Illert M (1997) Gait analysis during treadmill and overground locomotion in children and adults. Electroencephalogr clin Neurophysiol 105(6):490–497CrossRefGoogle Scholar
  101. 101.
    Stopher P, FitzGerald C, Zhang J (2008) Search for a global positioning system device to measure person travel. Transp Res Part C 16(3):350–369CrossRefGoogle Scholar
  102. 102.
    Sun H-J, Campos JL, Chan GSW (2004a) Multisensory integration in the estimation of relative path length. Exp Brain Res 154(2):246–254CrossRefGoogle Scholar
  103. 103.
    Sun H-J, Campos JL, Young M, Chan GSW, Ellard C (2004b) The contributions of static visual cues, nonvisual cues, and optic flow in distance estimation. Perception 33(1):49–65CrossRefGoogle Scholar
  104. 104.
    Tan H, Wilson AM, Lowe J (2008) Measurement of stride parameters using a wearable GPS and inertial measurement unit. J Biomech 41(7):1398–1406CrossRefGoogle Scholar
  105. 105.
    Tarr MJ, Warren WH (2002) Virtual reality in behavioral neuroscience and beyond. Nat Neurosci 5:1089–1092CrossRefGoogle Scholar
  106. 106.
    Terrier P, Ladetto Q, Merminod B, Schutz Y (2000) High-precision satellite positioning system as a new tool to study the biomechanics of human locomotion. J Biomech 33(12):1717–1722CrossRefGoogle Scholar
  107. 107.
    Terrier P, Schutz Y (2003) Variability of gait patterns during unconstrained walking assessed by satellite positioning (GPS). Eur J Appl Physiol 90(5–6):554–561CrossRefGoogle Scholar
  108. 108.
    Terrier P, Turner V, Schutz Y (2005) GPS analysis of human locomotion: Further evidence for long-range correlations in stride-to-stride fluctuations of gait parameters. Hum Mov Sci 24(1):97–115CrossRefGoogle Scholar
  109. 109.
    Thomson JA (1983) Is continuous visual monitoring necessary in visually guided locomotion? J Exp Psychol: Hum Percept Perform 9(3):427–443CrossRefGoogle Scholar
  110. 110.
    Troped PJ, Oliveira MS, Matthews CE, Cromley EK, Melly SJ, Craig BA (2008) Prediction of activity mode with global positioning system and accelerometer data. Med Sci Sports Exerc 40(5):972–978CrossRefGoogle Scholar
  111. 111.
    Vallis LA, Patla AE (2004) Expected and unexpected head yaw movements result in different modifications of gait and whole body coordination strategies. Exp Brain Res 157(1):94–110CrossRefGoogle Scholar
  112. 112.
    Van den Bergh M, Koller-Meier E, Van Gool L (2009) Real-time Body Pose Recognition using 2D or 3D Haarlets. Int J Comput Vis 83(1):72–84CrossRefGoogle Scholar
  113. 113.
    Wann JP, Swapp DK (2000) Why you should look where you are going. Nat Neurosci 3(7):647–648CrossRefGoogle Scholar
  114. 114.
    Warabi T, Kato M, Kiriyama K, Yoshida T, Kobayashi N (2005) Treadmill walking and overground walking of human subjects compared by recording sole-floor reaction force. Neurosci Res 53(3):343–348CrossRefGoogle Scholar
  115. 115.
    Zarrugh MY, Radcliffe CW (1978) Predicting metabolic cost of level walking. Eur J Appl Physiol 38(3):215–223CrossRefGoogle Scholar
  116. 116.
    Zehr EP, Stein RB (1999) What functions do reflexes serve during human locomotion. Prog Neurobiol 58(2):185–205CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Ilja Frissen
    • 2
    • 1
  • Jennifer L. Campos
    • 1
    • 3
    • 4
    • 5
  • Manish Sreenivasa
    • 1
    • 6
  • Marc O. Ernst
    • 1
    • 7
  1. 1.Max Planck Institute for Biological CyberneticsMultisensory Perception and Action GroupTübingenGermany
  2. 2.LUNAM Université, CNRS, Ecole Centrale de NantesIRCCyN (Institut de Recherche en Communications et Cybernétique de Nantes)Nantes Cedex 3France
  3. 3.Max Planck Institute for Biological CyberneticsMultisensory Perception and Action GroupTübingenGermany
  4. 4.iDAPTToronto Rehabilitation InstituteOntarioCanada
  5. 5.Department of PsychologyUniversity of Toronto OntarioCanada
  6. 6.Nakamura Laboratory, Department of Mechano-InformaticsUniversity of TokyoTokyoJapan
  7. 7.Department of Cognitive NeuroscienceUniversity of BielefeldBielefeldGermany

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