Usability and Performance of Leap Motion and Oculus Rift for Upper Arm Virtual Reality Stroke Rehabilitation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Intensified rehabilitation is important for stroke survivors but difficult to achieve due to limited access to physiotherapy. We present a virtual reality rehabilitation system, Target Acquiring Exercise (TAGER), designed to supplement center-based physiotherapy by providing engaging and personalized exercises. TAGER uses natural user interface devices, the Microsoft Kinect, Leap Motion and Myo armband, to track upper arm and body motion. Linear regression was applied to 3D user motion data using four popular forms of Fitts’s law and each approach evaluated. While all four forms of Fitt’s Law produced similar results and could model users effectively, it may be argued that a 3D tailored form provided the best fit. However, we propose that Fitts’s Law may be more suitable as the basis of a more complex model to profile user performance. Evaluated by healthy users TAGER proved effective, with important lessons learned which will inform future design.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages9
Publication statusE-pub ahead of print - 20 Sep 2016
Event11th International Conference on Disability, Virtual Reality & Associated Technologies -
Duration: 20 Sep 2016 → …

Conference

Conference11th International Conference on Disability, Virtual Reality & Associated Technologies
Period20/09/16 → …

Fingerprint

Physical therapy
Patient rehabilitation
Virtual reality
Linear regression
User interfaces

Keywords

  • Games
  • Virtual Reality
  • Upper arm
  • stroke Rehabilitation
  • Leap Motion
  • Oculus Rift.

Cite this

@inproceedings{98aa14171ba1483fb408307f16ddbf17,
title = "Usability and Performance of Leap Motion and Oculus Rift for Upper Arm Virtual Reality Stroke Rehabilitation",
abstract = "Intensified rehabilitation is important for stroke survivors but difficult to achieve due to limited access to physiotherapy. We present a virtual reality rehabilitation system, Target Acquiring Exercise (TAGER), designed to supplement center-based physiotherapy by providing engaging and personalized exercises. TAGER uses natural user interface devices, the Microsoft Kinect, Leap Motion and Myo armband, to track upper arm and body motion. Linear regression was applied to 3D user motion data using four popular forms of Fitts’s law and each approach evaluated. While all four forms of Fitt’s Law produced similar results and could model users effectively, it may be argued that a 3D tailored form provided the best fit. However, we propose that Fitts’s Law may be more suitable as the basis of a more complex model to profile user performance. Evaluated by healthy users TAGER proved effective, with important lessons learned which will inform future design.",
keywords = "Games, Virtual Reality, Upper arm, stroke Rehabilitation, Leap Motion, Oculus Rift.",
author = "Dominic Holmes and DK Charles and PJ Morrow and S McClean and SM McDonough",
note = "Reference text: Avanzini, F. et al., 2009. Integrating auditory feedback in motor rehabilitation systems. Proceedings of International Conference on Multimodal Interfaces for Skills Transfer (SKILLS09), 232, pp.53–58. Burke, J.W. et al., 2009. Serious Games for Upper Limb Rehabilitation Following Stroke. 2009 Conference in Games and Virtual Worlds for Serious Applications, pp.103–110. B{\"u}tefisch, C., Hummelsheim, H. & Denzler, P., 1995. Repetitive training of isolated movements improves the outcome of motor rehabilitation of the centrally paretic hand. Journal of the Neurological Sciences, 130, pp.59–68. Cha, Y. & Myung, R., 2013. Extended Fitts’ law for 3D pointing tasks using 3D target arrangements. International Journal of Industrial Ergonomics, 43(4), pp.350–355. Charles, D. et al., 2014. Close range depth sensing cameras for virtual reality based hand rehabilitation. Journal of Assistive Technologies, 8(3), pp.138–149. Crosbie, J. et al., 2007. Virtual reality in stroke rehabilitation: Still more virtual than real. Disabil Rehabil, 29(14), pp.1139–1146. Heiko, D., 2013. A Lecture on Fitts ’ Law. , (July), pp.19–25. Hochstenbach-Waelen, A. & Seelen, H. a M., 2012. Embracing change: practical and theoretical considerations for successful implementation of technology assisting upper limb training in stroke. Journal of neuroengineering and rehabilitation, 9(1), p.52. Karime, A. et al., 2014. A Fuzzy-Based Adaptive Rehabilitation Framework for Home-Based Wrist Training. IEEE Transactions on Instrumentation and Measurement, 63(1), pp.135–144. Kwakkel, G. et al., 1999. Intensity of leg and arm training after primary middle-cerebral-artery stroke: a randomised trial. Lancet, 354(9174), pp.191–6. Laver, K. et al., 2015. Virtual reality for stroke rehabilitation. Cochrane Database of Systematic Reviews, (2), p.8,11,12,13. Levin, M.F., Weiss, P.L. & Keshner, E. a, 2015. Emergence of virtual reality as a tool for upper limb rehabilitation. Physical therapy, 95(3), pp.415–25. Monica, S.C., Sergi, B. i B. & Paul, F.M.J. verschure, 2008. Virtual Reality Based Upper Extremity Rehabilitation Following Stroke: A Review. Journal of CyberTherapy & Rehabilitation, 1(1), pp.63–74. Murata, A. & Iwase, H., 2001. Extending Fitts’ law to a three-dimensional pointing task. Human Movement Science, 20(6), pp.791–805. Powell, V. & Powell, W.A., 2014. Locating objects in virtual reality – the effect of visual properties on target acquisition in unrestrained reaching. Intl Conf. Disability, Virtual Reality & Associated Technologies, pp.2–4. Zimmerli, L. et al., 2012. Validation of a mechanism to balance exercise difficulty in robot-assisted upper-extremity rehabilitation after stroke. Journal of neuroengineering and rehabilitation, 9(1), p.6.",
year = "2016",
month = "9",
day = "20",
language = "English",
booktitle = "Unknown Host Publication",

}

Holmes, D, Charles, DK, Morrow, PJ, McClean, S & McDonough, SM 2016, Usability and Performance of Leap Motion and Oculus Rift for Upper Arm Virtual Reality Stroke Rehabilitation. in Unknown Host Publication. 11th International Conference on Disability, Virtual Reality & Associated Technologies, 20/09/16.

Usability and Performance of Leap Motion and Oculus Rift for Upper Arm Virtual Reality Stroke Rehabilitation. / Holmes, Dominic; Charles, DK; Morrow, PJ; McClean, S; McDonough, SM.

Unknown Host Publication. 2016.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Usability and Performance of Leap Motion and Oculus Rift for Upper Arm Virtual Reality Stroke Rehabilitation

AU - Holmes, Dominic

AU - Charles, DK

AU - Morrow, PJ

AU - McClean, S

AU - McDonough, SM

N1 - Reference text: Avanzini, F. et al., 2009. Integrating auditory feedback in motor rehabilitation systems. Proceedings of International Conference on Multimodal Interfaces for Skills Transfer (SKILLS09), 232, pp.53–58. Burke, J.W. et al., 2009. Serious Games for Upper Limb Rehabilitation Following Stroke. 2009 Conference in Games and Virtual Worlds for Serious Applications, pp.103–110. Bütefisch, C., Hummelsheim, H. & Denzler, P., 1995. Repetitive training of isolated movements improves the outcome of motor rehabilitation of the centrally paretic hand. Journal of the Neurological Sciences, 130, pp.59–68. Cha, Y. & Myung, R., 2013. Extended Fitts’ law for 3D pointing tasks using 3D target arrangements. International Journal of Industrial Ergonomics, 43(4), pp.350–355. Charles, D. et al., 2014. Close range depth sensing cameras for virtual reality based hand rehabilitation. Journal of Assistive Technologies, 8(3), pp.138–149. Crosbie, J. et al., 2007. Virtual reality in stroke rehabilitation: Still more virtual than real. Disabil Rehabil, 29(14), pp.1139–1146. Heiko, D., 2013. A Lecture on Fitts ’ Law. , (July), pp.19–25. Hochstenbach-Waelen, A. & Seelen, H. a M., 2012. Embracing change: practical and theoretical considerations for successful implementation of technology assisting upper limb training in stroke. Journal of neuroengineering and rehabilitation, 9(1), p.52. Karime, A. et al., 2014. A Fuzzy-Based Adaptive Rehabilitation Framework for Home-Based Wrist Training. IEEE Transactions on Instrumentation and Measurement, 63(1), pp.135–144. Kwakkel, G. et al., 1999. Intensity of leg and arm training after primary middle-cerebral-artery stroke: a randomised trial. Lancet, 354(9174), pp.191–6. Laver, K. et al., 2015. Virtual reality for stroke rehabilitation. Cochrane Database of Systematic Reviews, (2), p.8,11,12,13. Levin, M.F., Weiss, P.L. & Keshner, E. a, 2015. Emergence of virtual reality as a tool for upper limb rehabilitation. Physical therapy, 95(3), pp.415–25. Monica, S.C., Sergi, B. i B. & Paul, F.M.J. verschure, 2008. Virtual Reality Based Upper Extremity Rehabilitation Following Stroke: A Review. Journal of CyberTherapy & Rehabilitation, 1(1), pp.63–74. Murata, A. & Iwase, H., 2001. Extending Fitts’ law to a three-dimensional pointing task. Human Movement Science, 20(6), pp.791–805. Powell, V. & Powell, W.A., 2014. Locating objects in virtual reality – the effect of visual properties on target acquisition in unrestrained reaching. Intl Conf. Disability, Virtual Reality & Associated Technologies, pp.2–4. Zimmerli, L. et al., 2012. Validation of a mechanism to balance exercise difficulty in robot-assisted upper-extremity rehabilitation after stroke. Journal of neuroengineering and rehabilitation, 9(1), p.6.

PY - 2016/9/20

Y1 - 2016/9/20

N2 - Intensified rehabilitation is important for stroke survivors but difficult to achieve due to limited access to physiotherapy. We present a virtual reality rehabilitation system, Target Acquiring Exercise (TAGER), designed to supplement center-based physiotherapy by providing engaging and personalized exercises. TAGER uses natural user interface devices, the Microsoft Kinect, Leap Motion and Myo armband, to track upper arm and body motion. Linear regression was applied to 3D user motion data using four popular forms of Fitts’s law and each approach evaluated. While all four forms of Fitt’s Law produced similar results and could model users effectively, it may be argued that a 3D tailored form provided the best fit. However, we propose that Fitts’s Law may be more suitable as the basis of a more complex model to profile user performance. Evaluated by healthy users TAGER proved effective, with important lessons learned which will inform future design.

AB - Intensified rehabilitation is important for stroke survivors but difficult to achieve due to limited access to physiotherapy. We present a virtual reality rehabilitation system, Target Acquiring Exercise (TAGER), designed to supplement center-based physiotherapy by providing engaging and personalized exercises. TAGER uses natural user interface devices, the Microsoft Kinect, Leap Motion and Myo armband, to track upper arm and body motion. Linear regression was applied to 3D user motion data using four popular forms of Fitts’s law and each approach evaluated. While all four forms of Fitt’s Law produced similar results and could model users effectively, it may be argued that a 3D tailored form provided the best fit. However, we propose that Fitts’s Law may be more suitable as the basis of a more complex model to profile user performance. Evaluated by healthy users TAGER proved effective, with important lessons learned which will inform future design.

KW - Games

KW - Virtual Reality

KW - Upper arm

KW - stroke Rehabilitation

KW - Leap Motion

KW - Oculus Rift.

M3 - Conference contribution

BT - Unknown Host Publication

ER -