An interactive therapy system for arm and hand rehabilitation

The paper presents results from a virtual reality (VR)-based system for upper limb rehabilitation. The system incorporates a range of interchangeable direction sensing devices (the Optical Linear Encoder (OLE) and the inertial measurement unit (IMU)) that can be adjusted to a large range of different arm and hand sizes, and interactive practice applications designed for motivating and seamlessly driving users to perform the functional and non-functional motor recovery tasks. We describe the kinematic models of both arm and hand, the technical details of two motion track components (the arm suit and the SmartGlove) and the design of the interactive scenarios. The system thus promises to be a valuable complement to conventional therapeutic programs offered in rehabilitation clinics.

[1]  N. Miller,et al.  Technique to improve chronic motor deficit after stroke. , 1993, Archives of physical medicine and rehabilitation.

[2]  Y Laufer,et al.  Repetitive Practice of a Single Joint Movement for Enhancing Elbow Function in Hemiparetic Patients , 1997, Perceptual and motor skills.

[3]  Huosheng Hu,et al.  Integration of Vision and Inertial Sensors for 3D Arm Motion Tracking in Home-based Rehabilitation , 2007, Int. J. Robotics Res..

[4]  Philippe Coiffet,et al.  Virtual Reality Technology , 1992 .

[5]  Zhaoying Zhou,et al.  A real-time articulated human motion tracking using tri-axis inertial/magnetic sensors package. , 2004, IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[6]  Derek G. Kamper,et al.  A low cost instrumented glove for extended monitoring and functional hand assessment , 2007, Journal of Neuroscience Methods.

[7]  A. Prevo,et al.  The long-term outcome of arm function after stroke: results of a follow-up study. , 1999, Disability and rehabilitation.

[8]  Grigore C. Burdea,et al.  A virtual-reality-based telerehabilitation system with force feedback , 2000, IEEE Transactions on Information Technology in Biomedicine.

[9]  Yu-Luen Chen,et al.  Application of tilt sensors in human-computer mouse interface for people with disabilities. , 2001, IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[10]  M. Levin,et al.  Compensatory strategies for reaching in stroke. , 2000, Brain : a journal of neurology.

[11]  Kevin C. Chung,et al.  Atlas of Hand Anatomy and Clinical Implications. , 2005 .

[12]  N. Hogan,et al.  Movement Smoothness Changes during Stroke Recovery , 2002, The Journal of Neuroscience.

[13]  Henry Been-Lirn Duh,et al.  A wearable, self-calibrating, wireless sensor network for body motion processing , 2008, 2008 IEEE International Conference on Robotics and Automation.

[14]  M. Tomizuka,et al.  Control of Exoskeletons Inspired by Fictitious Gain in Human Model , 2009, IEEE/ASME Transactions on Mechatronics.

[15]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[16]  Albert Rizzo,et al.  Virtual reality for psychotherapy: Current reality and future possibilities. , 2003 .