Gesture Therapy: A Vision-Based System for Arm Rehabilitation after Stroke
Each year millions of people in the world survive a stroke, in the U.S. alone the figure is over 600,000 people per year. Movement impairments after stroke are typically treated with intensive, hands-on physical and occupational therapy for several weeks after the initial injury. However, due to economic pressures, stroke patients are receiving less therapy and going home sooner, so the potential benefit of the therapy is not completely realized. Thus, it is important to develop rehabilitation technology that allows individuals who had suffered a stroke to practice intensive movement training without the expense of an always-present therapist. Current solutions are too expensive, as they require a robotic system for rehabilitation. We have developed a low-cost, computer vision system that allows individuals with stroke to practice arm movement exercises at home or at the clinic, with periodic interactions with a therapist. The system integrates a web based virtual environment for facilitating repetitive movement training, with state-of-the art computer vision algorithms that track the hand of a patient and obtain its 3-D coordinates, using two inexpensive cameras and a conventional personal computer. An initial prototype of the system has been evaluated in a pilot clinical study with promising results.
KeywordsRehabilitation stroke therapeutic technology computer vision
Unable to display preview. Download preview PDF.
- 1.American Stroke Association (2004) (Retrieved July 10, 2007), http://www.strokeassociation.org
- 2.Bradski, G.R.: Computer vision face tracking as a component of a perceptual user interface. In: Workshop on Applications of Computer Vision, pp. 214–219 (1998)Google Scholar
- 4.González, P., Cañas, J.: Seguimiento tridimensional usando dos cámaras. Technical Report, Universidad Rey Juan Carlos, Spain (2004) (in Spanish)Google Scholar
- 6.Reinkensmeyer, D., Pang, C., Nessler, J., Painter, C.: Web-based telerehabilitation for the upper extremity after stroke. IEEE Trans. Neural Sci. Rehabil. Eng. 10, 1–7 (2000)Google Scholar
- 7.Reinkensmeyer, D., Housman, S., Le Vu Rahman, T., Sanchez, R.: Arm-Training with T-WREX After Chronic Stroke: Preliminary Results of a Randomized Controlled Trial. In: ICORR 2007, 10th International Conference on Rehabilitation Robotics, Noordwijk (2007)Google Scholar
- 8.Reinkensmeyer, D., Housman, S.: If I can’t do it once, why do it a hundred times?: Connecting volition to movement success in a virtual environment motivates people to exercise the arm after stroke. In: IWVR (2007)Google Scholar
- 9.Sanchez, R.J., Liu, J., Rao, S., Shah, P., Smith, T., Rahman, T., Cramer, S.C., Bobrow, J.E., Reinkensmeyer, D.: Automating arm movement training following severe stroke: Functional exercise with quantitative feedback in a gravity-reduced environment. IEEE Trans. Neural Sci. Rehabil. Eng. 14(3), 378–389 (2006)CrossRefGoogle Scholar
- 11.Uswatte, G., Giuliani, C., Winstein, C., Zeringue, A., Hobbs, L., Wolf, S.L.: Validity of accelerometry for monitoring real-world arm activity in patients with sub acute stroke: evidence from the extremity constraint-induced therapy evaluation trial. Arch. Med. Rehabil. 86, 1340–1345 (2006)CrossRefGoogle Scholar