Here we present results where nineteen stroke survivors with chronic hemiparesis simultaneously employed the trio of patient, therapist, and machine. Massed practice combined with error augmentation, where haptic (robotic forces) and graphic (visual display) distortions are used to enhance the feedback of error, was compared to massed practice alone. The 6-week randomized crossover design involved approximately 60 minutes of daily treatment three times per week for two weeks, followed by one week of rest, and then repeated using the alternate treatment protocol. A therapist provided a visual target using a tracking device that moved a cursor in front of the patient, who was instructed to maintain the cursor on the target. The patient, therapist, technician-operator, and rater were blinded to treatment type. Several clinical measures gauged outcomes at the beginning and end of each 2-week period and one week post training. Results showed incremental benefit across most but not all days, abrupt gains in performance, and a benefit to error augmentation training in final evaluations. This application of interactive technology may be a compelling new method for enhancing a therapist's productivity in stroke-rehabilitation.
A pilot study was conducted to test the feasibility of using electromyographic signals to drive an active orthosis for hand therapy after stroke. Five stroke survivors with chronic hemiparesis completed 18 one-hour training sessions over 6 weeks. Activation patterns of a long finger flexor muscle and a long finger extensor muscle controlled an orthosis, the J-Glove, which provided assistance to finger extension to facilitate grasp-and-release movements. Initial results showed improvement in performance on one component, lifting a can, of the Wolf Motor Function Test for every subject and on the Action Research Arm Test for three of the subjects. Excitingly, a couple of the subjects showed signs of improved muscle activation patterns, although this requires further investigation.
Citation: Sharp, I., Patton, J., Listenberger, M., Case, E. Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy. J. Vis. Exp. (54), e3007, doi:10.3791/3007 (2011).
AbstractRecent research that tests interactive devices for prolonged therapy practice has revealed new prospects for robotics combined with graphical and other forms of biofeedback. Previous human-robot interactive systems have required different software commands to be implemented for each robot leading to unnecessary developmental overhead time each time a new system becomes available. For example, when a haptic/ graphic virtual reality environment has been coded for one specific robot to provide haptic feedback, that specific robot would not be able to be traded for another robot without recoding the program. However, recent efforts in the open source community have proposed a wrapper class approach that can elicit nearly identical responses regardless of the robot used. The result can lead researchers across the globe to perform similar experiments using shared code. Therefore modular "switching out"of one robot for another would not affect development time. In this paper, we outline the successful creation and implementation of a wrapper class for one robot into the open-source H3DAPI, which integrates the software commands most commonly used by all robots.
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