Exploring the bases for a mixed reality stroke rehabilitation system, Part II: Design of Interactive Feedback for upper limb rehabilitation

• Type of Material: Article
• Authors: Nicole Lehrer, Arizona State University; Yinpeng Chen, Arizona State University; Margaret Duff, Arizona State University; Steven L Wolf, Emory University; Thanassis Rikakis, Arizona State University
• Language: English
• Date: 2011-09-08
• Publisher: BioMed Central
• Publication Version: Final Published Version
• Copyright Statement: © 2011 Lehrer et al; licensee BioMed Central Ltd.
• License: Creative Commons Attribution 2.0 Generic
• Final Published Version (URL): http://www.jneuroengrehab.com/content/8/1/54
• Title of Journal or Parent Work: Journal of NeuroEngineering and Rehabilitation
• ISSN: 1743-0003
• Volume: 8
• Issue: 54
• Start Page: 1
• End Page: 21
• Research Categories: Engineering, Biomedical

Abstract

Background Few existing interactive rehabilitation systems can effectively communicate multiple aspects of movement performance simultaneously, in a manner that appropriately adapts across various training scenarios. In order to address the need for such systems within stroke rehabilitation training, a unified approach for designing interactive systems for upper limb rehabilitation of stroke survivors has been developed and applied for the implementation of an Adaptive Mixed Reality Rehabilitation (AMRR) System. Results The AMRR system provides computational evaluation and multimedia feedback for the upper limb rehabilitation of stroke survivors. A participant's movements are tracked by motion capture technology and evaluated by computational means. The resulting data are used to generate interactive media-based feedback that communicates to the participant detailed, intuitive evaluations of his performance. This article describes how the AMRR system's interactive feedback is designed to address specific movement challenges faced by stroke survivors. Multimedia examples are provided to illustrate each feedback component. Supportive data are provided for three participants of varying impairment levels to demonstrate the system's ability to train both targeted and integrated aspects of movement. Conclusions The AMRR system supports training of multiple movement aspects together or in isolation, within adaptable sequences, through cohesive feedback that is based on formalized compositional design principles. From preliminary analysis of the data, we infer that the system's ability to train multiple foci together or in isolation in adaptable sequences, utilizing appropriately designed feedback, can lead to functional improvement. The evaluation and feedback frameworks established within the AMRR system will be applied to the development of a novel home-based system to provide an engaging yet low-cost extension of training for longer periods of time.