Interdisciplinary concepts for Design and Implementation of mixed reality interactive Neurorehabilitation systems for stroke

Michael Baran*, Nicole Lehrer, Margaret Duff, Vinay Venkataraman, Pavan Turaga, Todd Ingalls, W. Zev Rymer, Steven L. Wolf, Thanassis Rikakis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


Interactive neurorehabilitation (INR) systems provide therapy that can evaluate and deliver feedback on a patient’s movement computationally. There are currently many approaches to INR design and implementation, without a clear indication of which methods to utilize best. This article presents key interactive computing, motor learning, and media arts concepts utilized by an interdisciplinary group to develop adaptive, mixed reality INR systems for upper extremity therapy of patients with stroke. Two INR systems are used as examples to show how the concepts can be applied within: (1) a small-scale INR clinical study that achieved integrated improvement of movement quality and functionality through continuously supervised therapy and (2) a pilot study that achieved improvement of clinical scores with minimal supervision. The notion is proposed that some of the successful approaches developed and tested within these systems can form the basis of a scalable design methodology for other INR systems. A coherent approach to INR design is needed to facilitate the use of the systems by physical therapists, increase the number of successful INR studies, and generate rich clinical data that can inform the development of best practices for use of INR in physical therapy.

Original languageEnglish (US)
Pages (from-to)449-460
Number of pages12
JournalPhysical therapy
Issue number3
StatePublished - Mar 1 2015

ASJC Scopus subject areas

  • Physical Therapy, Sports Therapy and Rehabilitation

Fingerprint Dive into the research topics of 'Interdisciplinary concepts for Design and Implementation of mixed reality interactive Neurorehabilitation systems for stroke'. Together they form a unique fingerprint.

Cite this