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The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by Strathclyde researchers from the Department of Computer & Information Sciences involved in researching exciting new applications for mobile and smartphone technology. But the transformative application of mobile technologies is also the focus of research within disciplines as diverse as Electronic & Electrical Engineering, Marketing, Human Resource Management and Biomedical Enginering, among others.

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Innovating technology for use in rehabiliation

Rowe, Philip (2012) Innovating technology for use in rehabiliation. Journal of Bioengineering and Biomedical Science (specia). ISSN 2155-9538

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

In rehabilitation, as with most other health care fields, there is strong demand for a robust evidence base of effectiveness and cost efficiency. However, researching the evidence base in our field is complex. To evaluate outcome we must adopt a multi-variate and multi-domain approach. Further rehabilitation services are often concerned with patients with multiple long term conditions rather than a single acute illness and hence the results of intervention are less certain and may only be apparent over the longer term. Unlike conventional clinical trials of medicines or medical devices rehabilitation research must therefore develop alternate methods for evaluating and exploring innovation and practice. Complex interventions such as rehabilitation need a more flexible development and evaluation roadmap which is more akin to those used in engineering than those used in medicine. These complex methodologies and development processes which mix quantitative and qualitative data in the research, development and evaluation process are familiar to designers, technologists and engineers who often have to take on mixed model data when designing products or services. The opinion of users must be mixed with hard scientific data on cause and effect when developing and engineering products.