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Assessing the effectiveness of robot facilitated neurorehabilitation for relearning motor skills following a stroke

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Abstract

A growing awareness of the potential for machine-mediated neurorehabilitation has led to several novel concepts for delivering these therapies. To get from laboratory demonstrators and prototypes to the point where the concepts can be used by clinicians in practice still requires significant additional effort, not least in the requirement to assess and measure the impact of any proposed solution. To be widely accepted a study is required to use validated clinical measures but these tend to be subjective, costly to administer and may be insensitive to the effect of the treatment. Although this situation will not change, there is good reason to consider both clinical and mechanical assessments of recovery. This article outlines the problems in measuring the impact of an intervention and explores the concept of providing more mechanical assessment techniques and ultimately the possibility of combining the assessment process with aspects of the intervention.

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Notes

  1. Hocoma, Switzerland.

  2. A Hammerstein model is a simple non-linear model that consists of a static non-linear element that shapes the input variable, followed by a linear dynamic element.

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Authors and Affiliations

  1. Cybernetics Research Group, School of Systems Engineering, University of Reading, Reading, RG6 6AY, UK

    W. S. Harwin

  2. Department of Human Movement Sciences, Maastricht University, Maastricht, The Netherlands

    A. Murgia

  3. Department of Physiotherapy, School of Medicine, Trinity College, Dublin, Ireland

    E. K. Stokes

Authors
  1. W. S. Harwin
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  2. A. Murgia
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  3. E. K. Stokes
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Correspondence to W. S. Harwin.

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Harwin, W.S., Murgia, A. & Stokes, E.K. Assessing the effectiveness of robot facilitated neurorehabilitation for relearning motor skills following a stroke. Med Biol Eng Comput 49, 1093–1102 (2011). https://doi.org/10.1007/s11517-011-0799-y

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