title: Vision-based body tracking: turning Kinect into a clinical tool.
abstract: Vision-based body tracking technologies, originally developed for the consumer gaming market, are being repurposed to form the core of a range of innovative healthcare applications in the clinical assessment and rehabilitation of movement ability. Vision-based body tracking has substantial potential, but there are technical limitations.
  
  
  
  We use our "stories from the field" to articulate the challenges and offer examples of how these can be overcome.
  
  
  
  We illustrate that: (i) substantial effort is needed to determine the measures and feedback vision-based body tracking should provide, accounting for the practicalities of the technology (e.g. range) as well as new environments (e.g. home). (ii) Practical considerations are important when planning data capture so that data is analysable, whether finding ways to support a patient or ensuring everyone does the exercise in the same manner. (iii) Home is a place of opportunity for vision-based body tracking, but what we do now in the clinic (e.g. balance tests) or in the home (e.g. play games) will require modifications to achieve capturable, clinically relevant measures.
  
  
  
  This article articulates how vision-based body tracking works and when it does not to continue to inspire our clinical colleagues to imagine new applications. Implications for Rehabilitation Vision-based body tracking has quickly been repurposed to form the core of innovative healthcare applications in clinical assessment and rehabilitation, but there are clinical as well as practical challenges to make such systems a reality. Substantial effort needs to go into determining what types of measures and feedback vision-based body tracking should provide. This needs to account for the practicalities of the technology (e.g. range) as well as the opportunities of new environments (e.g. the home). Practical considerations need to be accounted for when planning capture in a particular environment so that data is analysable, whether it be finding a chair substitute, ways to support a patient or ensuring everyone does the exercise in the same manner. The home is a place of opportunity with vision-based body tracking, but it would be naïve to think that we can do what we do now in the clinic (e.g. balance tests) or in the home (e.g. play games), without appropriate modifications to what constitutes a practically capturable, clinically relevant measure.
authors.affiliation: a Microsoft Research , Cambridge , UK .
authors.forename: Cecily
authors.initials: C
authors.lastname: Morrison
authors.affiliation: b School of Mechanical Engineering, University of Leeds , Leeds , UK .
authors.forename: Peter
authors.initials: P
authors.lastname: Culmer
authors.affiliation: c University of Maryland Baltimore County , Baltimore MD , USA , and.
authors.forename: Helena
authors.initials: H
authors.lastname: Mentis
authors.affiliation: d Department of Psychology , Royal Holloway University of London , Egham , UK.
authors.forename: Tamar
authors.initials: T
authors.lastname: Pincus
mesh_terms: D004185:Disability Evaluation; D004777:Environment; D005246:Feedback; D006801:Humans; D009068:Movement / Q000502:physiology*; D026741:Physical Therapy Modalities / Q000295:instrumentation*; D011597:Psychomotor Performance / Q000502:physiology*; D018910:Video Games
keywords: Clinical assessment; kinect; movement ability; rehabilitation; vision-based body tracking