Literature DB >> 25495708

Vision-based body tracking: turning Kinect into a clinical tool.

Cecily Morrison1, Peter Culmer2, Helena Mentis3, Tamar Pincus4.   

Abstract

PURPOSE: 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.
METHOD: We use our "stories from the field" to articulate the challenges and offer examples of how these can be overcome.
RESULTS: 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.
CONCLUSIONS: 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.

Entities:  

Keywords:  Clinical assessment; kinect; movement ability; rehabilitation; vision-based body tracking

Mesh:

Year:  2014        PMID: 25495708     DOI: 10.3109/17483107.2014.989419

Source DB:  PubMed          Journal:  Disabil Rehabil Assist Technol        ISSN: 1748-3107


  4 in total

1.  Modifying Kinect placement to improve upper limb joint angle measurement accuracy.

Authors:  Na Jin Seo; Mojtaba F Fathi; Pilwon Hur; Vincent Crocher
Journal:  J Hand Ther       Date:  2016-10-18       Impact factor: 1.950

2.  The Quantified Brain: A Framework for Mobile Device-Based Assessment of Behavior and Neurological Function.

Authors:  David E Stark; Rajiv B Kumar; Christopher A Longhurst; Dennis P Wall
Journal:  Appl Clin Inform       Date:  2016-05-04       Impact factor: 2.342

3.  Validation of Marker-Less System for the Assessment of Upper Joints Reaction Forces in Exoskeleton Users.

Authors:  Simone Pasinetti; Cristina Nuzzi; Nicola Covre; Alessandro Luchetti; Luca Maule; Mauro Serpelloni; Matteo Lancini
Journal:  Sensors (Basel)       Date:  2020-07-13       Impact factor: 3.576

4.  Usability and Acceptability of ASSESS MS: Assessment of Motor Dysfunction in Multiple Sclerosis Using Depth-Sensing Computer Vision.

Authors:  Cecily Morrison; Marcus D'Souza; Kit Huckvale; Jonas F Dorn; Jessica Burggraaff; Christian Philipp Kamm; Saskia Marie Steinheimer; Peter Kontschieder; Antonio Criminisi; Bernard Uitdehaag; Frank Dahlke; Ludwig Kappos; Abigail Sellen
Journal:  JMIR Hum Factors       Date:  2015-06-24
  4 in total

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