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8th International Conference on Pervasive Computing Technologies for Healthcare

Research Article

ASSESS MS: Supporting the Clinical Assessment of Multiple Sclerosis using Kinect

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BibTeX Plain Text
  • @INPROCEEDINGS{10.4108/icst.pervasivehealth.2014.255429,
        author={Cecily Morrison and Robert Corish and Abigail Sellen},
        title={ASSESS MS: Supporting the Clinical Assessment of Multiple Sclerosis using Kinect},
        proceedings={8th International Conference on Pervasive Computing Technologies for Healthcare},
        publisher={ICST},
        proceedings_a={PERVASIVEHEALTH},
        year={2014},
        month={7},
        keywords={kinect multiple sclerosis hci computer vision machine learning},
        doi={10.4108/icst.pervasivehealth.2014.255429}
    }
    
  • Cecily Morrison
    Robert Corish
    Abigail Sellen
    Year: 2014
    ASSESS MS: Supporting the Clinical Assessment of Multiple Sclerosis using Kinect
    PERVASIVEHEALTH
    ACM
    DOI: 10.4108/icst.pervasivehealth.2014.255429
Cecily Morrison1,*, Robert Corish1, Abigail Sellen1
  • 1: Microsoft Research
*Contact email: cecilym@microsoft.com

Abstract

We present an early prototype of the ASSESS MS system, developed to help health professionals more accurately monitor the progression of Multiple Sclerosis (MS). Specifically, the system aims to detect and quantify changes in motor dysfunction more objectively and accurately than human assessors. We focus on key interaction design decisions needed to deploy a machine-learning based system in a real clinical context.

Keywords
kinect multiple sclerosis hci computer vision machine learning
Published
2014-07-23
Publisher
ICST
http://dx.doi.org/10.4108/icst.pervasivehealth.2014.255429
Copyright © 2014–2025 ICST
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