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

Cecily Morrison; Robert Corish; Abigail Sellen

8th International Conference on Pervasive Computing Technologies for Healthcare

Research Article

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

Cite: 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