@inproceedings{69596dacb27641f6b2d2486a84ee6f4a,
title = "Calculating reachable workspace volume for use in quantitative medicine",
abstract = "Quantitative measures of the space an individual can reach is essential for tracking the progression of a disease and the effects of therapeutic intervention. The reachable workspace can be used to track an individuals{\textquoteright} ability to perform activities of daily living, such as feeding and grooming. There are few methods for quantifying upper limb performance, none of which are able to generate a reachable workspace volume from motion capture data. We introduce a method to estimate the reachable workspace volume for an individual by capturing their observed joint limits using a low cost depth camera. This method is then tested on seven individuals with varying upper limb performance. Based on these initial trials, we found that the reachable workspace volume decreased as muscular impairment increased. This shows the potential for this method to be used as a quantitative clinical assessment tool.",
keywords = "Assessment, Diagnosis, Functional workspace, Goniometry, Kinect, Muscular dystrophy, Rehabilitation, Skeletal Modelling",
author = "Matthew, {Robert Peter} and Gregorij Kurillo and Han, {Jay J.} and Ruzena Bajcsy",
year = "2015",
doi = "10.1007/978-3-319-16199-0_40",
language = "English (US)",
isbn = "9783319161983",
volume = "8927",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "570--583",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
note = "13th European Conference on Computer Vision, ECCV 2014 ; Conference date: 06-09-2014 Through 12-09-2014",
}