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Sit-to-stand measurement for in-home monitoring using voxel analysis.

Authors :
Banerjee T
Skubic M
Keller JM
Abbott C
Source :
IEEE journal of biomedical and health informatics [IEEE J Biomed Health Inform] 2014 Jul; Vol. 18 (4), pp. 1502-9. Date of Electronic Publication: 2013 Oct 03.
Publication Year :
2014

Abstract

We present algorithms to segment the activities of sitting and standing, and identify the regions of sit-to-stand (STS) transitions in a given image sequence. As a means of fall risk assessment, we propose methods to measure STS time using the 3-D modeling of a human body in voxel space as well as ellipse fitting algorithms and image features to capture orientation of the body. The proposed algorithms were tested on ten older adults with ages ranging from 83 to 97. Two techniques in combination yielded the best results, namely the voxel height in conjunction with the ellipse fit. Accurate STS time was computed on various STSs and verified using a marker-based motion capture system. This application can be used as part of a continuous video monitoring system in the homes of older adults and can provide valuable information to help detect fall risk and enable early interventions.

Details

Language :
English
ISSN :
2168-2208
Volume :
18
Issue :
4
Database :
MEDLINE
Journal :
IEEE journal of biomedical and health informatics
Publication Type :
Academic Journal
Accession number :
24108751
Full Text :
https://doi.org/10.1109/JBHI.2013.2284404