NDLI: A wearable triaxial accelerometry system for longitudinal assessment of falls risk

Content Provider	IEEE Xplore Digital Library
Author	Narayanan, Michael R. Scalzi, Maria Elena Redmond, Stephen J. Lord, Steven R. Celler, Branko G. Lovell, Nigel H.
Copyright Year	2008
Description	Author affiliation: Graduate School of Biomedical Engineering, University of New South Wales, Australia (Redmond, Stephen J.; Lovell, Nigel H.) \|\| Biomedical Systems Laboratory, School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney 2052, Australia (Narayanan, Michael R.; Celler, Branko G.) \|\| Prince of Wales Medical Research Institute and with the School of Medicine, University of New South Wales, Australia (Lord, Steven R.) \|\| Department of Biomedical Engineering, Politecnico di Milano, Italy (Scalzi, Maria Elena)
Abstract	Falls-related injuries in the elderly population are a major cause of morbidity and represent one of the most significant contributors to hospitalizations and rising health care expense in developed countries. Many laboratory-based studies have described falls detection systems using wearable accelerometry. However, only a limited number of reports have tried to address the difficult issues of falls detection and falls prevention in unsupervised or free-living environments. We describe a waist-mounted triaxial accelerometry (Triax) system with a remote data collection capability to provide unsupervised monitoring of the elderly. The basis of the monitoring is a self-administered directed-routine (DR) comprising three separate tests measured by way of the Triax. We present an initial evaluation of the DR results in 36 patients to detect early changes in functional ability and facilitate falls risk stratification. Extracted features considered alone show a correlation with falls risk of approximately ρ=0.5. Estimation of falls risk using a linear least squares model provides a root-mean-squared error of 0.69 (ρ=0.58, p<0.0002).
Starting Page	2840
Ending Page	2843
File Size	137662
Page Count	4
File Format	PDF
ISBN	9781424418145
ISSN	1557170X
DOI	10.1109/IEMBS.2008.4649794
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-08-20
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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