NDLI: Pressure signal feature extraction for the differentiation of clinical mobility assessments

Content Provider	IEEE Xplore Digital Library
Author	Bennett, S.L. Goubran, R. Rockwood, K. Arcelus, A. Knoefel, F.
Copyright Year	2012
Description	Author affiliation: Division of Geriatric Medicine, Dalhousie University, Capital District Health Authority, 1421-5955 Veterans Memorial Lane, Halifax, NS, B3H 2E1, Canada (Arcelus, A.) \|\| CIHR-STIHR Health Care Technology and Place, Intelligent Assistive Technology and Systems Lab, University of Toronto, 160-500 University Ave, Toronto, ON M5G 1V7, Canada (Rockwood, K.) \|\| Department of Computer and Systems Engineering, Carleton University, 1125 Colonel By Drive, Ottawa ON, K1S 5B6 Canada (Bennett, S.L.; Goubran, R.; Knoefel, F.)
Abstract	While clinical measures of mobility and balance are important for tracking disease progression in the elderly, most of these tools are based on what can be observed by the human eye, and many do not assess bedridden patients. This paper examines the potential for pressure sensitive mats to be used in conjunction with data processing to develop a system that automates a clinical tool used to assess balance and mobility in the elderly. A study was conducted in which pressure data were gathered while 30 non-patient volunteers performed partial in-bed clinical assessments. Data were then analyzed by grouping sensor data, calculating ratios, then extracting features from the analyzed signals. Pressure ratio signals representing each part of the simulated assessment, were consistent among volunteers and were visually and numerically distinguishable from another. These results indicate that the movement specific pressure signal features identified here are quantifiable and that algorithms may be written to identify and distinguish between certain movements and output the correct clinical assessment.
Starting Page	1
Ending Page	5
File Size	1374654
Page Count	5
File Format	PDF
ISBN	9781467308809
e-ISBN	9781467308823
DOI	10.1109/MeMeA.2012.6226640
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-18
Publisher Place	Hungary
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Senior citizens Geriatrics Feature extraction System-on-a-chip Educational institutions Diseases mobility measurement Elderly unobtrusive monitering pressure sensor array signal processing fraily
Content Type	Text
Resource Type	Article

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