NDLI: Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring

Content Provider	IEEE Xplore Digital Library
Author	Karantonis, D.M. Narayanan, M.R. Mathie, M. Lovell, N.H. Celler, B.G.
Copyright Year	1997
Abstract	The real-time monitoring of human movement can provide valuable information regarding an individual's degree of functional ability and general level of activity. This paper presents the implementation of a real-time classification system for the types of human movement associated with the data acquired from a single, waist-mounted triaxial accelerometer unit. The major advance proposed by the system is to perform the vast majority of signal processing onboard the wearable unit using embedded intelligence. In this way, the system distinguishes between periods of activity and rest, recognizes the postural orientation of the wearer, detects events such as walking and falls, and provides an estimation of metabolic energy expenditure. A laboratory-based trial involving six subjects was undertaken, with results indicating an overall accuracy of 90.8% across a series of 12 tasks (283 tests) involving a variety of movements related to normal daily activities. Distinction between activity and rest was performed without error; recognition of postural orientation was carried out with 94.1% accuracy, classification of walking was achieved with less certainty (83.3% accuracy), and detection of possible falls was made with 95.6% accuracy. Results demonstrate the feasibility of implementing an accelerometry-based, real-time movement classifier using embedded intelligence
Sponsorship	IEEE Engineering in Medicine and Biology Society IEEE Computer Society
Page Count	12
File Size	374932
Starting Page	156
Ending Page	167
File Format	PDF
ISSN	10897771
Volume Number	10
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-01-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biomedical monitoring Accelerometers Legged locomotion Real time systems Signal processing Event detection Testing Intelligent sensors Remote monitoring Australia movement classification Accelerometer ambulatory monitoring home telecare
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications Biotechnology

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