Activity identification using body-mounted sensors — a review of classification techniques

Preece, SJ ORCID:, Goulermas, JY, Kenney, LPJ ORCID:, Howard, D ORCID:, Meijer, K and Crompton, R 2009, 'Activity identification using body-mounted sensors — a review of classification techniques' , Physiological Measurement, 30 , R1-R33.

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With the advent of miniaturized sensing technology, which can be body-worn, it is nowpossible to collect and store data on different aspects of human movement under the conditions of free living. This technology has the potential to be used in automated activity profiling systems which roduce a continuous record of activity patterns over extended periods of time. Such activity profiling systems are dependent on classification algorithms which can effectively interpret body-worn sensor data and identify different activities. This article reviews the different techniques which have been used to classify normal activities and/or identify falls from body-worn sensor data. The review is structured according to the different analytical techniques and illustrates the variety of approaches which have previously been applied in this field. Although significant progress has been made in this important area, there is still significant scope for further work, particularly in the application of advanced classification techniques to problems involving many different activities.

Item Type: Article
Themes: Subjects / Themes > R Medicine > RZ Other systems of medicine
Health and Wellbeing
Schools: Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Schools > School of Health and Society > Centre for Health Sciences Research
Journal or Publication Title: Physiological Measurement
Publisher: Institute of Physics
Refereed: Yes
ISSN: 0967-3334
Depositing User: SJ Preece
Date Deposited: 21 Dec 2010 10:29
Last Modified: 15 Feb 2022 15:48

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