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Cited by 600

The DOI matches its Crossref record; 140 of the 140 references it cites were found in a registry or an index.

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

Open access
Preece, Stephen J, Goulermas, John Y, Kenney, Laurence P J, Howard, Dave, Meijer, Kenneth, Crompton, Robin·2009·Physiological Measurement
DOI 10.1088/0967-3334/30/4/r01
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Abstract

With the advent of miniaturized sensing technology, which can be body-worn, it is now possible 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 produce 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.

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Citations

Cites

Show all 140 references

Research works printed but not linked: 29

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Metadata

Authors
Preece, S. J., Goulermas, J. Y., Kenney, L. P. J., Howard, D., Meijer, K., & Crompton, R.
Venue
Physiological Measurement
Publisher
IOP Publishing
Published
2009-04-01
Volume
30
Issue
4
Pages
R1-R33
ISSN
  • 0967-3334 (ISSN-L)
  • 1361-6579
DOI
10.1088/0967-3334/30/4/r01
OpenAlex
W1993761347
Cited by
600
References
140
FWCI
30.42
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Activity identification using body-mounted sensors—a review of classification techniques. https://app.cochat.ai/papers/10.1088/0967-3334/30/4/r01
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Preece, S. J., Goulermas, J. Y., Kenney, L. P. J., Howard, D., Meijer, K., & Crompton, R. (2009). Activity identification using body-mounted sensors—a review of classification techniques. Physiological Measurement. https://doi.org/10.1088/0967-3334/30/4/r01

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