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An optimised algorithm for accurate steps counting from smart-phone accelerometry

Abstract:

Step counting from smart-phones allows a wide range of applications related to fitness and health. Estimating steps from phones' accelerometers is challenging because of the multitude of ways a smart-phone can be carried. We focus our work on the windowed peak detection algorithm, which has previously been shown to be accurate and efficient and thus suitable for mobile devices. We explore and optimise further the algorithm and its parameters making use of data collected by three volunteers ho...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/EMBC.2018.8513319

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0002-9203-1124
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
NIHR Oxford Biomedical Research Centre More from this funder
Publisher:
IEEE Publisher's website
Journal:
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Journal website
Pages:
4423-4427
Host title:
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Publication date:
2018-10-29
Acceptance date:
2018-04-18
DOI:
ISSN:
1558-4615
Source identifiers:
944600
ISBN:
9781538636466
Pubs id:
pubs:944600
UUID:
uuid:b1b3cf44-8fa6-4866-9408-bb65129340a8
Local pid:
pubs:944600
Deposit date:
2018-11-20

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