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Using unsupervised machine learning to quantify physical activity from accelerometry in a diverse and rapidly changing population

Lookup NU author(s): Dr Christopher ThorntonORCiD, Professor Niina KolehmainenORCiD, Professor Kianoush Nazarpour

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Publication metadata

Author(s): Thornton C, Kolehmainen N, Nazarpour K

Publication type: Article

Publication status: Published

Journal: PLOS Digital Health

Year: 2023

Volume: 2

Issue: 4

Online publication date: 05/04/2023

Acceptance date: 23/02/2023

Date deposited: 20/04/2023

ISSN (electronic): 2767-3170

Publisher: Public Library of Science

URL: https://doi.org/10.1371/journal.pdig.0000220

DOI: 10.1371/journal.pdig.0000220

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Funding

Funder referenceFunder name
EP/R004242/2
ICA-SCL-2015-01-003National Institute for Health Research (NIHR)
ICA-SCL-2015-01-003National Institute for Health Research (NIHR)

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