Physical activity phenotyping with activity bigrams, and their association with BMI | Zendy

Louise A C Millard | Zendy; Kate Tilling | Zendy; Debbie A. Lawlor | Zendy; Peter Flach | Zendy; Tom R. Gaunt | Zendy

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Physical activity phenotyping with activity bigrams, and their association with BMI

Author(s) -

Louise A C Millard,

Kate Tilling,

Debbie A. Lawlor,

Peter Flach,

Tom R. Gaunt

Publication year - 2017

Publication title -

international journal of epidemiology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.406

H-Index - 208

eISSN - 1464-3685

pISSN - 0300-5771

DOI - 10.1093/ije/dyx093

Subject(s) - bigram , physical activity , body mass index , confidence interval , association (psychology) , demography , statistics , activity tracker , longitudinal study , psychology , medicine , computer science , physical therapy , mathematics , artificial intelligence , sociology , psychotherapist , trigram

Analysis of physical activity usually focuses on a small number of summary statistics derived from accelerometer recordings: average counts per minute and the proportion of time spent in moderate-vigorous physical activity or in sedentary behaviour. We show how bigrams, a concept from the field of text mining, can be used to describe how a person's activity levels change across (brief) time points. These variables can, for instance, differentiate between two people spending the same time in moderate activity, where one person often stays in moderate activity from one moment to the next and the other does not.

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