title: Normalization and extraction of interpretable metrics from raw accelerometry data.
abstract: We introduce an explicit set of metrics for human activity based on high-density acceleration recordings from a hip-worn tri-axial accelerometer. These metrics are based on two concepts: (i) Time Active, a measure of the length of time when activity is distinguishable from rest and (ii) AI, a measure of the relative amplitude of activity relative to rest. All measurements are normalized (have the same interpretation across subjects and days), easy to explain and implement, and reproducible across platforms and software implementations. Metrics were validated by visual inspection of results and quantitative in-lab replication studies, and by an association study with health outcomes.
authors.affiliation: Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205, USA.
authors.forename: Jiawei
authors.initials: J
authors.lastname: Bai
authors.forename: Bing
authors.initials: B
authors.lastname: He
authors.forename: Haochang
authors.initials: H
authors.lastname: Shou
authors.forename: Vadim
authors.initials: V
authors.lastname: Zipunnikov
authors.forename: Thomas A
authors.initials: TA
authors.lastname: Glass
authors.forename: Ciprian M
authors.initials: CM
authors.lastname: Crainiceanu
mesh_terms: D000054:Acceleration; D000368:Aged; D015142:Baltimore; D015331:Cohort Studies; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008297:Male; D009043:Motor Activity / Q000502:physiology*
keywords: Activity intensity; Movelets; Movement; Signal processing; Time active; Tri-axial accelerometer