@article {804,
	title = {Normalization and extraction of interpretable metrics from raw accelerometry data.},
	journal = {Biostatistics},
	volume = {15},
	year = {2014},
	month = {2014 Jan},
	pages = {102-16},
	abstract = {<p>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.</p>},
	keywords = {Acceleration, Aged, Baltimore, Cohort Studies, Data Interpretation, Statistical, Female, Humans, Male, Motor Activity},
	issn = {1468-4357},
	doi = {10.1093/biostatistics/kxt029},
	author = {Bai, Jiawei and He, Bing and Shou, Haochang and Zipunnikov, Vadim and Glass, Thomas A and Crainiceanu, Ciprian M}
}
@article {Bai2014Metrics,
	title = {Normalization and extraction of interpretable metrics from raw accelerometry data},
	journal = {Biostatistics},
	volume = {15},
	number = {1},
	year = {2014},
	pages = {102{\textendash}116},
	abstract = {<p>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.</p>},
	keywords = {Activity intensity, Movelets, Movement, Signal processing, Time active, Tri-axial accelerometer},
	issn = {14654644},
	author = {Bai, Jiawei and He, Bing and Shou, Haochang and Zipunnikov, Vadim and Glass, Thomas A. and Crainiceanu, Ciprian M.}
}
