acc: An R package to process, visualize, and analyze accelerometer data[Formula presented]

Jaejoon Song; Michael D. Swartz; Karen Basen-Engquist

doi:10.1016/j.simpa.2023.100577

acc: An R package to process, visualize, and analyze accelerometer data[Formula presented]

Jaejoon Song, Michael D. Swartz, Karen Basen-Engquist

Behavioral Science

Research output: Contribution to journal › Article › peer-review

Abstract

Wearable activity monitors are now widely used in behavioral and epidemiological studies to measure physical activity in free-living conditions. Despite the widespread use in research, the development of software to explore the data collected from these devices has been limited. We present acc, a comprehensive, free, and open-source R package to provide a seamless environment for exploring accelerometer data (https://cran.r-project.org/web/packages/acc). In this article, we demonstrate the software for processing, visualizing, and analyzing accelerometer data using real and simulated datasets.

Original language	English (US)
Article number	100577
Journal	Software Impacts
Volume	18
DOIs	https://doi.org/10.1016/j.simpa.2023.100577
State	Published - Nov 2023

Keywords

Accelerometer
Physical activity monitoring
Wearable sensor

ASJC Scopus subject areas

Software

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10.1016/j.simpa.2023.100577

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@article{c978f7d842b54ddbbee0d99676227232,

title = "acc: An R package to process, visualize, and analyze accelerometer data[Formula presented]",

abstract = "Wearable activity monitors are now widely used in behavioral and epidemiological studies to measure physical activity in free-living conditions. Despite the widespread use in research, the development of software to explore the data collected from these devices has been limited. We present acc, a comprehensive, free, and open-source R package to provide a seamless environment for exploring accelerometer data (https://cran.r-project.org/web/packages/acc). In this article, we demonstrate the software for processing, visualizing, and analyzing accelerometer data using real and simulated datasets.",

keywords = "Accelerometer, Physical activity monitoring, Wearable sensor",

author = "Jaejoon Song and Swartz, {Michael D.} and Karen Basen-Engquist",

note = "Funding Information: This study was supported by the National Institutes of Health/ National Cancer Institute, USA through R01 CA 109919 , R25T CA057730 , R25E CA056452 , P30 CA016672 (M. D. Anderson{\textquoteright}s Cancer Center Support Grant and PROSPR Shared Resource), and the Center for Energy Balance in Cancer Prevention and Survivorship, Duncan Family Institute for Cancer Prevention and Risk Assessment, USA . Publisher Copyright: {\textcopyright} 2023",

year = "2023",

month = nov,

doi = "10.1016/j.simpa.2023.100577",

language = "English (US)",

volume = "18",

journal = "Software Impacts",

issn = "2665-9638",

publisher = "Elsevier BV",

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T2 - An R package to process, visualize, and analyze accelerometer data[Formula presented]

AU - Song, Jaejoon

AU - Swartz, Michael D.

AU - Basen-Engquist, Karen

N1 - Funding Information: This study was supported by the National Institutes of Health/ National Cancer Institute, USA through R01 CA 109919 , R25T CA057730 , R25E CA056452 , P30 CA016672 (M. D. Anderson’s Cancer Center Support Grant and PROSPR Shared Resource), and the Center for Energy Balance in Cancer Prevention and Survivorship, Duncan Family Institute for Cancer Prevention and Risk Assessment, USA . Publisher Copyright: © 2023

PY - 2023/11

Y1 - 2023/11

N2 - Wearable activity monitors are now widely used in behavioral and epidemiological studies to measure physical activity in free-living conditions. Despite the widespread use in research, the development of software to explore the data collected from these devices has been limited. We present acc, a comprehensive, free, and open-source R package to provide a seamless environment for exploring accelerometer data (https://cran.r-project.org/web/packages/acc). In this article, we demonstrate the software for processing, visualizing, and analyzing accelerometer data using real and simulated datasets.

AB - Wearable activity monitors are now widely used in behavioral and epidemiological studies to measure physical activity in free-living conditions. Despite the widespread use in research, the development of software to explore the data collected from these devices has been limited. We present acc, a comprehensive, free, and open-source R package to provide a seamless environment for exploring accelerometer data (https://cran.r-project.org/web/packages/acc). In this article, we demonstrate the software for processing, visualizing, and analyzing accelerometer data using real and simulated datasets.

KW - Accelerometer

KW - Physical activity monitoring

KW - Wearable sensor

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DO - 10.1016/j.simpa.2023.100577

M3 - Article

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JO - Software Impacts

JF - Software Impacts

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ER -

acc: An R package to process, visualize, and analyze accelerometer data[Formula presented]

Abstract

Keywords

ASJC Scopus subject areas

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