GGIR: A Research Community–Driven Open Source R Package for Generating Physical Activity and Sleep Outcomes From Multi-Day Raw Accelerometer Data

Migueles, Jairo H.; Rowlands, Alex V.; Huber, Florian; Sabia, Sèverine; Hees, Vincent T. van

doi:10.1123/jmpb.2018-0063

articleJournal for the Measurement of Physical BehaviourSep 1, 2019HYBRID OA

GGIR: A Research Community–Driven Open Source R Package for Generating Physical Activity and Sleep Outcomes From Multi-Day Raw Accelerometer Data

JHJairo H. Migueles AVAlex V. Rowlands FHFlorian Huber SSSèverine Sabia VTVincent T. van Hees

Universidad de Granada · University of Leicester · +3 more institutions

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Abstract

Recent technological advances have transformed the research on physical activity initially based on questionnaire data to the most recent objective data from accelerometers. The shift to availability of raw accelerations has increased measurement accuracy, transparency, and the potential for data harmonization. However, it has also shifted the need for considerable processing expertise to the researcher. Many users do not have this expertise. The R package GGIR has been made available to all as a tool to convermulti-day high resolution raw accelerometer data from wearable movement sensors into meaningful evidence-based outcomes and insightful reports for the study of human daily physical activity and sleep.…

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946

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FWCI: 39.01
Percentile: 100%
References: 34

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Topics & keywords

Topics

Keywords

Raw data
Computer science
Harmonization
Accelerometer
Transparency (behavior)
Wearable computer
Physical activity
Data science

UN Sustainable Development Goals

Industry, innovation and infrastructure

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