An open-source tool to identify active travel from hip-worn accelerometer, GPS and GIS data.

ABSTRACT:

Background

Increases in physical activity through active travel have the potential to have large beneficial effects on populations, through both better health outcomes and reduced motorized traffic. However accurately identifying travel mode in large datasets is problematic. Here we provide an open source tool to quantify time spent stationary and in four travel modes(walking, cycling, train, motorised vehicle) from accelerometer measured physical activity data, combined with GPS and GIS data.

Methods

The Examining Neighbourhood Activities in Built Living Environments in London study evaluates the effect of the built environment on health behaviours, including physical activity. Participants wore accelerometers and GPS receivers on the hip for 7 days. We time-matched acceler

SUBMITTER: Procter DS 

PROVIDER: S-EPMC6150970 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature