Objective: GPS data can add context to physical activity data, and have previously been integrated with epoch-based physical activity data. The current study aimed to develop a framework for integrating GPS data and event-based physical activity data (suitable for assessing patterns of behaviour). Methods: A convenience dataset of concurrent GPS (AMOD) and physical activity (activPAL) data were collected from 69 adults. GPS data was (semi-) regularly sampled every 5 seconds. The physical activity data output was presented as walking events, which are continuous periods of walking with a time-stamped start time and duration (to nearest 0.1s). GPS outcome measures and the potential correspondence of their timing with walking events were identified and a framework was developed describing data integration for each combination of GPS outcome and walking event correspondence. Results: GPS outcome measures were categorised as those deriving from a single GPS point (e.g. location), or from the difference between successive GPS points (e.g. distance), and could be categorical, scale or rate outcomes. Walking events were categorised as having zero (13% of walking events, 3% of walking duration), or one or more (52% of walking events, 75% of walking duration) GPS points occurring during the event. Additionally, some walking events did not have GPS points suitably close to allow calculation of outcome measures (31% of walking events, 22% of walking duration). The framework required different integration approaches for each GPS outcome type, and walking events containing zero or more than one GPS points.
|Journal||Journal for the Measurement of Physical Behaviour|
|Publication status||Accepted/In press - 23 Sep 2020|
- physical activity, GPS, accelerometer, event-based data, methods