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dc.contributor.authorSteel, Chelsea
dc.contributor.authorCrist, Katie
dc.contributor.authorGrimes, Amanda
dc.contributor.authorBejarano, Carolina
dc.contributor.authorOrtega, Adrian
dc.contributor.authorHibbing, Paul R.
dc.contributor.authorSchipperijn, Jasper
dc.contributor.authorCarlson, Jordan A.
dc.identifier.citationSteel, C., Crist, K., Grimes, A., Bejarano, C., Ortega, A., Hibbing, P. R., Schipperijn, J., & Carlson, J. A. (2021). Validity of a Global Positioning System-Based Algorithm and Consumer Wearables for Classifying Active Trips in Children and Adults. Journal for the measurement of physical behaviour, 4(4), 321–332.
dc.descriptionAccepted author manuscript version reprinted, by permission, from [Journal for the Measurement of Physical Behaviour, 2021, Volume 4: Issue 4: pp. 321–332, © Human Kinetics, Inc.en_US
dc.description.abstractObjective: To investigate the convergent validity of a global positioning system (GPS)-based and two consumer-based measures with trip logs for classifying pedestrian, cycling, and vehicle trips in children and adults. Methods: Participants (N = 34) wore a Qstarz GPS tracker, Fitbit Alta, and Garmin vivosmart 3 on multiple days and logged their outdoor pedestrian, cycling, and vehicle trips. Logged trips were compared with device-measured trips using the Personal Activity Location Measurement System (PALMS) GPS-based algorithms, Fitbit’s SmartTrack, and Garmin’s Move IQ. Trip- and day-level agreement were tested. Results: The PALMS identified and correctly classified the mode of 75.6%, 94.5%, and 96.9% of pedestrian, cycling, and vehicle trips (84.5% of active trips, F1 = 0.84 and 0.87) as compared with the log. Fitbit and Garmin identified and correctly classified the mode of 26.8% and 17.8% (22.6% of active trips, F1 = 0.40 and 0.30) and 46.3% and 43.8% (45.2% of active trips, F1 = 0.58 and 0.59) of pedestrian and cycling trips. Garmin was more prone to false positives (false trips not logged). Day-level agreement for PALMS and Garmin versus logs was favorable across trip modes, though PALMS performed best. Fitbit significantly underestimated daily cycling. Results were similar but slightly less favorable for children than adults. Conclusions: The PALMS showed good convergent validity in children and adults and were about 50% and 27% more accurate than Fitbit and Garmin (based on F1). Empirically-based recommendations for improving PALMS’ pedestrian classification are provided. Since the consumer devices capture both indoor and outdoor walking/running and cycling, they are less appropriate for trip-based research.en_US
dc.publisherHuman Kineticsen_US
dc.rights© Human Kinetics, Inc.en_US
dc.titleValidity of a Global Positioning System-Based Algorithm and Consumer Wearables for Classifying Active Trips in Children and Adultsen_US
kusw.kuauthorBejarano, Carolina
kusw.kuauthorOrtega, Adrian
kusw.kudepartmentClinical Child Psychology Programen_US
kusw.oanotesPer Sherpa Romeo 03/02/2023:

Journal for the Measurement of Physical Behaviour [Open panel below]Publication Information TitleJournal for the Measurement of Physical Behaviour [English] ISSNs Print: 2575-6605 Electronic: 2575-6613 URL PublishersHuman Kinetics [Commercial Publisher] [Open panel below]Publisher Policy Open Access pathways permitted by this journal's policy are listed below by article version. Click on a pathway for a more detailed view.

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None Institutional Repository, Institutional Website, Author's Homepage, +4 EmbargoNo Embargo Copyright OwnerPublishers Location Academic Social Network Author's Homepage Institutional Repository Institutional Website Named Academic Social Network (, ResearchGate, Mendeley) Conditions Publisher copyright and source must be acknowledged Must link to publisher version with DOI Set statement to accompany deposit (see policy) NotesAfter publication, Accepted version must be in PDF or other image capturing format
kusw.oaversionScholarly/refereed, author accepted manuscripten_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US

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