Publication | Closed Access
Identification and Classification of Usage Patterns in Long-Term Activity Tracking
71
Citations
25
References
2017
Year
Unknown Venue
Physical ActivityEngineeringWearable TechnologyBehavior MonitoringHuman MonitoringKinesiologyInformation RetrievalData ScienceData MiningActivity TrackersActivity Tracker UsePublic HealthHealth SciencesAssistive TechnologyHealth PolicyUser Behavior ModelingKnowledge DiscoveryTemporal Pattern RecognitionComputer ScienceMobile ComputingUsage PatternsMobile SensingHealth MonitoringTechnologyGeneral Tracker UseActivity RecognitionMobile Health
Activity trackers are frequently used in health and well-being, but their application in effective interventions is challenging. While research for reasons of use and non-use is ongoing, little is known about the way activity trackers are used in everyday life and over longer periods. We analyzed data of 104 individuals over 14,413 use days, and in total over 2.5 years. We describe general tracker use, periodic changes and overall changes over time, and identify characteristic patterns. While the use of trackers shows large individual heterogeneity, from our findings we could identify and classify general patterns for activity tracker use such as try-and-drop, slow-starter, experimenter, hop-on hop-off, intermittent and power user. Our findings contribute to the body of knowledge towards the successful design of effective health technologies, health interventions, and long-term health applications.
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