This paper presents an approach for describing personal movement patterns for typical daily activities undertaken by subjects within free living structured environments (e.g. home or office). Conventionally this requires specialized technology for personal movement monitoring involving measurement of location and motion, and results in the collection of large datasets in order to provide sufficient descriptive power. Here we advocate the preferential observation of sentinel activities based on the expectation of routine and repetitive personal movement episodes, which can be considered as ‘habits’. These identified habitual patterns provide a useful context for understanding the dominant characteristics of typical daily activities, enabling purposeful design of behaviour change interventions to improve healthy living. This approach has been applied here to office stepcount data from consumer wearables.