The quantification of Physical Behaviour is important to understand the relationship between patterns of free-living physical activities and health outcomes. In addition these measures can be used to evaluate clinical interventions and public health campaigns. Traditional sources of context rich information on free-living physical activities have relied on self-report or on direct observation. As defined in the SOPARC model the multitude of possible physical activities can be distilled down to a primary classification of lying, sitting, standing, walking and vigorous activities. Accelerometer data can provide a robust classification into similar activity categories using an event-based approach. By quantifying the patterns of these free-living physical activities we can generate objective measures of a subject’s Physical Behaviour. This workshop explored novel ways of analysing free-living physical activity derived from accelerometer data and how, by quantifying Physical Behaviours, we can more effectively understand our populations and evaluate interventions. The workshop began with a structured discussion using exemplar data to outline the key concepts. Participants were split into groups that  analysed a sample data set showing how contextual information can be inferred.