A Design Science methodology was used to create a context recognition method for data from a single, wearable inertial sensor. The sensor was worn on riders right wrists. The data was associated with a rider mounting their horse within the traditional European riding style. Data was collected from 20 participants, 2 laboratory and 55 real-life data collection sessions. A manual human pattern matching search method was applied to 2 laboratory and 7 real life datasets during recognition training and two features, one within the accelerometer data and the other within the gyroscope data were identified. The method was evaluated by searching for these two features within 15 alternate datasets. The method was successful in recognising features that could be associated with mounting where riders used a hand-on-cantle mounting technique. The method did not consistently recognise features that could be associated with mounting when riders used a hand-on-front of saddle mounting technique. The researcher concluded that manual heuristic human pattern search and matching methods could be used to distinguish mounting in 11 out of 12 cases where the domain was restricted to hand-on-cantle mounting techniques and that such methods may possibly be generalised to include other mounting techniques and other contexts. The researcher also concluded that a single compound sensor can, in some instances, provide enough information within a restricted domain to enable successful context recognition.