Current advances in mobile and sensor technologies have provided new opportunities for many fields of research, especially in healthcare. Chronic pain is one such field, where low back pain is a common problem that affects 20% of the population, and is also a major contributor to disability. Unfortunately, not much is yet known about the contributing factors, nor the nature of low back pain itself. Existing research does not collect data frequently - with most studies only collecting pain data monthly, or half yearly. Experts agree that there is a need for the increase in frequency of data collection, and to study the context of the patient’s pain experience in order to understand the nature of pain. Currently, there are not any research that attempts to include the context around the patient’s pain experience, to collect and analyze data for correlations on an individual patient basis. This research will propose a context-aware pain trajectory approach capitalizing on the opportunities that arise from advances in mobile and sensor technologies, to increase the frequency of data collection, and enable the collection and integration of the patient’s context into current low back pain models using day to day pain trajectories.