Sleep and physical activity are human behaviors that play a major role in our health. Poor sleep or lack of physical activity have been found to increase health risks and reduce quality of life. The rapid adoption and evolution of pervasive computing systems, both in the health and wellness domain, are creating a new data-intensive context in which we can learn about the sleep and physical activity patterns of individuals. In this paper we provide an overview of the toolkit we have developed to conduct research on personal health data about sleep and physical activity. This toolkit has been used to develop predictive models of sleep quality based on wearable data, and also to create visualizations of data to help healthcare professionals in making decisions.