Peripheral psychophysiological measures have been used to inform our understanding of symptoms in mental health disorders, to predict treatment response, and to investigate mechanisms of treatment change. Typically, psychophysiological measures are laboratory-based, yielding precise, reliable, but infrequent assessment. Wearable technology can provide new ways to understand physiology beyond the laboratory. In order to harness this potential, we need to develop methods to monitor patients unobtrusively, with minimal patient burden, and due concern for privacy issues. Furthermore, we need to ensure that methods developed are acceptable to patients, as well as being engaging to use. In this interdisciplinary project, we adopt approaches from human-computer interaction, where target users are involved in the design and refinement of our technological solutions. The engineering challenge involves building a smartphone application that can gather and analyse physiological and behavioural data securely. From testing wearable device capacities, we suggest that resting sleeping heart rate may comprise a measurable index of physiological functioning. This measure, together with behavioural indices, such as daily rhythmic patterns of activity, may provide new insights into patient functioning. Furthermore, high-frequency recording, over extended periods as available from wearable devices, will provide us with a temporally-sensitive means to investigate treatment effects.