The rise of smart mobile devices presents increasing opportunities for health monitoring outside the clinic. Through the use of sensors and wearables, innovative Connected Health applications can be developed. In particular, Digital Therapeutics (DT), a type of technology-enabled intervention, can be made possible through continuous data capture, aiding users through gaining feedback on their lifestyle choices and engagement with programs of recovery, and supplementing conventional treatments for chronic disease management such as in diabetes, epilepsy, and mental health. Unfortunately, patient-facing professionals capable of articulating appropriate sensor-enabled solutions, generally lack the full range of skills to develop such systems. A connected health application may involve mobile development, data services, visualisation, machine learning, and sensor signal processing, needing multidisciplinary teams, including professional software engineers. The cost of maintaining a software team across the research and development stages may prove prohibitive for many, hindering innovation. This paper focuses on gathering requirements for  data collection  in mHealth studies, and reports the initial findings after a round of interviews with researchers in areas such as psychology, physiotherapy, neurology, and health promotion education. Those requirements are framed within an existing End User Development (EUD) tool to create mobile apps for the Android platform, the open source project MIT App Inventor. The survey results highlight not only the development work needed for App Inventor to be used as a data collection tool in DT, but also a number of potential security and privacy issues, and the implementation of a  layered  feedback loop with a social aspect at the heart of it.
['José Juan Dominguez Veiga', 'Tomas Ward']
Data collection requirements for mobile connected health: an end user development approach