The increasing prevalence of smart mobile devices (e.g., smartphones) enables the combined use of ecological momentary assessments (EMA) and mobile crowdsensing (MCS) in the healthcare domain. This combination not only allows researchers to collect ecologically valid data, but also to use smartphones as well as external sensors to capture the context in which these data are collected. By correlating the qualitative longitudinal and ecologically valid EMA assessment data with sensor measurements in mobile apps, new valuable insights about patients can be gained. However, the engineering of software systems that enable both EMA and MCS is a challenging endeavor that is accompanied by a multitude of conceptual, legal, architectural, and technical issues.
This work identifies these issues based on a literature review and the insights gained in several large-scale, long-term mHealth studies. In particular, characteristic requirements for an integrated EMA & MCS platform are elicited in a structured manner and implemented in a technical framework that fosters the evaluation of healthcare data gathered with the platform. Major aspects of the technical framework include the conceptual design of a reference architecture, original implementation concepts, and the comparability of measurements in mobile health app engineering. Altogether, the framework shall serve as basis for the technical support of the entire workflow when realizing EMA & MCS software solutions, from their development to mHealth data analytics.