Audapret: Towards a Cloud Architecture Supporting Multi-Device Research Studies

Abstract

Recent improvements in the functional range and measurement accuracy of commercially available biosignal measurement devices enable cost-effective human trials with large numbers of participants. Biosignals can be tracked outside the research institution, with only minor restrictions in the daily activities of the study participants, compared to stationary measuring devices. However, there is a lack of data acquisition systems supporting the use of several different devices needed, so that the collected data from measurement devices have to be processed manually. Researchers must also abide by strict legal regulations when handling health-related data of study participants, which is often cumbersome and requires additional time-consuming efforts. To address these challenges, this paper proposes the AUtomatic DAta Processing of REsearch Trials (AUDAPRET) architecture, which enables researchers to conduct trials requiring health-related data of participants in a less time-consuming and legally compliant manner. AUDAPRET is designed in such a way that study participants retain full control over their data and the access rights of anyone requesting access.