Abstract
Most human subjects, research requires data collection by contacting local participants who visit a research site. This is costly, time-consuming, and decreases subject retention with each required visit. Additionally, studies require increasingly large troves of data collected continuously during their typical daily lives using sensors (e.g., fitness trackers). Long-term, continuous collection is becoming more feasible as smartphones become ubiquitous. However, data is highly detailed, and identifiable even when de-identified according to typical practice (e.g., keeping names separate from study data). To enable remote collection of these rich data sets while ensuring privacy, we built a system to allow secure and fully human-out-of-the-loop participant recruitment, screening, onboarding, data collection on smartphones, data transmission to the cloud, data security in the cloud, and data access by analysis and modeling teams. We believe this approach is applicable to a large number of researchers, both within universities and in industry.
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