HOPES -- An Integrative Digital Phenotyping Platform for Data Collection, Monitoring and Machine Learning
This is an incremental platform development for data collection and monitoring in clinical research, particularly for schizophrenia trials.
The authors developed HOPES, a digital phenotyping platform that extends the open-source Beiwe platform by integrating wearable and smartphone sensor data, and tested it by analyzing digital behaviors of 20 participants during the COVID-19 pandemic.
We describe the development of, and early experiences with, comprehensive Digital Phenotyping platform: Health Outcomes through Positive Engagement and Self-Empowerment (HOPES). HOPES is based on the open-source Beiwe platform but adds a much wider range of data collection, including the integration of wearable data sources and further sensor collection from the smartphone. Requirements were in part derived from a concurrent clinical trial for schizophrenia. This trial required development of significant capabilities in HOPES in security, privacy, ease-of-use and scalability, based on a careful combination of public cloud and on-premises operation. We describe new data pipelines to clean, process, present and analyze data. This includes a set of dashboards customized to the needs of the research study operations and for clinical care. A test use of HOPES is described by analyzing the digital behaviors of 20 participants during the SARS-CoV-2 pandemic.