HOPES -- An Integrative Digital Phenotyping Platform for Data Collection, Monitoring and Machine Learning
August 28, 2020 Β· Declared Dead Β· π arXiv.org
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Authors
Xuancong Wang, Nikola Vouk, Creighton Heaukulani, Thisum Buddhika, Wijaya Martanto, Jimmy Lee, Robert JT Morris
arXiv ID
2008.12431
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
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.
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