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.
@article{arxiv.2008.12431,
title = {HOPES -- An Integrative Digital Phenotyping Platform for Data Collection, Monitoring and Machine Learning},
author = {Xuancong Wang and Nikola Vouk and Creighton Heaukulani and Thisum Buddhika and Wijaya Martanto and Jimmy Lee and Robert JT Morris},
journal= {arXiv preprint arXiv:2008.12431},
year = {2020}
}
Comments
This document includes both the main paper and its supplementary material