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HOPES：一个用于数据收集、监测和机器学习的综合数字表型平台。

HOPES: An Integrative Digital Phenotyping Platform for Data Collection, Monitoring, and Machine Learning.

机构信息

Office for Healthcare Transformation, Ministry of Health, Singapore, Singapore.

Institute of Mental Health, Singapore, Singapore.

出版信息

J Med Internet Res. 2021 Mar 15;23(3):e23984. doi: 10.2196/23984.

DOI:10.2196/23984
PMID:33720028
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8074871/
Abstract

The collection of data from a personal digital device to characterize current health conditions and behaviors that determine how an individual's health will evolve has been called digital phenotyping. In this paper, we describe the development of and early experiences with a 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 wider range of data collection, including the integration of wearable devices and further sensor collection from smartphones. Requirements were partly derived from a concurrent clinical trial for schizophrenia that required the development of significant capabilities in HOPES for 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 research study operations and clinical care. A test use case for HOPES was described by analyzing the digital behavior of 22 participants during the SARS-CoV-2 pandemic.

摘要

从个人数字设备中收集数据，以描述当前的健康状况和行为，从而确定个体的健康状况将如何发展，这被称为数字表型。在本文中，我们描述了一个全面的数字表型平台的开发和早期经验：通过积极参与和自我赋权实现健康结果（HOPES）。HOPES 基于开源的 Beiwe 平台，但增加了更广泛的数据收集，包括可穿戴设备的集成以及来自智能手机的进一步传感器收集。需求部分源于同时进行的精神分裂症临床试验，该试验要求根据公共云和内部部署操作的精心组合，在 HOPES 中开发安全、隐私、易用性和可扩展性方面的重要功能。我们描述了用于清理、处理、呈现和分析数据的新数据管道。这包括一组根据研究操作和临床护理需求定制的仪表板。通过分析 22 名参与者在 SARS-CoV-2 大流行期间的数字行为，描述了 HOPES 的一个测试用例。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20aa/8074871/88a23e16c902/jmir_v23i3e23984_fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20aa/8074871/515343435250/jmir_v23i3e23984_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20aa/8074871/b444113316f4/jmir_v23i3e23984_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20aa/8074871/51d6a6477400/jmir_v23i3e23984_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20aa/8074871/339aa248ffec/jmir_v23i3e23984_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20aa/8074871/95b6613a989f/jmir_v23i3e23984_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20aa/8074871/88a23e16c902/jmir_v23i3e23984_fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20aa/8074871/515343435250/jmir_v23i3e23984_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20aa/8074871/b444113316f4/jmir_v23i3e23984_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20aa/8074871/51d6a6477400/jmir_v23i3e23984_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20aa/8074871/339aa248ffec/jmir_v23i3e23984_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20aa/8074871/95b6613a989f/jmir_v23i3e23984_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20aa/8074871/88a23e16c902/jmir_v23i3e23984_fig6.jpg

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