JTrack：用于神经和精神疾病远程监测的数字生物标志物平台
JTrack: A Digital Biomarker Platform for Remote Monitoring in Neurological and Psychiatric Diseases
摘要：
目的：通过智能手机收集的健康相关数据为临床评估提供了一种有前途的补充方法。在这里，我们介绍JTrack平台作为一个安全，可靠和可扩展的开源解决方案，用于日常生活和数字表型的远程监控。方法：JTrack由一个基于Android的智能手机应用程序和一个基于Web的项目管理仪表板组成。可以以主动或被动模式收集来自运动传感器、社交和身体活动以及地理位置信息的各种匿名测量。仪表板还提供了管理工具，用于监测和管理研究间的数据汇集。为了便于扩展、再现、数据管理和共享，我们将DataLad集成为数据管理基础设施。JTrack的开发符合安全、隐私和通用数据保护条例（GDPR）的要求。结果如下：JTrack是一个开源（在开源Apache 2.0许可下发布）平台，用于远程评估神经学，精神病学和其他适应症的数字生物标志物（DB）。这里介绍了JTrack平台的主要组件以及使用JTrack收集数据的示例。结论：基于智能手机的数字生物标志物数据可以为健康和疾病的日常生活行为提供有价值的见解。JTrack为收集此类数据提供了一个简单可靠的开源解决方案。
英文摘要：
Objective: Health-related data being collected by smartphones offer a promising complementary approach to in-clinic assessments. Here we introduce the JTrack platform as a secure, reliable and extendable open-source solution for remote monitoring in daily-life and digital phenotyping. Method: JTrack consists of an Android-based smartphone application and a web-based project management dashboard. A wide range of anonymized measurements from motion-sensors, social and physical activities and geolocation information can be collected in either active or passive modes. The dashboard also provides management tools to monitor and manage data collection across studies. To facilitate scaling, reproducibility, data management and sharing we integrated DataLad as a data management infrastructure. JTrack was developed to comply with security, privacy and the General Data Protection Regulation (GDPR) requirements. Results: JTrack is an open-source (released under open-source Apache 2.0 licenses) platform for remote assessment of digital biomarkers (DB) in neurological, psychiatric and other indications. The main components of the JTrack platform and examples of data being collected using JTrack are presented here. Conclusion: Smartphone-based Digital Biomarker data may provide valuable insight into daily life behaviour in health and disease. JTrack provides an easy and reliable open-source solution for collection of such data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
