PhysioTag: An Open-Source Platform for Collaborative Annotation of Physiological Waveforms

To develop robust algorithms for automated diagnosis of medical conditions such as cardiac arrhythmias, researchers require large collections of data with human expert annotations. Currently, there is a lack of accessible, open-source platforms for human experts to collaboratively develop these annotated datasets through a web interface. In this work, we developed a flexible, generalizable, web-based framework to enable multiple users to create and share annotations on multi-channel physiological waveforms. The software is simple to install and offers a range of features, including: user management and task customization; a programmatic interface for data import and export; and a leaderboard for annotation progress tracking.

为构建用于自动诊断诸如心律失常等医疗状况的稳健算法，研究人员需要大量带有人类专家标注的数据集。目前，缺乏可供人类专家通过网页界面协作开发这些标注数据集的易于访问的开源平台。在本研究中，我们开发了一个灵活、通用的基于网络的框架，以允许多用户创建和共享对多通道生理波形进行标注。该软件安装简便，并提供了一系列功能，包括：用户管理与任务定制；数据导入和导出的编程接口；以及用于跟踪标注进度的排行榜。