Sleep-tracking devices, particularly within the consumer sleep technology (CST) space, are increasingly used in both research and clinical settings, providing new opportunities for large-scale data collection in highly ecological conditions. Due to the fast pace of the CST industry combined with the lack of a standardized framework to evaluate the performance of sleep trackers, their accuracy and reliability in measuring sleep remains largely unknown. Here, we provide a step-by-step analytical framework for evaluating the performance of sleep trackers (including standard actigraphy), as compared to gold-standard polysomnography (PSG) or other reference methods. The analytical guidelines are based on recent recommendations for evaluating and using CST from our group and others (de Zambotti, Cellini, Goldstone, Colrain & Baker, 2019; Depner et al., 2019), and include raw data organization as well as critical analytical procedures, including discrepancy analysis, Bland-Altman plots, and epoch-by-epoch analysis. Analytical steps are accompanied by open-source R functions (depicted at https://sri-human-sleep.github.io/sleep-trackers-performance/AnalyticalPipeline_v1.0.0.html). In addition, an empirical sample dataset is used to describe and discuss the main outcomes of the proposed pipeline. The guidelines and the accompanying functions are aimed at standardizing the testing of CSTs performance, to not only increase the replicability of validation studies, but also to provide ready-to-use tools to researchers and clinicians. All in all, this work can help to increase the efficiency, interpretation, and quality of validation studies, and to improve the informed adoption of CST in research and clinical settings.

中文翻译：

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用于测试睡眠跟踪技术性能的标准化框架：分步指南和开源代码

睡眠跟踪设备，特别是在消费者睡眠技术 (CST) 领域，越来越多地用于研究和临床环境，为在高度生态条件下的大规模数据收集提供了新的机会。由于 CST 行业的快速发展加上缺乏评估睡眠追踪器性能的标准化框架，它们在测量睡眠方面的准确性和可靠性在很大程度上仍然未知。在这里，与黄金标准多导睡眠图 (PSG) 或其他参考方法相比，我们提供了一个分步分析框架，用于评估睡眠跟踪器（包括标准活动记录）的性能。分析指南基于我们小组和其他人最近关于评估和使用 CST 的建议（de Zambotti、Cellini、Goldstone、Colrain & Baker，2019 年；Depner et al., 2019)，包括原始数据组织以及关键分析程序，包括差异分析、Bland-Altman 图和逐纪元分析。分析步骤伴随着开源 R 函数（在 https://sri-human-sleep.github.io/sleep-trackers-performance/AnalyticalPipeline_v1.0.0.html 中描述）。此外，经验样本数据集用于描述和讨论拟议管道的主要结果。该指南和附带的功能旨在标准化 CST 性能的测试，不仅提高验证研究的可重复性，而且还为研究人员和临床医生提供即用型工具。总而言之，这项工作有助于提高验证研究的效率、解释和质量，