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可穿戴指环追踪器在临床环境中用于诊断性睡眠测量的性能。

Performance of wearable finger ring trackers for diagnostic sleep measurement in the clinical context.

作者信息

Herberger Sebastian, Aurnhammer Christoph, Bauerfeind Sophie, Bothe Tomas, Penzel Thomas, Fietze Ingo

机构信息

Interdisciplinary Center of Sleep Medicine, Charité University Medicine Berlin, Berlin, Germany.

Mentalab GmbH, Munich, Germany.

出版信息

Sci Rep. 2025 Mar 19;15(1):9461. doi: 10.1038/s41598-025-93774-z.

Abstract

Ring-trackers are a growing consumer wearable category that provide a number of sleep metrics, yet their measurement accuracy remains poorly understood. Previous validation studies have mainly focused on healthy individuals, while a significant part of the potential present and future value lies in applications on non-healthy subjects. To enable applications in research and medical applications, rigorous evaluation of performance in clinical settings against the gold-standard polysomnography is needed. To address this knowledge gap, we investigated how the measurements of three commercially available ring trackers (Oura, SleepOn, Circul) perform against polysomnography in a university sleep lab population with a diverse set sleep-related disorders as well as sleep-unrelated medical conditions. We evaluated individual-level and group-level discrepancies of standard sleep measures and conducted an epoch-by-epoch analysis of sleep staging classification performance using a standardized analysis framework. While average group-level sleep measures are similar (e.g., TST differences between rings and gold standard were below 12 min for the Oura ring), individual-level differences often remained large. Ring-derived sleep metrics were characterized by complex bias, indicating that their correction is non-trivial. Sleep/Wake distinction of the Oura and SleepOn rings reached similar performance as previously reported for healthy individuals (~ 85% accuracy), but was worse for the Circul ring (~ 65% accuracy). Sleep stage classification (Wake, Light, Deep, REM sleep) sensitivity ranged from 0.14 (REM sleep classification of the Circul ring) to 0.58 (Light sleep classification of the SleepOn ring). Across all sleep stages, the Oura and SleepOn ring performed similarly (53.18% and 50.48% accuracy), whereas the Circul ring performed worse (35.06% accuracy). Our findings confirm recent descriptions of device-related bias and additionally uncover practical limitations in the application in a real-world sleep laboratory patient cohort. Critically, while some devices may demonstrate reasonable agreement with PSG on average, this agreement masks substantial individual-level inaccuracies, prohibiting their use in clinical sleep medicine, as accurate assessment of individual nights, including both nights with exceptionally low or high sleep quality and quantity, is essential for patient care.

摘要

指环追踪器是一类不断发展的消费级可穿戴设备,可提供多项睡眠指标,但其测量准确性仍知之甚少。以往的验证研究主要集中在健康个体上,而当前和未来潜在价值的很大一部分在于在非健康受试者中的应用。为了实现研究和医学应用,需要在临床环境中对照金标准多导睡眠图对性能进行严格评估。为了填补这一知识空白,我们调查了三款市售指环追踪器(Oura、SleepOn、Circul)在一所大学睡眠实验室中,针对患有多种与睡眠相关疾病以及与睡眠无关的医疗状况的人群,其测量结果与多导睡眠图相比表现如何。我们评估了标准睡眠指标在个体层面和群体层面的差异,并使用标准化分析框架对睡眠分期分类性能进行了逐时段分析。虽然平均群体层面的睡眠指标相似(例如,Oura指环与金标准之间的总睡眠时间差异低于12分钟),但个体层面的差异往往仍然很大。指环得出的睡眠指标具有复杂的偏差,这表明对其进行校正并非易事。Oura和SleepOn指环的睡眠/清醒区分性能与先前报道的健康个体相似(准确率约为85%),但Circul指环的表现较差(准确率约为65%)。睡眠阶段分类(清醒、浅睡眠、深睡眠、快速眼动睡眠)的敏感度范围从0.14(Circul指环的快速眼动睡眠分类)到0.58(SleepOn指环的浅睡眠分类)。在所有睡眠阶段中,Oura和SleepOn指环的表现相似(准确率分别为53.18%和50.48%),而Circul指环的表现较差(准确率为35.06%)。我们的研究结果证实了近期关于设备相关偏差的描述,并进一步揭示了在实际睡眠实验室患者队列中的应用存在的实际局限性。至关重要的是,虽然一些设备平均而言可能与多导睡眠图显示出合理的一致性,但这种一致性掩盖了个体层面的大量不准确之处,禁止它们在临床睡眠医学中使用,因为准确评估每个夜晚,包括睡眠质量和数量极低或极高的夜晚,对患者护理至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b881/11923143/dc124c9b55b3/41598_2025_93774_Fig1_HTML.jpg

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