Biometrics of complete human pregnancy recorded by wearable devices

IF 12.4 1区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Lauryn Keeler Bruce, Dalila González, Subhasis Dasgupta, Benjamin L. Smarr
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Abstract

In the United States, normal-risk pregnancies are monitored with the recommended average of 14 prenatal visits. Check-ins every few weeks are the standard of care. This low time resolution and reliance on subjective feedback instead of direct physiological measurement, could be augmented by remote monitoring. To date, continuous physiological measurements have not been characterized across all of pregnancy, so there is little basis of comparison to support the development of the specific monitoring capabilities. Wearables have been shown to enable the detection and prediction of acute illness, often faster than subjective symptom reporting. Wearables have also been used for years to monitor chronic conditions, such as continuous glucose monitors. Here we perform a retrospective analysis on multimodal wearable device data (Oura Ring) generated across pregnancy within 120 individuals. These data reveal clear trajectories of pregnancy from cycling to conception through postpartum recovery. We assessed individuals in whom pregnancy did not progress past the first trimester, and found associated deviations, corroborating that continuous monitoring adds new information that could support decision-making even in the early stages of pregnancy. By contrast, we did not find significant deviations between full-term pregnancies of people younger than 35 and of people with “advanced maternal age”, suggesting that analysis of continuous data within individuals can augment risk assessment beyond standard population comparisons. Our findings demonstrate that low-cost, high-resolution monitoring at all stages of pregnancy in real-world settings is feasible and that many studies into specific demographics, risks, etc., could be carried out using this newer technology.

Abstract Image

Abstract Image

通过可穿戴设备记录人类怀孕全过程的生物特征
在美国,正常风险妊娠的监测建议是平均 14 次产前检查。每隔几周检查一次是护理标准。这种低时间分辨率和依赖主观反馈而非直接生理测量的做法,可以通过远程监测来加强。迄今为止,连续的生理测量还没有贯穿整个孕期,因此几乎没有比较的基础来支持特定监测功能的开发。可穿戴设备已被证明能够检测和预测急性疾病,通常比主观症状报告更快。多年来,可穿戴设备还被用于监测慢性疾病,如连续血糖监测仪。在此,我们对 120 人怀孕期间产生的多模态可穿戴设备数据(Oura Ring)进行了回顾性分析。这些数据揭示了从骑自行车到受孕再到产后恢复的清晰怀孕轨迹。我们对怀孕未超过前三个月的孕妇进行了评估,发现了相关的偏差,这证实了持续监测增加了新的信息,即使在怀孕早期也能为决策提供支持。相比之下,我们没有发现 35 岁以下的足月妊娠和 "高龄产妇 "的足月妊娠之间存在明显偏差,这表明对个体内部的连续数据进行分析可以增强风险评估,而不是进行标准的人群比较。我们的研究结果表明,在现实世界中对妊娠各个阶段进行低成本、高分辨率的监测是可行的,而且可以利用这种较新的技术对特定的人口统计学、风险等进行许多研究。
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来源期刊
CiteScore
25.10
自引率
3.30%
发文量
170
审稿时长
15 weeks
期刊介绍: npj Digital Medicine is an online open-access journal that focuses on publishing peer-reviewed research in the field of digital medicine. The journal covers various aspects of digital medicine, including the application and implementation of digital and mobile technologies in clinical settings, virtual healthcare, and the use of artificial intelligence and informatics. The primary goal of the journal is to support innovation and the advancement of healthcare through the integration of new digital and mobile technologies. When determining if a manuscript is suitable for publication, the journal considers four important criteria: novelty, clinical relevance, scientific rigor, and digital innovation.
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