从可穿戴设备收集的生理数据识别和预测炎症性肠病爆发
Robert P Hirten1, Matteo Danieletto2, Milagros Sanchez-Mayor3
1The Dr. Henry D. Janowitz Division of Gastroenterology, Icahn School of Medicine at Mount Sinai, New York, New York; The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York; Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, New York.
可穿戴设备可以跟踪与炎症性肠病 (IBD) 活动相关的生理变化. 这些指标,包括心率和HRV,可以提前7周预测IBD爆发.
科学领域:
- 生物医学工程 生物医学工程
- 数字健康数字健康
- 胃肠病学 胃肠病学
背景情况:
- 可穿戴设备非侵入性地监测生理信号.
- 几个生理参数与炎症性肠病 (IBD) 活动相关.
研究的目的:
- 评估生理指标和IBD爆发之间的关联.
- 确定这些指标在IBD爆发之前如何变化.
主要方法:
- 参与者使用可穿戴设备 (Apple Watch,Fitbit,Oura Ring) 来收集HR,RHR,HRV,步骤和氧化量.
- 还收集了疾病活动调查和护理标准生物标志物.
- 统计模型分析了关联和预测能力的生理数据.
主要成果:
- 在爆发和缓解状态之间,循环 HRV 模式有所不同.
- 在爆发期间观察到HR和RHR的升高和步骤的减少.
- 在症状和炎症性IBD爆发前7周,生理指标发生变化.
结论:
- 来自可穿戴设备的纵向数据可以识别IBD爆发.
- 可穿戴设备指标显示了监测和预测IBD活动的潜力.
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