Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information.
Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information.
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DOI：
10.1371/journal.pbio.2001402
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发表时间：
2017-01
期刊：
影响因子：
9.8
通讯作者：
Snyder MP
中科院分区：
文献类型：
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作者：
Li X;Dunn J;Salins D;Zhou G;Zhou W;Schüssler-Fiorenza Rose SM;Perelman D;Colbert E;Runge R;Rego S;Sonecha R;Datta S;McLaughlin T;Snyder MP
新一波便携式生物传感器允许频繁测量与健康相关的生理学。我们研究了这些设备在各种活动中监测人体生理变化的用途，以及它们在管理健康和诊断和分析疾病中的作用。通过记录多达43人的超过250，000次日常测量，我们发现了生理参数的个性化昼夜节律差异，复制了以前的生理发现。有趣的是，我们发现在特定的环境中，如航空公司的航班（降低外周毛细血管血氧饱和度[SpO 2]和增加辐射暴露）的显着变化。这些事件与生理宏观表型（如疲劳）相关，提供了高空飞行中压力/氧气降低与疲劳之间的强烈关联。重要的是，我们将生物传感器信息与频繁的医学测量相结合，并进行了两个重要的观察：首先，可穿戴设备在识别莱姆病和炎症反应的早期迹象方面很有用;我们使用这些信息开发了一个个性化的，基于活动的标准化框架，以从纵向数据中识别异常生理信号，从而进行简单的疾病检测。其次，可穿戴设备可以区分胰岛素敏感和胰岛素抵抗个体之间的生理差异。总体而言，这些结果表明，便携式生物传感器提供了有用的信息，用于监测个人活动和生理，并可能在管理健康和使负担得起的医疗保健获得传统上受社会经济阶层或偏远地区限制的群体发挥重要作用。新一波可穿戴传感器允许频繁和连续地测量身体功能（生理学），包括心率、皮肤温度、血氧水平和身体活动。我们研究了可穿戴传感器跟踪一天中，疾病和其他活动期间发生的生理变化的能力。来自这些传感器的数据揭示了日常活动模式的个性化差异。有趣的是，我们发现在特定的环境中，如航空公司的航班，发生了惊人的变化。在高海拔飞行期间，血氧水平下降，这种下降与疲劳有关。通过将传感器信息与频繁的医疗测量相结合，我们得出了两个重要的与健康相关的观察结果。首先，可穿戴传感器在识别莱姆病和炎症的发病方面很有用。根据这一观察，我们开发了一种使用这种传感器进行个性化疾病检测的计算算法。其次，我们发现可穿戴传感器可以揭示胰岛素敏感者和胰岛素抵抗者之间的生理差异，从而提高了这些传感器有助于检测2型糖尿病风险的可能性。总的来说，这些结果表明，可穿戴传感器提供的信息是生理上有意义的和可操作的。可穿戴传感器可能在管理健康方面发挥重要作用。
A new wave of portable biosensors allows frequent measurement of health-related physiology. We investigated the use of these devices to monitor human physiological changes during various activities and their role in managing health and diagnosing and analyzing disease. By recording over 250,000 daily measurements for up to 43 individuals, we found personalized circadian differences in physiological parameters, replicating previous physiological findings. Interestingly, we found striking changes in particular environments, such as airline flights (decreased peripheral capillary oxygen saturation [SpO2] and increased radiation exposure). These events are associated with physiological macro-phenotypes such as fatigue, providing a strong association between reduced pressure/oxygen and fatigue on high-altitude flights. Importantly, we combined biosensor information with frequent medical measurements and made two important observations: First, wearable devices were useful in identification of early signs of Lyme disease and inflammatory responses; we used this information to develop a personalized, activity-based normalization framework to identify abnormal physiological signals from longitudinal data for facile disease detection. Second, wearables distinguish physiological differences between insulin-sensitive and -resistant individuals. Overall, these results indicate that portable biosensors provide useful information for monitoring personal activities and physiology and are likely to play an important role in managing health and enabling affordable health care access to groups traditionally limited by socioeconomic class or remote geography. A new wave of wearable sensors allows frequent and continuous measurements of body functions (physiology), including heart rate, skin temperature, blood oxygen levels, and physical activity. We investigated the ability of wearable sensors to follow physiological changes that occur over the course of a day, during illness and other activities. Data from these sensors revealed personalized differences in daily patterns of activities. Interestingly, we discovered striking changes in particular environments such as airline flights. Blood oxygen levels decreased during high-altitude flights, and this decrease was associated with fatigue. By combining sensor information with frequent medical measurements, we made two important health-related observations. First, wearable sensors were useful in identifying the onset of Lyme disease and inflammation. From this observation, we then developed a computational algorithm for personalized disease detection using such sensors. Second, we found that wearable sensors can reveal physiological differences between insulin-sensitive and insulin-resistant individuals, raising the possibility that these sensors could help detect risk for type 2 diabetes. Overall, these results indicate that the information provided by wearable sensors is physiologically meaningful and actionable. Wearable sensors are likely to play an important role in managing health.