Li Huijie, Yuan Jianhe, Fennell Gavin, Abdulla Vagif, Nistala Ravi, Dandachi Dima, Ho Dominic K C, Zhang Yi
Department of Biomedical Engineering and the Institute of Materials Science, University of Connecticut, Storrs, Connecticut 06269, USA.
Department of Electrical Engineering and Computer Science, University of Missouri-Columbia, Columbia, Missouri 65211, USA.
Biophys Rev (Melville). 2023 Jul 19;4(3):031302. doi: 10.1063/5.0140900. eCollection 2023 Sep.
The COVID-19 pandemic has changed the lives of many people around the world. Based on the available data and published reports, most people diagnosed with COVID-19 exhibit no or mild symptoms and could be discharged home for self-isolation. Considering that a substantial portion of them will progress to a severe disease requiring hospitalization and medical management, including respiratory and circulatory support in the form of supplemental oxygen therapy, mechanical ventilation, vasopressors, etc. The continuous monitoring of patient conditions at home for patients with COVID-19 will allow early determination of disease severity and medical intervention to reduce morbidity and mortality. In addition, this will allow early and safe hospital discharge and free hospital beds for patients who are in need of admission. In this review, we focus on the recent developments in next-generation wearable sensors capable of continuous monitoring of disease symptoms, particularly those associated with COVID-19. These include wearable non/minimally invasive biophysical (temperature, respiratory rate, oxygen saturation, heart rate, and heart rate variability) and biochemical (cytokines, cortisol, and electrolytes) sensors, sensor data analytics, and machine learning-enabled early detection and medical intervention techniques. Together, we aim to inspire the future development of wearable sensors integrated with data analytics, which serve as a foundation for disease diagnostics, health monitoring and predictions, and medical interventions.
新冠疫情改变了全球许多人的生活。根据现有数据和已发表的报告,大多数新冠确诊患者没有症状或症状轻微,可出院居家自我隔离。鉴于其中很大一部分患者会发展为需要住院治疗和医疗管理的重症,包括以补充氧气治疗、机械通气、血管活性药物等形式提供呼吸和循环支持。对新冠患者进行居家病情持续监测将有助于早期判定疾病严重程度并进行医疗干预,以降低发病率和死亡率。此外,这还将使患者能够尽早安全出院,并为需要住院的患者腾出病床。在本综述中,我们重点关注能够持续监测疾病症状,特别是与新冠相关症状的下一代可穿戴传感器的最新进展。这些传感器包括可穿戴的非侵入性/微创生物物理(体温、呼吸频率、血氧饱和度、心率和心率变异性)和生化(细胞因子、皮质醇和电解质)传感器、传感器数据分析以及机器学习驱动的早期检测和医疗干预技术。我们共同旨在激发与数据分析集成的可穿戴传感器的未来发展,这些传感器为疾病诊断、健康监测与预测以及医疗干预奠定基础。