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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. 

Rapid and ultrasensitive point-of-care RNA detection plays a critical role in the diagnosis and management of various infectious diseases. The gold-standard detection method of reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is ultrasensitive and accurate yet limited by the lengthy turnaround time (1-2 days). On the other hand, antigen test offers rapid at-home detection (15-20 min) but suffers from low sensitivity and high false-negative rates. An ideal point-of-care diagnostic device would combine the merits of PCR-level sensitivity and rapid sample-to-result workflow comparable to antigen testing. However, the existing RNA detection platform typically possesses superior sensitivity or rapid sample-to-result time, but not both. This paper reports a point-of-care microfluidic device that offers ultrasensitive yet rapid detection of viral RNA from clinical samples. The device consists of a microfluidic chip for precisely manipulating small volumes of samples, a miniaturized heater for viral lysis and ribonuclease (RNase) inactivation, a CRISPR Cas13a- electrochemical sensor for target preamplification-free and ultrasensitive RNA detection, and a smartphone-compatible potentiostat for data acquisition. As demonstrations, the devices achieve the detection of heat-inactivated SARS-CoV-2 samples with a limit of detection (LOD) down to 10 aM within 25 minutes, which is comparable to the sensitivity of RT-PCR and rapidness of antigen test. The platform also successfully distinguishes all nine positive unprocessed clinical SARS-CoV-2 nasopharyngeal swab samples from four negative samples within 25 minutes of sample-to-result time. Together, this device provides a point-of-care solution that can be deployed in diverse settings beyond laboratory environments for rapid and accurate detection of RNA from clinical samples. The device can potentially be expandable to detect other viral targets, such as human immunodeficiency virus (HIV) self-testing and Zika virus, where rapid and ultrasensitive point-of-care detection is required.