Recent advances in microfluidics, microelectronics, and electrochemical sensing methods have steered the way for the development of novel and potential wearable biosensors for healthcare monitoring. Wearable bioelectronics has received tremendous attention worldwide due to its great a potential for predictive medical modeling and allowing for personalized point-of-care-testing (POCT). They possess many appealing characteristics, for example, lightweight, flexibility, good stretchability, conformability, and low cost. These characteristics make wearable bioelectronics a promising platform for personalized devices. In this paper, we review recent progress in flexible and wearable sensors for non-invasive biomonitoring using sweat as the bio-fluid. Real-time and molecular-level monitoring of personal health states can be achieved with sweat-based or perspiration-based wearable biosensors. The suitability of sweat and its potential in healthcare monitoring, sweat extraction, and the challenges encountered in sweat-based analysis are summarized. The paper also discusses challenges that still hinder the full-fledged development of sweat-based wearables and presents the areas of future research.

Since its outbreak in 2019, COVID-19 becomes a pandemic, severely burdening the public healthcare systems and causing an economic burden. Thus, societies around the world are prioritizing a return to normal. However, fighting the recession could rekindle the pandemic owing to the lightning-fast transmission rate of SARS-CoV-2. Furthermore, many of those who are infected remain asymptomatic for several days, leading to the increased possibility of unintended transmission of the virus. Thus, developing rigorous and universal testing technologies to continuously detect COVID-19 for entire populations remains a critical challenge that needs to be overcome. Wearable respiratory sensors can monitor biomechanical signals such as the abnormities in respiratory rate and cough frequency caused by COVID-19, as well as biochemical signals such as viral biomarkers from exhaled breaths. The point-of-care system enabled by advanced respiratory sensors is expected to promote better control of the pandemic by providing an accessible, continuous, widespread, noninvasive, and reliable solution for COVID-19 diagnosis, monitoring, and management.

Magnetoelastic effect characterizes the change of materials' magnetic properties under mechanical deformation, which is conventionally observed in some rigid metals or metal alloys. Here we show magnetoelastic effect can also exist in 1D soft fibers with stronger magnetomechanical coupling than that in traditional rigid counterparts. This effect is explained by a wavy chain model based on the magnetic dipole-dipole interaction and demagnetizing factor. To facilitate practical applications, we further invented a textile magnetoelastic generator (MEG), weaving the 1D soft fibers with conductive yarns to couple the observed magnetoelastic effect with magnetic induction, which paves a new way for biomechanical-to-electrical energy conversion with short-circuit current density of 0.63 mA cm^-2, internal impedance of 180 Ω, and intrinsic waterproofness. Textile MEG was demonstrated to convert the arterial pulse into electrical signals with a low detection limit of 0.05 kPa,  even with heavy perspiration or in underwater situations without encapsulations.

Coronavirus disease 2019 (COVID-19) as a severe acute respiratory syndrome infection has spread rapidly across the world since its emergence in 2019 and drastically altered our way of life. Patients who have recovered from COVID-19 may still face persisting respiratory damage from the virus, necessitating long-term supervision after discharge to closely assess pulmonary function during rehabilitation. Therefore, developing portable spirometers for pulmonary function tests is of great significance for convenient home-based monitoring during recovery. Here, we propose a wireless, portable pulmonary function monitor for rehabilitation care after COVID-19. It is composed of a breath-to-electrical (BTE) sensor, a signal processing circuit, and a Bluetooth communication unit. The BTE sensor, with a compact size and light weight of 2.5 cm³ and 1.8 g respectively, is capable of converting respiratory biomechanical motions into considerable electrical signals. The output signal stability is greater than 93% under 35%-81% humidity, which allows for ideal expiration airflow sensing. Through a wireless communication circuit system, the signals can be received by a mobile terminal and processed into important physiological parameters, such as forced expiratory volume in 1 s (FEV₁) and forced vital capacity (FVC). The FEV₁/FVC ratio is then calculated to further evaluate pulmonary function of testers. Through these measurement methods, the acquired pulmonary function parameters are shown to exhibit high accuracy (>97%) in comparison to a commercial spirometer. The practical design of the self-powered flow spirometer presents a low-cost and convenient method for pulmonary function monitoring during rehabilitation from COVID-19.

Wearable bioelectronics for continuous and reliable pulse wave monitoring against body motion and perspiration remains a great challenge and highly desired. Here, a low-cost, lightweight, and mechanically durable textile triboelectric sensor that can convert subtle skin deformation caused by arterial pulsatility into electricity for high-fidelity and continuous pulse waveform monitoring in an ambulatory and sweaty setting is developed. The sensor holds a signal-to-noise ratio of 23.3 dB, a response time of 40 ms, and a sensitivity of 0.21 µA kPa^-1 . With the assistance of machine learning algorithms, the textile triboelectric sensor can continuously and precisely measure systolic and diastolic pressure, and the accuracy is validated via a commercial blood pressure cuff at the hospital. Additionally, a customized cellphone application (APP) based on built-in algorithm is developed for one-click health data sharing and data-driven cardiovascular diagnosis. The textile triboelectric sensor enabled wireless biomonitoring system is expected to offer a practical paradigm for continuous and personalized cardiovascular system characterization in the era of the Internet of Things.