Sodium polyacrylate microparticle containing multifunctional skin patch for sweat analysis

Explainable Deep Learning-Assisted Self-Calibrating Colorimetric Patches for In Situ Sweat Analysis

Sweat has emerged as a compelling analyte for noninvasive biosensing technology because it contains a wealth of important biomarkers in hormones, organic biomacromolecules, and various ionic mixtures. These components offer valuable insights and can reflect an individual's physiological conditions. Here, we introduced an explainable deep learning (DL)-assisted wearable self-calibrating colorimetric biosensing analysis platform to efficiently and precisely detect the biomarker's concentration in sweat. Specifically, we have integrated the advantages of the colorimetric sensing method, adsorbing-swelling hydrogel, and explainable DL algorithms to develop an enzyme/indicator-immobilized colorimetric patch, which has reliable colorimetric sensing ability and excellent adsorbing-swelling function. A total of 5625 colorimetric images were collected as the analysis data set and assessed two DL algorithms and seven machine learning (ML) algorithms. Zn2+, glucose, and Ca2+ in human sweats could be facilely classified and quantified with 100% accuracy via the convolutional neural network (CNN) model, and the testing results of actual sweats via the DL-assisted colorimetric approach are 91.7-97.2% matching with the classical UV-vis spectrum. Class activation mapping (CAM) was utilized to visualize the inner working mechanism of CNN operation, which contributes to verify and explicate the design rationality of the noninvasive biosensing technology. An "end-to-end" model was established to ascertain the black box of the DL algorithm, promoted software design or principium optimization, and contributed facile indicators for health monitoring, disease prevention, and clinical diagnosis.

Sweat analysis for urea sensing: trends and challenges

With increasing population there is a rise in pathological diseases that the healthcare facilities are grappling with. Sweat-based wearable technologies for continuous monitoring have overcome the demerits associated with sweat sampling and sensing. Hence, sweat as an alternative biofluid holds great promise for the quantification of a host of biomarkers and understanding the functioning of the body, thereby deducing ailments quickly and economically. This comprehensive review accounts for recent advances in sweat-based LOCs (Lab-On-Chips), which are a likely alternative to the existing blood-urea sample testing that is invasive and time-consuming. The present review is focused on the advancements in sweat-based Lab-On-Chips (LOCs) as an alternative to invasive and time-consuming blood-urea sample testing. In addition, different sweat collection methods (direct skin, near skin and microfluidic) and their mechanism for urea sensing are explained in detail. The mechanism of urea in biofluids in protein metabolism, balancing nitrogen levels and a crucial factor of kidney function is described. In the end, research and technological advancements are explained to address current challenges and enable its widespread implementation.

Flexible and Wearable Biosensors for Monitoring Health Conditions

Flexible and wearable biosensors have received tremendous attention over the past decade owing to their great potential applications in the field of health and medicine. Wearable biosensors serve as an ideal platform for real-time and continuous health monitoring, which exhibit unique properties such as self-powered, lightweight, low cost, high flexibility, detection convenience, and great conformability. This review introduces the recent research progress in wearable biosensors. First of all, the biological fluids often detected by wearable biosensors are proposed. Then, the existing micro-nanofabrication technologies and basic characteristics of wearable biosensors are summarized. Then, their application manners and information processing are also highlighted in the paper. Massive cutting-edge research examples are introduced such as wearable physiological pressure sensors, wearable sweat sensors, and wearable self-powered biosensors. As a significant content, the detection mechanism of these sensors was detailed with examples to help readers understand this area. Finally, the current challenges and future perspectives are proposed to push this research area forward and expand practical applications in the future.

Wearable Sensor for Continuous Sweat Biomarker Monitoring

In recent years, wearable sensors have enabled the unique mode of real-time and noninvasive monitoring to develop rapidly in medical care, sports, and other fields. Sweat contains a wide range of biomarkers such as metabolites, electrolytes, and various hormones. Combined with wearable technology, sweat can reflect human fatigue, disease, mental stress, dehydration, and so on. This paper comprehensively describes the analysis of sweat components such as glucose, lactic acid, electrolytes, pH, cortisol, vitamins, ethanol, and drugs by wearable sensing technology, and the application of sweat wearable devices in glasses, patches, fabrics, tattoos, and paper. The development trend of sweat wearable devices is prospected. It is believed that if the sweat collection, air permeability, biocompatibility, sensing array construction, continuous monitoring, self-healing technology, power consumption, real-time data transmission, specific recognition, and other problems of the wearable sweat sensor are solved, we can provide the wearer with important information about their health level in the true sense.