Wearable Biosensors for Non-Invasive Sweat Diagnostics

Abstract

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.

Augmenting Sensor Performance with Machine Learning Towards Smart Wearable Sensing Electronic Systems

“…Additionally, personalized healthcare monitoring and disease treatment can be realized with the assistance of WSES and intelligent algorithms. In this section, we outline the applications of WSES assisted with ML algorithms for physiological signals monitoring (i.e., biochemical, biopotential, and biophysical signals), [30,41,[79][80][81][82] disease diagnosis, [83][84][85][86][87][88][89] and personalized healthcare (i.e., on-demand treatment and assistive devices). [7,[90][91][92][93] Some recent examples are highlighted in Table 1.…”

Colorimetric and Electrochemical Screening for Early Detection of Diabetes Mellitus and Diabetic Retinopathy—Application of Sensor Arrays and Machine Learning

“…Sweat might not be the best option for multi-array screening approaches; it seems that this body fluid could be more suitable for monitoring purposes, especially in the form of wearable electrochemical devices, which are usually interfaced with a ML software [ 134 ]. This approach can overcome the lack of big amounts of sample with direct contact of the sensor with the skin.…”

Highly integrated watch for noninvasive continual glucose monitoring

“…Considerable research efforts have been made in the last decade to develop noninvasive methods for the continuous monitoring of glucose, as well as other biomarkers. (e.g., lactate, uric acid, sodium, and potassium) in biofluids (e.g., sweat, saliva, tear, and ISF), resulting in a variety of devices 5 – 10 . Microneedles, albeit minimally invasive, are still accompanied by the risk of infection 11 – 13 , whereas devices such as mouthguards and contact lenses 14 – 17 lack well-established evidence for the correlation between saliva or tears and blood glucose.…”