Challenges and Strategies in Developing an Enzymatic Wearable Sweat Glucose Biosensor as a Practical Point-Of-Care Monitoring Tool for Type II Diabetes.
Sook Mei KhorJoonhwa ChoiPhillip WonSeung Hwan KoPublished in: Nanomaterials (Basel, Switzerland) (2022)
Recently, several studies have been conducted on wearable biosensors. Despite being skin-adhesive and mountable diagnostic devices, flexible biosensor patches cannot truly be considered wearable biosensors if they need to be connected to external instruments/processors to provide meaningful data/readings. A realistic and usable wearable biosensor should be self-contained, with a fully integrated device framework carefully designed and configured to provide reliable and intelligent diagnostics. There are several major challenges to achieving continuous sweat monitoring in real time for the systematic and effective management of type II diabetes (e.g., prevention, screening, monitoring, and treatment) through wearable sweat glucose biosensors. Consequently, further in-depth research regarding the exact interrelationship between active or passive sweat glucose and blood glucose is required to assess the applicability of wearable glucose biosensors in functional health monitoring. This review provides some useful insights that can enable effective critical studies of these unresolved issues. In this review, we first classify wearable glucose biosensors based on their signal transduction, their respective challenges, and the advanced strategies required to overcome them. Subsequently, the challenges and limitations of enzymatic and non-enzymatic wearable glucose biosensors are discussed and compared. Ten basic criteria to be considered and fulfilled in the development of a suitable, workable, and wearable sweat-based glucose biosensor are listed, based on scientific reports from the last five years. We conclude with our outlook for the controllable, well-defined, and non-invasive monitoring of epidermal glucose for maximum diagnostic potential in the effective management of type II diabetes.
Keyphrases
- blood glucose
- glycemic control
- heart rate
- label free
- type diabetes
- gold nanoparticles
- cardiovascular disease
- blood pressure
- quantum dots
- sensitive detection
- public health
- mental health
- machine learning
- adipose tissue
- insulin resistance
- social media
- weight loss
- climate change
- smoking cessation
- deep learning
- wound healing
- soft tissue
- patient reported outcomes
- molecular dynamics
- drug induced