An enhanced tool for monitoring diabetes can be realized by continuous tracking of a patient’s glucose levels using their sweat or tears. A flexible, ultra-thin sensor for real-time tracking of glucose levels, which can be integrated into contact lenses or at the back of watches, has been described in the ACS Nano journal.
Although wearable sensors are characteristic to a highly digitized world, commercially accessible ones generally monitor physical activities by measuring heart rate or steps taken. Devising techniques for measuring health markers at the molecular level has been highly difficult, though the advantages can be life-transforming for some people. Diagnosing and tracking conditions are usually set by investigating blood sample of a person. However, the pain caused while drawing blood or pricking fingers can prevent people from monitoring conditions such as diabetes that mandate constant checks. Although wearable glucose sensors are being developed to make the process painless, they have been hindered by various factors. Certain devices do not have the ability to detect lower levels of glucose included in sweat and tears or they do not work upon being bent. Moh Amer, Chongwu Zhou, and their collaborators strived to overcome these challenges.
The scientists developed a biosensor by making use of a natural chitosan film, indium oxide nanoribbons, single-walled carbon nanotubes and an enzyme glucose oxidase. If glucose is included in a test sample, it reacts with the enzyme, initiates a short chain of reactions, and eventually creates an electrical signal. Investigations revealed that the device had the ability to detect glucose concentrations of the range of 10 nanomolar to 1 millimolar, adequately sensitive to cover usual glucose levels in saliva, sweat, and tears in people suffering from and not suffering from diabetes. The performance of the film was not evidently affected even upon bending it for 100 times. Apart from glucose tracking, the scientists are of the view that the sensor can also be used for monitoring in the food and environmental fields.
Funding from the King Abdulaziz City of Science of Technology through the Center of Excellence for Green Nanotechnologies, part of the National Industrial Development and Logistics Program (NIDLP), and the University of Southern California is acknowledged by the authors.