![]() This is a consequence that can be dire to many and may result in missing critical hypo and hyperglycemic events. In fact, studies show that conventional blood glucose monitoring techniques that are painful such as finger pricking, result in non-compliance with regular glucose monitoring within the diabetic patients community 2, 4. All the developmental efforts must focus on providing the patients with continuous glucose monitoring (CGM) solutions that are not dependent on finger pricking for blood extraction but rather on a painless wireless method to detect glucose variations 4. It is now clear that continuous monitoring of the glycemic profiles of patients with diabetes, delays the progression of the disease 2, 3 since it provides a significant amount of information that allows healthcare professionals to plan personalized diabetes treatment regimens based on the patient’s individual glycemic profile. The future of continuous glucose monitoring is confidently heading towards non-invasive wearable solutions that are needle-free and pain-free, as also supported by the recent report of the world economic forum on the top ten emerging technologies 1. Hence, our approach ensures the continuous tracking of glucose variations from hypo-to-hyper glycemic levels with great fidelity. ![]() Human trials on patients with diabetes and healthy individuals reveal a clinical accuracy of continuous glucose monitoring of 99.01% in twenty-eight subjects who underwent Oral Glucose Tolerance Tests. In-Vivo experiments on diabetic rats and pigs exhibit a 100% diagnostic accuracy over a wide range of glucose variations. The entire wearable system is calibrated against temperature, humidity, and movement resulting in high accuracy in glucose variations tracking. These sensors are flexible, and embedded in wearable garments such as socks, which provide conformity to curved skin surfaces and movement resilience. The proposed sensors are personalized, leverage electromagnetic waves, and are coupled with a custom machine-learning-based signal-processing module. ![]() This work introduces novel body-matched, vasculature-inspired, quasi-antenna-arrays that act as electromagnetic sensors to instantaneously, continuously, and wirelessly sense glucose variations in the bloodstream.
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