Leveraging Neural Networks for Enhanced Biocompatible Wearable Antennas: A Case Study in Continuous Glucose Monitoring

Abstract

This chapter delves into the transformative applications of neural networks (NN) in the realm of biocompatible wearable antennas, presenting a tangible example to underscore its impact. The comprehensive exploration covers the entire process, from the initial design phase to the real-world outcome. In the exemplar scenario, NNs are employed to intricately optimize the antenna's characteristics for seamless integration into a wearable device dedicated to continuous glucose monitoring. The study meticulously details the considerations in adapting NNs to ensure biocompatibility, reliability, and precision in data transmission within the dynamic context of health monitoring. The research outcome offers a compelling demonstration of the NN-optimized antenna's efficacy. Notably, the antenna ensures robust and reliable communication channels, minimizing signal interference even in dynamic and challenging environments. This outcome is of paramount significance in the healthcare domain, particularly for diabetic patients relying on continuous glucose monitoring for effective disease management