Abstract This article introduces a biocompatible, non-invasive intra-body communication (IBC) system that employs a U-shaped, flexible wearable antenna specifically designed for fat-intra-body communication (Fat-IBC) applications. The proposed Fat-IBC system is engineered to function within the industrial, scientific, and medical (ISM) frequency range of 2.40–2.48 GHz. The U-shaped wearable antenna is encased in a biocompatible polydimethylsiloxane (PDMS) coating layer, enhancing durability and safety, making it suitable for continuous use in medical contexts. The U-shaped Fat-IBC antenna leverages the low-loss property of adipose (fat) tissue, positioned between skin and muscle layers, to facilitate efficient signal propagation across the body. The antenna is optimized for transmission through a three-layer tissue model (skin, fat, and muscle), leveraging the favorable transmission properties of adipose tissue to minimize signal loss. To assess performance, detailed numerical simulations and experimental validations were conducted using three-layer tissue models, torso phantoms (obese and athletic), and human volunteer trials. Ethical approvals were obtained for human testing, ensuring compliance with biomedical research standards. The performance of the U-shaped Fat-IBC antenna was benchmarked against a standard Bluetooth low energy (BLE) chip antenna under controlled conditions, with measurements taken in both front-to-back and side-to-side orientations across various body types. Experimental results demonstrated the superior performance of the U-shaped Fat-IBC antenna over BLE, specifically in terms of signal stability and transmission efficiency across body tissue, especially within adipose layers. Specific Absorption Rate (SAR) analysis revealed a peak value of 0.3061 W/kg, which is well within the IEEE safety limits, confirming the system’s suitability for biomedical applications. This Fat-IBC platform demonstrates the feasibility of fat tissue as a viable medium for intra-body networks, offering a reliable, power-efficient solution for real-time medical telemetry and patient monitoring, with promising implications for broader health applications.
Mandal et al. (Tue,) studied this question.