Monitoring Knee Health: Ultra-Wideband Radar Imaging for Early Detection of Osteoarthritis.

Abstract

This paper presents a non-invasive method and study for analyzing knee osteoarthritis, encompassing a dual-step approach: a) the employment of synthetic aperture radar (SAR)-based microwave reflection tomography for imaging the knee joint, and b) the application of an ultra-wideband (UWB) radar technique combined with a genetic algorithm to determine muscle electrical properties (permittivity) and the gap between the femur (thighbone) and tibia (shinbone). The assessment of osteoarthritis is conducted by integrating the outcomes of the knee joint imaging, change in muscle permittivity, and inter-bone spacing. This technique undergoes initial validation on simplified knee models, subsequently extending to adult human voxel knee tissues as represented in CST software. Experimental validation involves analyzing a porcine knee joint comprising sequential layers of skin, fat, muscle, and bone. Both simulated and experimental validations suggest that this technique is viable, safe, and cost-effective for estimating knee osteoarthritis in humans.