The rapid advancements in wearable antenna tech-nologies have opened up new avenues for non-invasive healthcare applications. This work uses a principal component analysis technique to monitor the hematomas using a wide-band textile monopole (WTM) antenna. The WTM antenna operates at 3.13 GHz to 10.87 GHz, and its electrical size of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">λ₀/5.38×λ₀/5.1 ×λ₀/90.9m³</tex> shows that it is compact and easy to assemble in the microwave sensing system. This research proposes an unsupervised machine-learning framework that leverages the data collected from wearable antennas to identify the presence of hematomas. These WTM antennas continuously capture elec-tromagnetic signals from the fractured bone, allowing for real-time monitoring of subtle changes in the fractured bone and tissue characteristics. The reported findings demonstrate the feasibility and effectiveness of this innovative approach, providing a promising foundation for further research and development in the field of non-invasive monitoring of hematomas using wearable antennas.
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Rizwan et al. (2024) studied this question.
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