Design and Optimization of Logarithmic Slot Antennas for High-Frequency Medical Imaging and Wireless Healthcare Systems: A Test-Driven AI Framework for Performance Enhancement and Reliable Deployment
Keywords:
Logarithmic Slot Antenna, Substrate Integrated Waveguide, Medical Imaging, Wireless Healthcare Systems, Biomedical Communication, Artificial Intelligence, High-Frequency AntennasAbstract
The advancement of biomedical imaging and wireless healthcare technologies has created a growing demand for compact, efficient, and high-gain antenna systems capable of operating effectively in complex biological environments. This study presents the design and optimization of substrate integrated waveguide (SIW)-based logarithmic slot antennas for high-frequency medical imaging and intelligent healthcare systems. The proposed antenna utilizes logarithmic slot geometry to achieve broadband operation, enhanced impedance matching, stable radiation characteristics, and improved signal transmission across microwave and millimeter-wave frequency bands. Electromagnetic simulations and experimental evaluations demonstrate superior gain, reduced signal attenuation, enhanced bandwidth, and improved imaging resolution compared to conventional antenna structures. The research also investigates the compatibility of the antenna with wearable and implantable healthcare devices used in modern smart healthcare systems. In addition, a test-driven artificial intelligence framework is incorporated into the optimization process to improve design validation, parameter tuning, and deployment reliability. Machine learning-assisted optimization significantly reduces design iterations while improving consistency between simulated and experimental results. Furthermore, the study highlights the relevance of advanced medical imaging technologies such as EEG-based image classification and cone-beam computed tomography in supporting intelligent healthcare systems. The results confirm that SIW-based logarithmic slot antennas provide an effective solution for next-generation biomedical imaging and wireless healthcare communication systems.
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