Advances in Antenna-Based Techniques for Detection and Monitoring of Critical Chronic Diseases: A Comprehensive Review

Abstract

Several research articles are available in the literature regarding the design of antennas, but hardly (to the best of authors' knowledge) few papers covered the antennas that are designed for the detection, diagnostics, and monitoring of various diseases. There is a need for a research article in which the design and performance of such significant antennas should be compared and highlighted based on various available design techniques to enhance performance parameters that include efficiency, bandwidth, size and appropriate bio-compatible material used to transmit data from the human body efficiently. Antennas are essential in biomedical applications for wireless communication, miniaturization, integration, implantable devices, diagnostic imaging, biotelemetry, and biosensing. They enable efficient and reliable wireless connectivity, facilitating remote monitoring, improving patient care, and advancing medical research. Designing biomedical antennas presents several challenges, including miniaturization and integration into compact devices, ensuring biocompatibility with the human body, conforming to biological structures, mitigating electromagnetic interference (EMI), accounting for signal attenuation and propagation in the body, optimizing power efficiency, and ensuring compliance with regulatory standards. Overcoming these challenges requires expertise in antenna design, biocompatibility, electromagnetic modelling, and collaboration between disciplines. Therefore, a detailed review is required so that any scholar who wishes to excel in this field may read this review to understand future directions better and work already done for the design of biomedical antennas. This review comprises a comparison of several significant biomedical antenna design techniques used for the detection, diagnosis and monitoring of various diseases, which can be helpful for the medical community for the detection of various diseases, including skin cancer, breast cancer, lungs cancer, endoscopy, brain tumor and glucose level detection. The various features of biomedical antennas are thoroughly investigated to provide performance metrics of the antennas designed to diagnose various diseases. The advantage of this study is the understanding of different types of antennas for various diseases. This study also allows realizing appropriate bio-compatible materials and flexible materials for biomedical antenna design, the effect of Specific Absorption Rate (SAR) on human/animal body and finally, the tables provide the antenna performance in terms of gain, bandwidth, and directivity with respect to antenna size and type of substrate material used for each disease. These biomedical antennas have several applications for diagnosis, early-stage cancer detection and, in some cases providing enough energy to cure the cancer cells in the human/animal body. Moreover, the implementation of Machine learning algorithms for the early detection of tumor for the above-mentioned diseases is also discussed. INDEX TERMSbiomedical antenna, breast cancer,...

Miniaturization and Fabrication of a Novel Cross-Fractal Biosensor and Sensor for Characterizing 3D Printing Electromagnetic Properties in Polylactic Acid

“…Using fractal forms at the nanotechnology level has proven its importance in improving the antenna characteristics in the Terahertz Regime [15]. Recent works have also demonstrated the importance of using fractal shapes in the biosensor field to improve its properties in identifying viruses and diseases, such as diabetes and cancer [16][17][18][19]. Recent research has concentrated on the use of fractal sensor for knowing 3D printing properties in Polylactic Acid (PLA), yielding promising results.…”

“…This device can be used as an antenna and a sensor simultaneously, so this idea is new and has not been spoken before. The value of this sensor, its characteristics (sensitivity, selectivity, and linearity) were compared with recent works [19][20][21][22], and it has proven effective in recognizing the objects. This is considered a contribution to the development of the field of smart robots and the AI applications.…”