Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Raveendra, K.; Muniyandy, Elangovan; Sindhu, V.; Arunachalam, Krishna Prakash Title A name given to the resource Compact LoRa Patch Antenna Optimization Using Dual Random Starfish Aggregation Coupled Transformer Network for Vital Sign Detection in Breast Cancer WBANs Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Biomedical Materials and Devices; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s44174-025-00547-3" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s44174-025-00547-3</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105019357075?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105019357075?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Raveendra K., Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Andhra Pradesh, Tirupati, India; Muniyandy E., Department of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Tamil Nadu, Chennai, 602105, India, Applied Science Research Center, Applied Science Private University, Amman, Jordan; Sindhu V., Department of Computer Science, Christ University, Karnataka, Bangalore, India; Arunachalam K.P., Departamento de Ciencias de la Construcci, Facultad de Ciencias de la Construcci Ordenamiento Territorial, Universidad Tecnolica Metropolitana, Santiago, Chile Description An account of the resource The rapid advancement of Wireless Body Area Networks (WBANs) has created a growing demand for compact, efficient, and reliable antenna systems to support continuous health monitoring, particularly for breast cancer applications. Recent methods, including CPW-fed patch antennas, artificial neural network (ANN)-driven models, and wearable textile antennas, have improved antenna design automation and flexibility. However, challenges such as signal distortion from body proximity, gain reduction under bending, Specific Absorption Rate (SAR) compliance, and lack of adaptive tuning continue to limit practical deployment. To overcome these limitations, this study presents a compact LoRa patch antenna optimized using a novel Dual Random Starfish Aggregation Coupled Transformer Network (Dual-Ran-SACTN) framework. This system combines the Starfish Optimization Algorithm (SFOA), a Random-Coupled Neural Network (RCCN), and a Dual-Aggregation Transformer Network (DuAT) to enhance convergence speed and learning efficiency. The antenna, designed in CST Microwave Studio, measures only 80נ60mm2 (0.23??נ0.17??), offering a lightweight and wearable structure for continuous vital sign monitoring. The proposed model exhibits a bidirectional radiation pattern in the E-plane and an omnidirectional pattern in the H-plane, achieving a peak gain of 2.12dBi and a high radiation efficiency of 99.8% at 868MHz. Additionally, the design maintains low SAR and stable performance under bending, making it robust for wearable WBAN applications. This work offers a real-time, energy-efficient solution for intelligent breast cancer monitoring through adaptive antenna optimization. This model supports practical applications such as continuous breast cancer monitoring, wearable health diagnostics, and real-time WBAN-based physiological signal tracking. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025. Subject The topic of the resource Breast cancer monitoring; Dual random starfish aggregation coupled transformer network (Dual-Ran-SACTN); Dual-aggregation transformer network (DuAT); Long range (LoRa) patch antenna; Random-coupled neural network (RCCN); Wireless body area networks (WBANs) Publisher An entity responsible for making the resource available Springer Nature Relation A related resource ISSN: 27314812; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online