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<p>This research presents a wearable dual-band type antenna designed for the Wireless Body Area Networks (WBAN). The current structure of conformal radiator operates at WLAN frequencies of 2.40&#xa0;GHz &amp; 5.80&#xa0;GHz featuring compact dimensions of 15 × 20 × 0.1 mm<sup>3</sup>. Specific absorption rate type (SAR) analysis confirms that radiator design adheres to standard requirement of 1.6&#xa0;W/kg making it suitable for wearable applications. The radiator underwent comprehensive testing, evaluating its flexibility, performance and S-parameters across various bending radii ranging 20–40&#xa0;mm. Additionally S<sub>11</sub> was analyzed and distinguish under different on-body conditions. The measured versus simulated results of S<sub>11</sub> and characteristics of radiation and gain demonstrate excellent agreement. Machine learning algorithms were utilized to optimize the wearable, flexible Bowtie Antenna for improving its return loss and VSWR metrics.</p>

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Machine learning-assisted design and optimization of a flexible dual-band bowtie antenna for wearable healthcare and WLAN applications

  • 期刊论文

  • 发表日期：

    2025年9月10日

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  • Pasumarthi Srinivasa Rao,
  • K. Vasu Babu,
  • Jagabathuni Kavitha,
  • Uppala Jayaram

摘要

This research presents a wearable dual-band type antenna designed for the Wireless Body Area Networks (WBAN). The current structure of conformal radiator operates at WLAN frequencies of 2.40 GHz & 5.80 GHz featuring compact dimensions of 15 × 20 × 0.1 mm3. Specific absorption rate type (SAR) analysis confirms that radiator design adheres to standard requirement of 1.6 W/kg making it suitable for wearable applications. The radiator underwent comprehensive testing, evaluating its flexibility, performance and S-parameters across various bending radii ranging 20–40 mm. Additionally S11 was analyzed and distinguish under different on-body conditions. The measured versus simulated results of S11 and characteristics of radiation and gain demonstrate excellent agreement. Machine learning algorithms were utilized to optimize the wearable, flexible Bowtie Antenna for improving its return loss and VSWR metrics.