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<p>Detection and quantification of <i>Mycobacterium tuberculosis</i> (MTB) remain critical challenges in global public health, particularly in resource-limited settings where tuberculosis (TB) drives significant morbidity and mortality. This study presents the development and characterization of a THz-based optical biosensor platform for ultra-sensitive MTB detection. The biosensor architecture incorporates a hybrid graphene-gold metasurfaces fabricated on silicon dioxide, featuring an optimized array of L-shaped, plus-shaped, and square-shaped resonators. Computational electromagnetic simulations performed via COMSOL Multiphysics demonstrated exceptional sensitivity to refractive index modulations associated with MTB-specific biomarkers, achieving a maximum sensitivity of 2000 GHzRIU<sup>-1</sup>. Systematic parametric analyses were conducted to evaluate sensor performance across varying graphene chemical potentials, resonator geometries, and electromagnetic field incident angles. Implementation of a locally weighted linear regression (LOWESS) model enabled accurate prediction of sensor response characteristics at intermediate frequencies, yielding coefficient of determination (R<sup>2</sup>) values exceeding 85% across all investigated parameters. This label-free biosensing platform demonstrates promising potential for rapid, highly specific MTB detection, addressing a critical need for improved tuberculosis diagnostics in clinical settings.</p>

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Machine Learning Optimized Optical Surface Plasmon Resonance Biosensor Using Locally Weighted Linear Regression for Rapid and Accurate Detection of Tuberculosis Biomarkers

  • 期刊论文

  • 发表日期：

    2025年2月8日

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  • Basim Ahmad Alabsi,
  • Jacob Wekalao,
  • R. Dhivya,
  • Marouan Kouki,
  • Abdulkarem H. M. Almawgani,
  • Shobhit K. Patel

摘要

Detection and quantification of Mycobacterium tuberculosis (MTB) remain critical challenges in global public health, particularly in resource-limited settings where tuberculosis (TB) drives significant morbidity and mortality. This study presents the development and characterization of a THz-based optical biosensor platform for ultra-sensitive MTB detection. The biosensor architecture incorporates a hybrid graphene-gold metasurfaces fabricated on silicon dioxide, featuring an optimized array of L-shaped, plus-shaped, and square-shaped resonators. Computational electromagnetic simulations performed via COMSOL Multiphysics demonstrated exceptional sensitivity to refractive index modulations associated with MTB-specific biomarkers, achieving a maximum sensitivity of 2000 GHzRIU-1. Systematic parametric analyses were conducted to evaluate sensor performance across varying graphene chemical potentials, resonator geometries, and electromagnetic field incident angles. Implementation of a locally weighted linear regression (LOWESS) model enabled accurate prediction of sensor response characteristics at intermediate frequencies, yielding coefficient of determination (R2) values exceeding 85% across all investigated parameters. This label-free biosensing platform demonstrates promising potential for rapid, highly specific MTB detection, addressing a critical need for improved tuberculosis diagnostics in clinical settings.