Simulation-driven dual-band Graphene–Silver terahertz metasurface biosensor integrated with machine learning for mode-resolved hemoglobin detection Article Swipe
Gunasekaran Thangavel
,
V. Joseph Michael Jerard
,
K. Manivannan
,
A. Sasikumar
,
V. Selvaraj
,
Manjunathan Alagarsamy
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.sintl.2025.100357
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.sintl.2025.100357
Accurate hemoglobin measurement is essential for diagnosing hematological disorders and monitoring cardiovascular health. This study introduces a terahertz metasurface biosensor combined with machine learning algorithms for rapid and non-invasive hemoglobin detection in clinical settings. The metasurface exhibits dual-band resonance in 2 THz regions, achieving a sensitivity of 450 GHz/RIU within a refractive index range of 1.34–1.43 RIU, with corresponding frequency shifts of 40 GHz and 30 GHz. Machine learning models, including Random Forest, Support Vector Machines, and Neural Networks, enhance the sensor's analytical capability. Across four clinical categories—normal, mild anemia, moderate anemia, and severe anemia—the models attain 96.5 percent classification accuracy, with recall and precision scores above 0.94. Ensemble learning reduces the root mean square error to 0.28 g/dL, while denoising methods increase the signal-to-noise ratio by 16.3 dB. The biosensor supports real-time analysis, requires minimal sample volume, and eliminates complex preparation, making it suitable for continuous hemoglobin monitoring and cardiovascular health management.
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Simulation-driven dual-band Graphene–Silver terahertz metasurface biosensor integrated with machine learning for mode-resolved hemoglobin detectionWork title
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2025Year of publication
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2025-11-05Full publication date if available
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Gunasekaran Thangavel, V. Joseph Michael Jerard, K. Manivannan, A. Sasikumar, V. Selvaraj, Manjunathan AlagarsamyList of authors in order
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https://doi.org/10.1016/j.sintl.2025.100357Publisher landing page
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goldOpen access status per OpenAlex
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