Sensing and Bio-Sensing Research最新文献

{"title":"Halophyte-based saline irrigation: A remote sensing study of eco-hydrological impacts","authors":"Ahmad Azeem,&nbsp;Wenxuan Mai,&nbsp;Liyuan Jiang","doi":"10.1016/j.sbsr.2026.101050","DOIUrl":"10.1016/j.sbsr.2026.101050","url":null,"abstract":"<div><div>Saline irrigation with halophytes has emerged as a promising nature based solution for enhancing ecosystem functioning in arid saline environments; however, its long term Eco-hydrological effects remain poorly understood. This study examined long term Eco-hydrological impacts of a halophyte based saline irrigation system at the Karamay experimental site, Xinjiang, China, by using multi-source remote sensing data between 2015 and 2025. Indicators of seasonal growing period, such as normalized difference vegetation index (NDVI), soil salinity index (SI), evapotranspiration (ET), and land surface temperature (LST) were compared between a managed halophyte garden and an adjacent control area. Findings indicated that the halophyte garden always had higher NDVI, ET and lower SI, LST, compared to the control area, which meant better vegetation performance, less salinity stress, and thermal conditions. Mann Kendall and Sen's slope analyses revealed no significant year to year trends in NDVI, SI, ET, or LST in either area. Regression analysis indicated that SI and NDVI had a strong negative relationship. While there was a positive relationship between ET and NDVI. These findings affirm that salinity in soils was the primary constraint to vegetation growth, whereas water flux favored the growth of the plants. Multivariate regression and machine learning models (Random Forest and Extreme Gradient Boosting), further established SI to be the best predictor of NDVI, followed by land management and ET, but temperature and precipitation did not have significant effects. Importantly, halophyte systems do not eliminate salinity stress but mitigate its ecological impact, promoting vegetation tolerance. The findings underscore their possible potential as a nature based solution to sustainable land and water management in arid salty environments.</div></div>","PeriodicalId":424,"journal":{"name":"Sensing and Bio-Sensing Research","volume":"53 ","pages":"Article 101050"},"PeriodicalIF":4.7,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148657337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design, fabrication, and machine learning-assisted dielectric constant prediction of a compact microwave metamaterial sensor for water adulteration detection in petrol","authors":"Dhavala Naga Lakshmi Koustubha,&nbsp;Sumit Singhal,&nbsp;Upender Patri,&nbsp;Sukriti,&nbsp;Amarjit Kumar","doi":"10.1016/j.sbsr.2026.101071","DOIUrl":"10.1016/j.sbsr.2026.101071","url":null,"abstract":"<div><div>The increasing demand for rapid and reliable fuel quality assessment has created a need for compact sensing platforms capable of accurately detecting fuel adulteration. This work presents a compact 6 × 6 mm² hexagonal metamaterial structure operating at 2.7578 GHz for the detection of water adulteration in petrol through dielectric characterization. The fabricated design comprises dual hexagonal split-ring resonators, a central hexagonal patch, and a connecting metallic strip printed on an FR-4 substrate. An equivalent circuit representation is developed to characterize the resonance mechanism and is validated through full-wave electromagnetic simulations. The sensing performance is investigated by varying the dielectric constant from 1 to 4, resulting in a resonance frequency shift of 1.805 GHz, a maximum sensitivity of 3.61 GHz/ε_r, and a quality factor of 137.89. The proposed metastructure is fabricated utilizing standard PCB technology and experimentally characterized using a free-space measurement setup. The measured resonance responses exhibit good correlation with the simulated responses, with a maximum frequency error of only 6.4 MHz and a relative error below 0.5%. Furthermore, a machine learning framework is developed to predict the dielectric constant directly from the measured resonance characteristics. Among the evaluated models, XGBoost demonstrates the highest prediction accuracy and the lowest prediction error, enabling rapid estimation of the dielectric properties of unknown fuel samples without repeated electromagnetic simulations. The proposed methodology combines compact sensor design, experimental validation, and intelligent data-driven analysis, providing an accurate and practical solution for real-time detection of water adulteration in petrol.</div></div>","PeriodicalId":424,"journal":{"name":"Sensing and Bio-Sensing Research","volume":"53 ","pages":"Article 101071"},"PeriodicalIF":4.7,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148737675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An electrochemical immunosensor based on the BiFeO3/Au nanocomposite for detection of the prostate specific antigen biomarker","authors":"Masoumeh Ranjbarzadhag,&nbsp;Biuck Habibi,&nbsp;Mohammad Reza Rashidi,&nbsp;Balal Khalilzadeh,&nbsp;Abdolali Alemi","doi":"10.1016/j.sbsr.2026.101065","DOIUrl":"10.1016/j.sbsr.2026.101065","url":null,"abstract":"<div><div>Prostate specific antigen (PSA) is widely recognized as a critical biomarker for diagnosis and clinical surveillance of prostate cancer. In this work, a novel sensitive immunosensor for quantifying of the PSA has been described based on the gold (Au) nanoparticles decorated on/in the BiFeO₃ perovskite and modified with PSA biomarker antibodies (Ab) and bovine serum albumin (BSA) via incubation on the nanocomposite (BiFeO₃/Au) platform; GCE/BiFeO₃/Au/Ab/BSA. The nanocomposite was thoroughly characterized using X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy, transmission electron microscopy, and electrochemical techniques. The obtained results show that the BiFeO₃/Au nanocomposite has large surface area and good biocompatible, conductivity and excellent electrocatalytic properties. The analytical performance of the immunosensor; GCE/BiFeO₃/Au/Ab/BSA, was evaluated using differential pulse voltammetry (DPV) method with [Fe(CN)₆]³⁻/⁴⁻ as a probe ion to reflect the PSA concentrations. Under the optimized conditions, the immunosensor exhibited a good linear relationship between the PSA concentrations and DPV signals; 0.1–100 ng/mL of PSA with excellent correlation coefficient (R² = 0.9997) and low detection limit (47.06 pg/mL). The fabricated perovskite-based immunosensor demonstrated high selectivity, superior sensitivity, good reproducibility, and long-term stability. Finally, the designed immunosensor was successfully applied to PSA detection in real samples, and the results were consistent with those obtained from a commercial enzyme-linked immunosorbent assay (ELISA) method, confirming its analytical reliability.</div></div>","PeriodicalId":424,"journal":{"name":"Sensing and Bio-Sensing Research","volume":"53 ","pages":"Article 101065"},"PeriodicalIF":4.7,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148738340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From limit of detection to effective sensitivity in charge-modulated organic-transistor biosensors","authors":"Ondrej Kokavec,&nbsp;Michal Mičjan,&nbsp;Martin Weis","doi":"10.1016/j.sbsr.2026.101072","DOIUrl":"10.1016/j.sbsr.2026.101072","url":null,"abstract":"<div><div>Organic-transistor biosensors are a promising platform for early diagnostics, and their reported detection limits now dwell in the femto- to attomolar range. However, the metric that dominates the literature, namely the static limit of detection (LoD), captures only one half of what governs the usable performance, and the second half is still not clearly addressed. Through a comparative analysis of organic charge-modulated field-effect transistors (OCM-FETs) and their interfacial (ISOFET) and volumetric (OECT) counterparts, we show that the achievable detection limit factorizes, to first order, into two engineering quantities, namely a capacitive gain term and a dielectric drift-floor term, so that the LoD is governed by their product. We find that the first term has been driven to its geometric minimum through deliberate capacitive-divider and channel down-scaling, whereas the second, the device-side drift floor – which in the OCM-FET reduces to the bulk Maxwell–Wagner relaxation time – has, for the affinity OCM-FET sensors in which the architecture’s advantage should matter most, scarcely been isolated as an independent quantity, even though the coupled foils quantify it routinely. Hence, the defining claim of this architecture, that its detection ceiling is an engineering rather than a thermodynamic limit, remains only half-demonstrated. We make the drift factor explicit through an effective-sensitivity decomposition, place the architectures on a single degree-of-coupling axis, and specify the time-domain measurement required to render the engineering-ceiling claim testable. We further show that, although the response time and the drift floor are set by the same bulk relaxation, they separate by orders of magnitude in affinity sensors, so that the operability number applies there without modification while saturating on a measurable capacitance ratio in the fast-transduction limit.</div></div>","PeriodicalId":424,"journal":{"name":"Sensing and Bio-Sensing Research","volume":"53 ","pages":"Article 101072"},"PeriodicalIF":4.7,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148770543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-Q Quasi-bound states in the continuum metasurface for simultaneous detection of magnetic induction intensity, refractive index and temperature","authors":"Chengbo Du,&nbsp;Zhe Han,&nbsp;Donghe Sheng,&nbsp;Huiping Tian","doi":"10.1016/j.sbsr.2026.101075","DOIUrl":"10.1016/j.sbsr.2026.101075","url":null,"abstract":"<div><div>Multi-parameter sensing has become a popular research topic. However, designing multi-parameter sensors with multiple high quality-factor (<em>Q</em>-factor) resonances remains challenging. In order to address the challenge, we employ quasi-bound states in the continuum (quasi-BICs) to design a silicon-based metasurface multi-parameter sensor with multiple high-<em>Q</em> resonances. The multi-parameter sensor can support three quasi-BICs resonances with a <em>Q</em>-factor exceeding 10⁴, and can detect three parameters of magnetic induction intensity (<em>B</em>), refractive index (<em>RI</em>) and temperature (<em>T</em>) simultaneously. In order to detect the three parameters using the proposed sensor, the sensitivities for <em>B</em>, <em>RI</em> and <em>T</em> of the three quasi-BICs resonances are calculated, respectively. Then we exploit a three-dimensional sensitivity matrix, and obtain a matrix equation to describe the relationship between the changes of the three parameters and the resonant wavelength shifts of the three quasi-BICs resonances. By solving the matrix equation, the three parameters can be simultaneously demodulated. The proposed sensor employs quasi-BICs to obtain resonances with high <em>Q</em>-factors, and can simultaneously detect <em>B</em>, <em>RI</em> and <em>T</em>. This work provides a feasible way for designing high-<em>Q</em> multi-parameter sensors.</div></div>","PeriodicalId":424,"journal":{"name":"Sensing and Bio-Sensing Research","volume":"53 ","pages":"Article 101075"},"PeriodicalIF":4.7,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148770544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Determination of D-L kynurenine in human plasma by electrochemical measurement with multi-wall carbon nanotube-modified carbon paste electrode","authors":"Ahmad Movahedpour,&nbsp;Omid Sheydaei,&nbsp;Arash Asfaram,&nbsp;Sajedeh Karami,&nbsp;Hassan Ghasemi","doi":"10.1016/j.sbsr.2026.101063","DOIUrl":"10.1016/j.sbsr.2026.101063","url":null,"abstract":"<div><div>This study presents the design and electrochemical characterization of a highly sensitive and selective sensor for the determination of D−/L- kynurenine (D−/L- KYN), based on a carbon paste electrode (CPE) modified with multi-walled carbon nanotubes (MWCNTs). The electrocatalytic oxidation of D−/L-KYN at the MWCNT-modified CPE was systematically investigated using cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The Structural and morphological characteristics of the MWCNTs were characterized by Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The combined characterization results confirmed the successful functionalization, morphological integrity, and crystalline structure of the MWCNTs, supporting their suitability as an efficient electrode modifier. At physiological pH (7.0) in phosphate buffer solution (PBS), D−/L-KYN exhibited a well-defined oxidation peak at +0.85 <em>V</em> (vs. Ag/AgCl). The electrochemical behavior of the analyte followed a diffusion-controlled mechanism involving a two-electron/two-proton transfer process. Key analytical parameters including solution pH and scan rate were optimized to enhance sensor performance. The fabricated sensor exhibited a linear concentration range of 0.06–40.0 μM, with an impressive limit of detection 3 nM (S/N = 3). Furthermore, the sensor demonstrated excellent reproducibility and repeatability, with relative standard deviations (RSDs) of 3.8% and 3.3%, respectively. The developed platform was successfully applied to the quantification of D−/L-KYN in spiked human plasma samples, demonstrating its potential for clinical and biomedical applications.</div></div>","PeriodicalId":424,"journal":{"name":"Sensing and Bio-Sensing Research","volume":"53 ","pages":"Article 101063"},"PeriodicalIF":4.7,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148737674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a lightweight, fully integrated qPCR sensor for environmental DNA","authors":"Edward Luy,&nbsp;Colin Sonnichsen,&nbsp;Andre Hendricks,&nbsp;Iain Grundke,&nbsp;Kyle Park,&nbsp;Jennifer Tolman,&nbsp;Robert G. Beiko,&nbsp;Julie LaRoche,&nbsp;Vincent Sieben","doi":"10.1016/j.sbsr.2026.101058","DOIUrl":"10.1016/j.sbsr.2026.101058","url":null,"abstract":"<div><div>Environmental DNA (eDNA) has emerged in recent years as a powerful tool in ecological monitoring. However, conventional eDNA methods are bottlenecked by long wait times due to sample transport and lab analysis. We present a compact and portable eDNA sensor to enable near real-time and in-situ detection of specific eDNA sequences. The instrument has been developed to autonomously sample from the surrounding environment and perform DNA extraction and target amplification. Sample water is rapidly pumped (∼430 mL/min) through a stacked double membrane filter and nucleic acid extraction follows a standardized protocol. A target DNA sequence is amplified and detected through quantitative polymerase chain reaction (qPCR), giving the user a sensitive and specific result on the presence of the target sequence in the environment. Results are obtained in less than 6 h from the beginning of sample capture, enabling same-day decision making. Performance was validated through detection of bowhead whale (<em>Balaena mysticetus</em>) DNA sampled from preserved tissue, with threshold cycles of 19.4 <span><math><mo>±</mo></math></span> 0.3 for positve controls, 13.3 <span><math><mo>±</mo></math></span> 0.8 for samples, and 35.2 <span><math><mo>±</mo></math></span> 1.2 for negative controls. A brief timeline to full sensor validation is presented, that once complete will mark a significant step towards real-time, in-situ eDNA analysis to inform conservation, remediation, and biodiversity management.</div></div>","PeriodicalId":424,"journal":{"name":"Sensing and Bio-Sensing Research","volume":"53 ","pages":"Article 101058"},"PeriodicalIF":4.7,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148657335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Graphene ribbon-based terahertz metamaterial for multi-toxic-gas detection: a comprehensive theoretical framework with machine learning and adaptive sensing","authors":"Aymen A. Altae,&nbsp;Ali Soldoozy,&nbsp;Ilghar Rezaei,&nbsp;Sadegh Biabanifard,&nbsp;Toktam Aghaee","doi":"10.1016/j.sbsr.2026.101059","DOIUrl":"10.1016/j.sbsr.2026.101059","url":null,"abstract":"<div><div>We present a comprehensive theoretical and numerical framework for the simultaneous detection of multiple toxic gases (SO<span><math><msub><mspace></mspace><mn>2</mn></msub></math></span>, NO<span><math><msub><mspace></mspace><mn>2</mn></msub></math></span>, CO, NH<span><math><msub><mspace></mspace><mn>3</mn></msub></math></span>, H<span><math><msub><mspace></mspace><mn>2</mn></msub></math></span>S) using a graphene ribbon-based terahertz metamaterial absorber. The structure is designed to exhibit multiple resonant modes that exactly match the characteristic rotational-vibrational fingerprints of the target gases in the 0.5–6 THz range. A rigorous multi-physics model is developed, combining quantum-mechanical molecular response via Voigt profiles, a multi-resonance Lorentzian metamaterial model, competitive Langmuir-Hill adsorption isotherms, Maxwell-Garnett effective medium theory for gas-metamaterial composites, and noise analysis for limit of detection (LOD) determination. Closed-form expressions for sensitivity, selectivity, response time, and cross-sensitivity are derived. Numerical simulations predict sub-ppm LODs (0.8 ppm for SO<span><math><msub><mspace></mspace><mn>2</mn></msub></math></span>, 0.6 ppm for NO<span><math><msub><mspace></mspace><mn>2</mn></msub></math></span>), response times below 0.5 s, and selectivity ratios exceeding 20:1 against common interferents such as H<span><math><msub><mspace></mspace><mn>2</mn></msub></math></span>O and CO<span><math><msub><mspace></mspace><mn>2</mn></msub></math></span>. A random forest classifier achieves 98.2% accuracy A random forest classifier achieves 98.2% accuracy on synthetic spectral datasets, with a detailed analysis of accuracy versus signal-to-noise ratio. Environmental stability is analyzed over temperature (250–350 K), humidity (0–100% RH), and long-term operation (3 years) using theoretical degradation models. Adaptive sensing and sensor fusion algorithms are shown to improve measurement efficiency and accuracy. The theoretical predictions are presented with clear discussion of model limitations, including effective medium theory applicability, surface adsorption effects, and the need for experimental validation. This work establishes a solid theoretical foundation for the development of low-cost, real-time, multi-gas sensors for environmental monitoring, industrial safety, and healthcare.</div></div>","PeriodicalId":424,"journal":{"name":"Sensing and Bio-Sensing Research","volume":"53 ","pages":"Article 101059"},"PeriodicalIF":4.7,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148770547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a contactless multimodal imaging and edge AI-based real-time monitoring system for contrast media extravasation: A translational feasibility study","authors":"Sen-Ping Lin,&nbsp;Wei-Chi Chen,&nbsp;Yung-Cheng Wang,&nbsp;Kang-Ping Lin,&nbsp;Wen-Chang Tseng","doi":"10.1016/j.sbsr.2026.101078","DOIUrl":"10.1016/j.sbsr.2026.101078","url":null,"abstract":"<div><h3>Background</h3><div>Contrast media extravasation (CMEX) during CT power injection may cause tissue injury, yet early detection remains difficult with visual inspection. To address single-modality sensing limitations, we developed a contactless multimodal monitoring system integrating uncooled thermography (256 × 192 pixels), dual-band near-infrared (NIR) imaging, edge computing, and AI analysis for CMEX screening.</div></div><div><h3>Methods</h3><div>The system was deployed on an NVIDIA Jetson Nano platform, integrating an uncooled thermal sensor and dual CMOS sensors at 850 nm and 940 nm. Homography-based registration using the butterfly needle as reference enabled multimodal fusion. A modified U-Net generated vascular masks from 850 nm images, and Efficient Net performed binary extravasation classification. Validation was conducted exclusively using a temperature-controlled phantom under varying monitoring distances, vessel temperatures, and leakage volumes without human subjects.</div></div><div><h3>Results</h3><div>After Tensor RT FP16/INT8 optimization, the system achieved real-time throughput of 15–20 fps with 150–250 ms latency and 2–4 mm mean registration error. At 100 cm, the thermal system maintained a Thermal Diffusion Ratio of 1.42 ± 0.10. Leakage Diffusion Ratio increased significantly with leakage volume, while the 940 nm channel showed 8–15% signal attenuation. Vascular segmentation achieved a Dice Similarity Coefficient of 0.882 ± 0.031 and IoU of 0.789 ± 0.042. Efficient Net achieved 0.9979 recall, 0.7997 precision, 0.6000 specificity, and 0.8451 accuracy. Ablation analysis confirmed multimodal fusion outperformed unimodal sensing (AUC = 0.93 vs. 0.79 for thermal-only, <em>p</em> &lt; 0.01).</div></div><div><h3>Conclusions</h3><div>This engineering prototype demonstrates proof-of-concept real-time CMEX monitoring with ultra-high screening sensitivity under controlled phantom conditions, establishing a preclinical foundation for trials.</div></div>","PeriodicalId":424,"journal":{"name":"Sensing and Bio-Sensing Research","volume":"53 ","pages":"Article 101078"},"PeriodicalIF":4.7,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148958733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust OCT-based thenar skin thickness quantification via a dual-path extraction framework","authors":"MingHui Chen,&nbsp;ZhengMao Zhao,&nbsp;WeiJie Xing,&nbsp;XiaoRu Feng,&nbsp;Chang Chen,&nbsp;Lin Zhou,&nbsp;You Wu","doi":"10.1016/j.sbsr.2026.101076","DOIUrl":"10.1016/j.sbsr.2026.101076","url":null,"abstract":"<div><div>Accurate skin-layer thickness quantification is needed for depth calibration in multiple μ-spatially offset Raman spectroscopy (mμSORS)-based noninvasive glucose sensing. Existing OCT-based analyses often estimate skin thickness from depth-intensity profiles generated by large-scale A-line averaging. However, this averaging can attenuate the OCT-visible lower stratum corneum (SC) boundary and make SC thickness estimation unstable in some volumes. Here, we present a dual-path SC thickness quantification framework. The framework uses the conventional profile-based pathway when the SC-related profile feature is preserved, and uses a segmentation-based recovery pathway when profile cues are degraded. In the recovery pathway, SC thickness is computed from spatially explicit SC boundaries delineated on individual B-scans, thereby reducing information loss caused by global averaging. On an independent thickness-evaluation cohort of 26 participants with 156 manually annotated B-scans, the framework showed strong agreement with manual reference measurements, with a participant-level MAE of 5.17 μm (0.6466 pixels) and RMSE of 6.58 μm (0.8225 pixels). These results suggest that OCT-derived SC thickness can provide useful geometric information for mμSORS depth calibration, especially when conventional profile-based estimation is unstable.</div></div>","PeriodicalId":424,"journal":{"name":"Sensing and Bio-Sensing Research","volume":"53 ","pages":"Article 101076"},"PeriodicalIF":4.7,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148958734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}