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Recent Advances in Optical Sensors
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Recent Advances in Optical Sensors

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Optics and Lasers".

Deadline for manuscript submissions: 20 December 2025 | Viewed by 582

Special Issue Editors

Dr. Oscar E. Bonilla Manrique

E-Mail Website
Guest Editor
Electronics Technology Department, Carlos III University of Madrid, 28911 Leganés, Spain
Interests: spectroscopy techniques; photoacoustics; thermoacoustics; dispersion; quantum cascade lasers; fiber optic based sensors
Dr. Pedro Martín-Mateos

E-Mail Website
Guest Editor
Electronics Technology Department, Carlos III University of Madrid, 28911 Leganés, Spain
Interests: Spectroscopy techniques, radiometry, imagin hyperspectral
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is dedicated to recent advances in optical sensors, a rapidly growing area that has a significant impact on a variety of industrial, medical and environmental applications. Optical sensors, which use light to detect changes in the environment or in objects, have undergone a remarkable evolution thanks to innovations in materials, manufacturing technologies and signal processing. This has made it possible to improve the accuracy, sensitivity and selectivity of measurements, opening up new possibilities in fields such as health, safety, environmental monitoring and automation.

The main objective of this Special Issue is to bring together original contributions presenting recent developments in the design, fabrication and application of optical sensors. Submitted papers are expected to address key aspects, such as new sensing principles, improvements in sensor configurations, advances in photonics-based technologies and integrated optics, as well as innovative approaches to sensing under extreme conditions. Authors are invited to present experimental, theoretical or simulation studies, with a focus on the practical applicability of optical sensors and the impact they may have on future technologies.

This Special Issue will provide a platform for the exchange of ideas and advances which will help define the future of optical sensors in multiple scientific and technological areas.

Dr. Oscar E. Bonilla Manrique
Dr. Pedro Martín-Mateos
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • optical sensor
  • spectroscopy
  • integrated optics
  • multisensing of different compounds
  • optical applications
  • optical sensor applications
  • new technologies
  • design and miniaturization of optical sensors
  • instrumentation

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Published Papers (1 paper)

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Research

16 pages, 2561 KiB  
Article
A Non-Invasive and Highly Accurate Multi-Wavelength Light Near-Infrared Glucose Sensor Using A Multilevel Metric Learning–Back Propagation Network
by Yuwei Chen, Chenxi Li, Bo Gao, Huangrong Xu and Weixing Yu
Appl. Sci. 2025, 15(10), 5652; https://doi.org/10.3390/app15105652 - 19 May 2025
Viewed by 338
Abstract
Non-invasive near-infrared (NIR) human glucose sensors have attracted great interest in managing diabetes mellitus and those with complex sensing backgrounds due to glucose absorption spectrum overlap. Here, we propose a non-invasive and highly accurate multi-wavelength light NIR glucose sensor using a multilevel metric [...] Read more.
Non-invasive near-infrared (NIR) human glucose sensors have attracted great interest in managing diabetes mellitus and those with complex sensing backgrounds due to glucose absorption spectrum overlap. Here, we propose a non-invasive and highly accurate multi-wavelength light NIR glucose sensor using a multilevel metric learning-back propagation network, i.e., “HMML-BP”, based on the narrowband multi-wavelength light NIR system. Our human glucose sensing method combines the advantages of this system and an HMML-BP network. The latter is composed of multilevel metric learning modules and a BP network to predict blood glucose concentrations. The narrowband multi-wavelength light NIR sensing system consists of six-channel NIR filters with center wavelengths of 850 nm, 940 nm, 1300 nm, 1400 nm, 1550 nm, and 1650 nm and a spectral resolution below 12 nm. The six NIR channels measured were first entered into the MML modules to build 3D multi-wavelength light data. Next, 3D multi-wavelength light data were optimized by stochastic neighbor embedding. Diffusion maps and factor analysis algorithms were used to retain effective NIR information. Finally, the optimized data were utilized as the BP network input to predict blood glucose concentrations. The predicted results showed that the factor analysis algorithm had the best performance in our HMML-BP network and that all the predicted glucose values fell into region A, with a mean absolute relative difference of 9.98%, meeting the requirements of daily glucose monitoring. Our blood glucose sensing method provides a new way of utilizing multi-wavelength light and hyperspectral information for smart human glucose monitoring. Full article
(This article belongs to the Special Issue Recent Advances in Optical Sensors)
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