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Sensors
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Optical Biosensors: Pioneering Technologies and Applications
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Optical Biosensors: Pioneering Technologies and Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors Development".

Deadline for manuscript submissions: 25 September 2024 | Viewed by 1939

Special Issue Editors

Dr. Akhilesh Pathak

E-Mail Website
Guest Editor
Center for Smart Structures and Materials, Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208, USA
Interests: fiber bragg gratings (FBG); PCF; sensors; plasmonic; waveguide; optical fibers; optical fiber sensor; finite element method; FEM; simulation; SPR; FBG; MOF; volatile organic compound (VOC); COMSOL; health; biosensors
Special Issues, Collections and Topics in MDPI journals
Dr. Rahul Gangwar

E-Mail Website
Guest Editor
Rajdhani College, University of Delhi, Delhi, India
Interests: fiber optics; photonics; photonic crystal fiber; sensor; chemical sensor; physical sensor

Special Issue Information

Dear Colleagues,

Optical biosensors gain huge interest among researchers due to their wide range of applications in healthcare and environmental monitoring. The optical biosensor utilizes the property of propagated light in order to detect and analyze biological and chemical interactions; therefore, it provides several benefits including exceptional in situ monitoring, high sensitivity, and rapid response time. Optical biosensors generally involve the study of light–matter interaction for target-specific detection. This interaction leads to a change in the property of the measurable optical signal, which can be correlated to the concentration or presence of the analytes. The optical signals through the optical devices can be generated via several mechanisms, such as variation in fluorescence, absorbance, interferometry, evanescent wave coupling, and surface plasmon resonance. This Special Issue is dedicated to exploring the groundbreaking technologies and applications of optical biosensors. The applications of optical biosensors are vast and diverse. These biosensors play a crucial role in the detection of several diseases at an early stage by detecting pathogens, biomarkers, and genetic disorders. Optical biosensors are also useful in other sectors such as environmental sensing, food safety monitoring, and drug delivery. This Special Issue highlights the most recent development in the area of optical biosensors, including cutting-edge fabrication techniques, innovative sensing configurations, and the integration of optical devices with novel sensing materials. This Special Issue includes studies that demonstrate successful implementations of optical biosensors in these domains, emphasizing their remarkable accuracy, specificity, and potential for high-throughput analysis. The articles featured in this Special Issue explore various sensing devices and novel configurations, emphasizing their potential to achieve high sensitivity and a rapid response time.

Dr. Akhilesh Pathak
Dr. Rahul Gangwar
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. Sensors 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 2600 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

• fiber optics and photonic devices
• smart sensing materials
• medical and biomedical optics
• optical and photonic materials (inc. metamaterials)
• polymer and nanomaterial
• biophotonics

Published Papers (1 paper)

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Research

18 pages, 11662 KiB  
Article
A Comparative Analysis of Various Machine Learning Algorithms to Improve the Accuracy of HbA1c Estimation Using Wrist PPG Data
by Shama Satter, Tae-Ho Kwon and Ki-Doo Kim
Sensors 2023, 23(16), 7231; https://doi.org/10.3390/s23167231 - 17 Aug 2023
Cited by 2 | Viewed by 1552
Abstract
Due to the inconvenience of drawing blood and the possibility of infection associated with invasive methods, research on non-invasive glycated hemoglobin (HbA1c) measurement methods is increasing. Utilizing wrist photoplethysmography (PPG) with machine learning to estimate HbA1c can be a promising method for non-invasive [...] Read more.
Due to the inconvenience of drawing blood and the possibility of infection associated with invasive methods, research on non-invasive glycated hemoglobin (HbA1c) measurement methods is increasing. Utilizing wrist photoplethysmography (PPG) with machine learning to estimate HbA1c can be a promising method for non-invasive HbA1c monitoring in diabetic patients. This study aims to develop a HbA1c estimation system based on machine learning algorithms using PPG signals obtained from the wrist. We used a PPG based dataset of 22 subjects and algorithms such as extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), Categorical Boost (CatBoost) and random forest (RF) to estimate the HbA1c values. Note that the AC-to-DC ratios for three wavelengths were newly adopted as features in addition to the previously acquired 15 features from the PPG signal and a comparative analysis was performed between the performances of several algorithms. We showed that feature-importance-based selection can improve performance while reducing computational complexity. We also showed that AC-to-DC ratio (AC/DC) features play a dominant role in improving HbA1c estimation performance and, furthermore, a good performance can be obtained without the need for external features such as BMI and SpO2. These findings may help shape the future of wrist-based HbA1c estimation (e.g., via a wristwatch or wristband), which could increase the scope of noninvasive and effective monitoring techniques for diabetic patients. Full article
(This article belongs to the Special Issue Optical Biosensors: Pioneering Technologies and Applications)
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