Optical biosensors: A decade in review
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Miniaturized, specific, rapid response and economical biosensors are finding applications in biotechnology, environmental studies, agriculture, food inspection and safety, disease diagnosis and medical utilities. Of the many categories of biosensors, optical biosensors have brought about an extra edge in sensing applications due to their selective, rapid and extremely sensitive measurements. Biosensors are analytical tools used to detect specific analytes such as cholesterol, urea, etc. having biomolecules such as nucleic acids, proteins, carbohydrates as key element for detecting these analytes along with a transducer and a data analysis and visualization tool. In case of optical biosensors the analyte is detected using light with either label based or label free techniques. In this paper some of the marked advances in the last decade in the field of optical biosensors have been reviewed with an emphasis on their fabrication approaches and growing application areas. Along with some of the carefully selected article on new developments in optical biosensors through the last decade, a brief historical review of optical biosensors since the breakthrough in optical biosensors in 1970s has also been presented. Another focus of the current review is the classification of biosensors, typical structures along with emerging developments in optical biosensing that are likely to impact the current decade. Major application areas and emerging applications through the last decade have been outlined to present a clear picture on the versatility of optical biosensors. Finally, the review also considers the challenges and future of emerging optical biosensing technologies in the current decade.
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Label-based optical techniques are colorimetric or fluorometric methods that have demonstrated great promise for monitoring metabolites, glucose, and other biomarkers in sweat, tears, or interstitial fluid.
“Label-based optical techniques are colorimetric or fluorometric methods [172] which have demonstrated great promise for monitoring of metabolites, glucose, and other biomarkers in sweat, tears, or interstitial fluid, providing valuable insights for disease management and preventive healthcare [173,174].”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [172]
Integration of these materials into flexible substrates and microfluidic devices has facilitated the development of wearable devices that are lightweight, conformable, and comfortable for long-term use.
“Integration of these materials into flexible substrates and microfluidic devices has facilitated the development of wearable devices that are lightweight, conformable, and comfortable for long-term use [172].”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [172]
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- Authors
- Singh, A. K., Mittal, S., Das, M., Saharia, A., & Tiwari, M.
- Affiliations
- Manipal University Jaipur (IN)
- Vellore Institute of Technology University (IN)
- Corresponding author
- Tiwari, Manish
- Venue
- Alexandria Engineering Journal
- Publisher
- Elsevier BV
- Published
- 2023-03
- Volume
- 67
- Pages
- 673-691
- ISSN
- 1110-0168 (ISSN-L)
- OpenAlex
- W4320474624
- Cited by
- 292
- References
- 266
- Citations by year
- 2026: 64 · 2025: 108 · 2024: 87 · 2023: 33
- FWCI
- 26.02
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Alexandria Engineering Journal (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced biosensing and bioanalysis techniques
- Physical Sciences › Engineering › Biomedical Engineering › Biosensors and Analytical Detection
- Physical Sciences › Chemical Engineering › Bioengineering › Analytical Chemistry and Sensors
- Keywords
- optical biosensors, biosensor fabrication, label-free detection, biosensor classification, biosensor applications, biosensor miniaturization, disease diagnosis, food safety, environmental monitoring
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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