ArticleSensors (Basel, Switzerland)2014
Recent developments in optical detection technologies in lab-on-a-chip devices for biosensing applications.
Article in Sensors (Basel, Switzerland), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.
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Who cites it
67 citing papers in PubMed, 298 citations in OpenAlex.
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7 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The field of microfluidics has yet to develop practical devices that provide real clinical value. One of the main reasons for this is the difficulty in realizing low-cost, sensitive, reproducible, and portable analyte detection microfluidic systems. Previous research has addressed two main approaches for the detection technologies in lab-on-a-chip devices: (a) study of the compatibility of conventional instrumentation with microfluidic structures, and (b) integration of innovative sensors contained within the microfluidic system. Despite the recent advances in electrochemical and mechanical based sensors, their drawbacks pose important challenges to their application in disposable microfluidic devices. Instead, optical detection remains an attractive solution for lab-on-a-chip devices, because of the ubiquity of the optical methods in the laboratory. Besides, robust and cost-effective devices for use in the field can be realized by integrating proper optical detection technologies on chips. This review examines the recent developments in detection technologies applied to microfluidic biosensors, especially addressing several optical methods, including fluorescence, chemiluminescence, absorbance and surface plasmon resonance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.