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Sensors 2018, 18(3), 710; https://doi.org/10.3390/s18030710

Single Particle Differentiation through 2D Optical Fiber Trapping and Back-Scattered Signal Statistical Analysis: An Exploratory Approach

1
INESC TEC-INESC Technology and Science, 4200 Porto, Portugal
2
Physics and Astronomy Department, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal
3
Faculty of Engineering, University of Porto, 4200 Porto, Portugal
These authors contributed equally to this work.
Rita S. R. Ribeiro is currently with 4Dcell and Elvesys, Paris, France.
*
Author to whom correspondence should be addressed.
Received: 2 February 2018 / Revised: 16 February 2018 / Accepted: 24 February 2018 / Published: 27 February 2018
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Abstract

Recent trends on microbiology point out the urge to develop optical micro-tools with multifunctionalities such as simultaneous manipulation and sensing. Considering that miniaturization has been recognized as one of the most important paradigms of emerging sensing biotechnologies, optical fiber tools, including Optical Fiber Tweezers (OFTs), are suitable candidates for developing multifunctional small sensors for Medicine and Biology. OFTs are flexible and versatile optotools based on fibers with one extremity patterned to form a micro-lens. These are able to focus laser beams and exert forces onto microparticles strong enough (piconewtons) to trap and manipulate them. In this paper, through an exploratory analysis of a 45 features set, including time and frequency-domain parameters of the back-scattered signal of particles trapped by a polymeric lens, we created a novel single feature able to differentiate synthetic particles (PMMA and Polystyrene) from living yeasts cells. This single statistical feature can be useful for the development of label-free hybrid optical fiber sensors with applications in infectious diseases detection or cells sorting. It can also contribute, by revealing the most significant information that can be extracted from the scattered signal, to the development of a simpler method for particles characterization (in terms of composition, heterogeneity degree) than existent technologies. View Full-Text
Keywords: polymeric optical lenses; optical fibers; micromanipulation; back-scattering; signal processing; features dimensionality reduction techniques; Linear Discriminant Analysis; particles sorting and differentiation polymeric optical lenses; optical fibers; micromanipulation; back-scattering; signal processing; features dimensionality reduction techniques; Linear Discriminant Analysis; particles sorting and differentiation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Paiva, J.S.; Ribeiro, R.S.R.; Cunha, J.P.S.; Rosa, C.C.; Jorge, P.A.S. Single Particle Differentiation through 2D Optical Fiber Trapping and Back-Scattered Signal Statistical Analysis: An Exploratory Approach. Sensors 2018, 18, 710.

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