Go to:
Logótipo
Comuta visibilidade da coluna esquerda
Você está em: Start > Publications > View > Towards real-time identification of trapped particles with UMAP-based classifiers
Publication

Publications

Towards real-time identification of trapped particles with UMAP-based classifiers

Title
Towards real-time identification of trapped particles with UMAP-based classifiers
Type
Article in International Conference Proceedings Book
Year
2022
Authors
Teixeira, J
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. View Authenticus page Without ORCID
Rocha, V
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
Oliveira, J
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
Jorge, PAS
(Author)
FCUP
View Personal Page You do not have permissions to view the institutional email. Search for Participant Publications View Authenticus page View ORCID page
Silva, NA
(Author)
Other
View Personal Page You do not have permissions to view the institutional email. Search for Participant Publications View Authenticus page Without ORCID
Conference proceedings International
5th International Conference on Applications of Optics and Photonics, AOP 2022
17 July 2022 through 22 July 2022
Indexing
Publicação em Scopus Scopus - 0 Citations
Other information
Authenticus ID: P-00X-Q8H
Abstract (EN): Optical trapping provides a way to isolate, manipulate, and probe a wide range of microscopic particles. Moreover, as particle dynamics are strongly affected by their shape and composition, optical tweezers can also be used to identify and classify particles, paving the way for multiple applications such as intelligent microfluidic devices for personalized medicine purposes, or integrated sensing for bioengineering. In this work, we explore the possibility of using properties of the forward scattered radiation of the optical trapping beam to analyze properties of the trapped specimen and deploy an autonomous classification algorithm. For this purpose, we process the signal in the Fourier domain and apply a dimensionality reduction technique using UMAP algorithms, before using the reduced number of features to feed standard machine learning algorithms such as K-nearest neighbors or random forests. Using a stratified 5-fold cross-validation procedure, our results show that the implemented classification strategy allows the identification of particle material with accuracies up to 80%, demonstrating the potential of using signal processing techniques to probe properties of optical trapped particles based on the forward scattered light. Furthermore, preliminary results of an autonomous implementation in a standard experimental optical tweezers setup show similar differentiation capabilities for real-time applications, thus opening some opportunities towards technological applications such as intelligent microfluidic devices and solutions for biochemical and biophysical sensing. © Published under licence by IOP Publishing Ltd.
Language: English
Type (Professor's evaluation): Scientific
Documents
We could not find any documents associated to the publication.
Related Publications

Of the same authors

Autonomous Optical Tweezers: From automatic trapping to single particle analysis (2022)
Article in International Conference Proceedings Book
Coutinho, F; Teixeira, J; Rocha, V; Oliveira, J; Jorge, PAS; Silva, NA
Recommend this page Top
Copyright 1996-2025 © Faculdade de Direito da Universidade do Porto  I Terms and Conditions  I Acessibility  I Index A-Z
Page created on: 2025-07-24 at 19:09:25 | Privacy Policy | Personal Data Protection Policy | Whistleblowing