Intelligent Optical Tweezers with deep neural network classifiers

• Type: Article in International Scientific Journal
• Date: 2022

Authors

Rocha, V (Author) Other; Oliveira, J (Author) Other; Guerreiro, A (Author) FCUP; Jorge, PAS (Author) FCUP; Silva, NA (Author) Other

Journal

Title: EPJ Web of Conferences

Vol. 27

ISSN: 2101-6275

Publisher: EDP Sciences

Other information

Authenticus ID: P-00X-J77

DOI: 10.1051/epjconf/202226613029

Abstract (EN): <jats:p>Optical tweezers use light to trap and manipulate mesoscopic scaled particles with high precision making them a useful tool in a plethora of natural sciences, with emphasis on biological applications. In principle, the Brownian-like dynamics reflect trapped particle properties making it a robust source of information. In this work, we exploit this information by plotting histogram based images of 250<jats:italic>ms</jats:italic> of position or displacement used as input to a Convolution Neural Network. Results of 2-fold stratified cross-validation show satisfying classifications between sizes or types of particles: Polystyrene and Polymethilmethacrylate thus highlighting the potential of CNN approaches in faster and non-invasive applications in intelligent opto and microfluidic devices using optical trapping tools.</jats:p>

Language: English

Type (Professor's evaluation): Scientific