Particle Classification through the Analysis of the Forward Scattered Signal in Optical Tweezers

• Type: Article in International Scientific Journal
• Date: 2021

Authors

Carvalho, IA (Author) Other; Silva, NA (Author) Other; Rosa, CC (Author) FCUP; Coelho, LCC (Author) FCUP; Jorge, PAS (Author) FCUP

Journal

Title: Sensors

Vol. 21 No. 2

Final page: 6181

ISSN: 1424-3210

Publisher: MDPI

Indexing

ISI Web of Knowledge - 7 Citations

Scopus - 9 Citations

Other information

Authenticus ID: P-00V-D0F

DOI: 10.3390/s21186181

Abstract (EN): The ability to select, isolate, and manipulate micron-sized particles or small clusters has made optical tweezers one of the emergent tools for modern biotechnology. In conventional setups, the classification of the trapped specimen is usually achieved through the acquired image, the scattered signal, or additional information such as Raman spectroscopy. In this work, we propose a solution that uses the temporal data signal from the scattering process of the trapping laser, acquired with a quadrant photodetector. Our methodology rests on a pre-processing strategy that combines Fourier transform and principal component analysis to reduce the dimension of the data and perform relevant feature extraction. Testing a wide range of standard machine learning algorithms, it is shown that this methodology allows achieving accuracy performances around 90%, validating the concept of using the temporal dynamics of the scattering signal for the classification task. Achieved with 500 millisecond signals and leveraging on methods of low computational footprint, the results presented pave the way for the deployment of alternative and faster classification methodologies in optical trapping technologies.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12