Copertina

Computational Tool for Curve Smoothing Methods Analysis and Surface Plasmon Resonance Biosensor Characterization

Salvato in:
Pubblicato in:Inventions vol. 10, no. 2 (2025), p. 31
Autore principale: Villarim, Mariana Rodrigues
Altri autori: Villarim Andréa Willa Rodrigues, Gazziro Mario, Cavallari, Marco Roberto, Belfort Diomadson Rodrigues, Ando Junior Oswaldo Hideo
Pubblicazione:
MDPI AG
Soggetti:
Data transfer (computers)
Accuracy
Smoothing
Scientific visualization
Data smoothing
Sensors
Signal processing
Spline functions
Optimization
Spectrum analysis
White noise
Data analysis
Biosensors
Algorithms
Real time
Surface plasmon resonance
Light
Dimensional analysis
Software
Accesso online:Citation/Abstract
Full Text + Graphics
Full Text - PDF
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
Abstract:Biosensors based on the surface plasmon resonance (SPR) technique are widely used for analyte detection due to their high selectivity and real-time detection capabilities. However, conventional SPR spectrum analysis can be affected by experimental noise and environmental variations, reducing the accuracy of results. To address these limitations, this study presents the development of an open-source computational tool to optimize SPR biosensor characterization, implemented using MATLAB App Designer (Version R2024b). The tool enables the importation of experimental data, application of different smoothing methods, and integration of traditional and hybrid approaches to enhance accuracy in determining the resonance angle. The proposed tool offers several innovations, such as integration of both traditional and hybrid (angle vs wavelength) analysis modes, implementation of four advanced curve smoothing techniques, including Gaussian filter, Savitzky–Golay, smoothing splines, and EWMA, as well as a user-friendly graphical interface supporting real-time data visualization, experimental data import, and result export. Unlike conventional approaches, the hybrid framework enables multidimensional optimization of SPR parameters, resulting in greater accuracy and robustness in detecting resonance conditions. Experimental validation demonstrated a marked reduction in spectral noise and improved consistency in resonance angle detection across conditions. The results confirm the effectiveness and practical relevance of the tool, contributing to the advancement of SPR biosensor analysis.
ISSN:2411-5134
DOI:10.3390/inventions10020031
Fonte:Advanced Technologies & Aerospace Database