BioPhotonics Signal Analysis: Phase-derived features for microparticles and nanoparticles identification
Data and Resources
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FilterM
Butterworth high-pass filter
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Pre-ProcessingM
Pre-processing of data (Z-score transformation, Epoching and Noisy segments...
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Discrete Fourier TransformM
DFT computation via FFT algorithm: DFT computation of an the input vector,...
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Hilbert TransformM
DFT computation via FFT algorithm: DFT computation of an the input vector,...
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Hilbert Phase SlopeM
Hilbert Unwrapped phase and Hilbert Unwrapped Phase Slope calculation
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Phase-based feature extractionM
Computation of 8 phase spectrum-derived features and phase portion of the...
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ReadMeMD
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Download all filesM
Additional Info
Field | Value |
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Author | Beatriz Barros, João Paulo Cunha |
Last Updated | May 3, 2024, 15:07 (UTC) |
Created | January 11, 2024, 15:06 (UTC) |
Citation | Barros, B., & Cunha, J. P. (2024). BioPhotonics Signal Analysis: Phase-derived features for microparticles and nanoparticles identification [Data set]. INESC TEC. https://doi.org/10.25747/XTXJ-AV32 |
Creation Date | September, 2022 |
DOI | https://doi.org/10.25747/XTXJ-AV32 |
Format | MATLAB (.m) |
Instrument | An opto-electronic setup based on Optical Fiber Tweezers (OFTs) was used to collect the back-scattering signals. |
Language | EN |
Project | Phase-based BioPhotonics Signal Analysis |
Relation | [1] Barros, B. J., & Cunha, J. P. S. (2022, June). Micron-Sized Bioparticles Detection through Phase Analysis of Back-Scattering Signals from Optical Fiber Tweezers: An Exploratory Study. In 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON) (pp. 271-275). IEEE. |
Size | 10 KB |
Software | MATLAB |
Type | Code for calculation of phase-derived features of back-scattering signals. |