BioPhotonics Signal Analysis: Phase-derived features for microparticles and nanoparticles identification
Data ja resurssit
-
FilterM
Butterworth high-pass filter
-
Pre-ProcessingM
Pre-processing of data (Z-score transformation, Epoching and Noisy segments...
-
Discrete Fourier TransformM
DFT computation via FFT algorithm: DFT computation of an the input vector,...
-
Hilbert TransformM
DFT computation via FFT algorithm: DFT computation of an the input vector,...
-
Hilbert Phase SlopeM
Hilbert Unwrapped phase and Hilbert Unwrapped Phase Slope calculation
-
Phase-based feature extractionM
Computation of 8 phase spectrum-derived features and phase portion of the...
-
ReadMeMD
-
Download all filesM
Lisätietoja
Kenttä | Arvo |
---|---|
Laatija | Beatriz Barros, João Paulo Cunha |
Viimeksi päivitetty | toukokuuta 3, 2024, 15:07 (UTC) |
Luotu | tammikuuta 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 |
Muoto | MATLAB (.m) |
Instrument | An opto-electronic setup based on Optical Fiber Tweezers (OFTs) was used to collect the back-scattering signals. |
Kieli | 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 |
Tyyppi | Code for calculation of phase-derived features of back-scattering signals. |