fast Fourier transform Dotaz Zobrazit nápovědu
Prentice-Hall signal processing series
xvi, 448 s. : il. ; 23 cm
- Klíčová slova
- Fourierova transformace,
- MeSH
- Fourierova analýza MeSH
- matematika MeSH
- signální transdukce MeSH
- Publikační typ
- monografie MeSH
- Konspekt
- Sdělovací technika
- NLK Obory
- přírodní vědy
This study reports on the successful use of a machine learning approach using attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy for the classification and prediction of a donor's sex from the fingernails of 63 individuals. A significant advantage of ATR FT-IR is its ability to provide a specific spectral signature for different samples based on their biochemical composition. The infrared spectrum reveals unique vibrational features of a sample based on the different absorption frequencies of the individual functional groups. This technique is fast, simple, non-destructive, and requires only small quantities of measured material with minimal-to-no sample preparation. However, advanced multivariate techniques are needed to elucidate multiplex spectral information and the small differences caused by donor characteristics. We developed an analytical method using ATR FT-IR spectroscopy advanced with machine learning (ML) based on 63 donors' fingernails (37 males, 26 females). The PLS-DA and ANN models were established, and their generalization abilities were compared. Here, the PLS scores from the PLS-DA model were used for an artificial neural network (ANN) to create a classification model. The proposed ANN model showed a greater potential for predictions, and it was validated against an independent dataset, which resulted in 92% correctly classified spectra. The results of the study are quite impressive, with 100% accuracy achieved in correctly classifying donors as either male or female at the donor level. Here, we underscore the potential of ML algorithms to leverage the selectivity of ATR FT-IR spectroscopy and produce predictions along with information about the level of certainty in a scientifically defensible manner. This proof-of-concept study demonstrates the value of ATR FT-IR spectroscopy as a forensic tool to discriminate between male and female donors, which is significant for forensic applications.
- MeSH
- dospělí MeSH
- elektrokardiografie metody MeSH
- Fourierova analýza MeSH
- infarkt myokardu diagnóza komplikace patologie MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- náhlá srdeční smrt etiologie MeSH
- počítačové zpracování signálu MeSH
- reprodukovatelnost výsledků MeSH
- senioři MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mužské pohlaví MeSH
- senioři MeSH
- Publikační typ
- hodnotící studie MeSH
- MeSH
- dospělí MeSH
- elektrokardiografie metabolismus MeSH
- Fourierova analýza MeSH
- infarkt myokardu diagnóza patofyziologie MeSH
- kontrakce myokardu genetika MeSH
- lidé MeSH
- počítačové zpracování signálu MeSH
- převodní systém srdeční patofyziologie MeSH
- referenční hodnoty MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mužské pohlaví MeSH
A fully automated atmospheric pressure ionization platform has been built and coupled with a commercial high-resolution Fourier transform ion cyclotron resonance mass spectrometer (FTICR-MS) instrument. The outstanding performance of this instrument allowed screening on the basis of exact masses in imaging mode. The main novel aspect was in the integration of the atmospheric pressure ionization imaging into the current software for matrix-assisted laser desorption ionization (MALDI) imaging, which allows the user of this commercial dual-source mass spectrometer to perform MALDI-MS and different ambient MS imaging from the same user interface and to utilize the same software tools. Desorption electrospray ionization (DESI) and desorption atmospheric pressure photoionization (DAPPI) were chosen to test the ambient surface imaging capabilities of this new ionization platform. Results of DESI imaging experiments performed on brain tissue sections are in agreement with previous MS imaging reports obtained by DESI imaging, but due to the high resolution and mass accuracy of the FTICR instrument it was possible to resolve several ions at the same nominal mass in the DESI-MS spectra of brain tissue. These isobaric interferences at low resolution are due to the overlap of ions from different lipid classes with different biological relevance. It was demonstrated that with the use of high-resolution MS fast imaging screening of lipids can be achieved without any preseparation steps. DAPPI, which is a relatively new and less developed ambient ionization technique compared to DESI, was used in imaging mode for the first time ever. It showed promise in imaging of phytocompounds from plant leaves, and selective ionization of a sterol lipid was achieved by DAPPI from a brain tissue sample.
- MeSH
- atmosférický tlak MeSH
- automatizace MeSH
- cyklotrony MeSH
- Fourierova analýza MeSH
- hmotnostní spektrometrie metody přístrojové vybavení MeSH
- listy rostlin metabolismus MeSH
- molekulární zobrazování metody přístrojové vybavení MeSH
- mozek metabolismus MeSH
- myši MeSH
- povrchové vlastnosti MeSH
- šalvěj lékařská metabolismus MeSH
- systémová integrace MeSH
- zvířata MeSH
- Check Tag
- myši MeSH
- zvířata MeSH
- Publikační typ
- práce podpořená grantem MeSH
Contents -- 1 Introduction 1 -- 1.1 Fourier Analysis 2 -- 1.2 Historical Development of Fourier Methods More Statistical Results 30 -- Appendix 34 -- xi -- X/7 CONTENTS -- 4 Harmonic Analysis 37 -- 4.1 Fourier Frequencies 37 -- 4.2 Discrete Fourier Fransform 40 -- 4.3 Decomposing the Sum of Squares 44 -- 4.4 Special Functions 45 -- 4.5 Smooth Functions 53 -- 5 The Fast Fourier Transform -- 5.1 Computational Cost of Fourier Transforms -- 5.2 Two-Factor Case -- 5.3 Application to Harmonic Analysis of Data --
Wiley series in probability and statistics
2nd ed. xiv, 261 s. : il.
- MeSH
- matematika MeSH
- Konspekt
- Přírodní vědy. Matematické vědy
- NLK Obory
- přírodní vědy
High-frequency waveform recordings of biological signals enable more detailed data analysis and deeper physiological exploration. However, the waveform data—like invasive arterial blood pressure (ABP)—are particularly susceptible to frequent contamination with artifacts that can devalue the subsequent calculations like pressure reactivity index (PRx). This study aimed to verify the ability of the short-time Fourier transform (STFT) based algorithm to detect artifacts in the ABP waveform. Four types of modeled artifacts (rectangular, fast impulse, sawtooth and baseline drift) with different durations and amplitudes were inserted into undisturbed ABP waveforms. Short-time Fourier transform with a 5-second time window is computed on artifact-polluted ABP signals to detect changes in the frequency domain caused by these artifacts. An algorithm with three decision-making rules based on the dominant frequency component, standardized power spectrum, and the value of the second harmonic of the dominant frequency was used. Only segments that passed all three rules were labeled as artifact-free. Results indicated high sensitivity (93.35% and 94.83%) in detecting rectangular and sawtooth artifacts, with specificity exceeding 99% for both. Baseline drift artifact was detected with a low sensitivity of 5.02%, and fast impulse was not detected. This study proposes the application of a short-time Fourier transform-based algorithm to enhance the detection of clinically significant artifacts in arterial blood pressure signals, particularly relevant for PRx and other secondary calculations.
