Fetal phonocardiography is a non-invasive, completely passive and low-cost method based on sensing acoustic signals from the maternal abdomen. However, different types of interference are sensed along with the desired fetal phonocardiography. This study focuses on the comparison of fetal phonocardiography filtering using eight algorithms: Savitzky-Golay filter, finite impulse response filter, adaptive wavelet transform, maximal overlap discrete wavelet transform, variational mode decomposition, empirical mode decomposition, ensemble empirical mode decomposition, and complete ensemble empirical mode decomposition with adaptive noise. The effectiveness of those methods was tested on four types of interference (maternal sounds, movement artifacts, Gaussian noise, and ambient noise) and eleven combinations of these disturbances. The dataset was created using two synthetic records r01 and r02, where the record r02 was loaded with higher levels of interference than the record r01. The evaluation was performed using the objective parameters such as accuracy of the detection of S1 and S2 sounds, signal-to-noise ratio improvement, and mean error of heart interval measurement. According to all parameters, the best results were achieved using the complete ensemble empirical mode decomposition with adaptive noise method with average values of accuracy = 91.53% in the detection of S1 and accuracy = 68.89% in the detection of S2. The average value of signal-to-noise ratio improvement achieved by complete ensemble empirical mode decomposition with adaptive noise method was 9.75 dB and the average value of the mean error of heart interval measurement was 3.27 ms.

• MeSH
• algoritmy MeSH
• fonokardiografie metody   MeSH
• počítačové zpracování signálu * MeSH
• poměr signál - šum MeSH
• vlnková analýza * MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

As it was mentioned in the previous part of this work (Part I)-the advanced signal processing methods are one of the quickest and the most dynamically developing scientific areas of biomedical engineering with their increasing usage in current clinical practice. In this paper, which is a Part II work-various innovative methods for the analysis of brain bioelectrical signals were presented and compared. It also describes both classical and advanced approaches for noise contamination removal such as among the others digital adaptive and non-adaptive filtering, signal decomposition methods based on blind source separation, and wavelet transform.

• Klíčová slova
• bioelectrical signals, brain signals, electrocorticography, electroencephalography, signal processing methods,
• MeSH
• mozek MeSH
• počítačové zpracování signálu * MeSH
• vlnková analýza * MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Fetal electrocardiography is among the most promising methods of modern electronic fetal monitoring. However, before they can be fully deployed in the clinical practice as a gold standard, the challenges associated with the signal quality must be solved. During the last two decades, a great amount of articles dealing with improving the quality of the fetal electrocardiogram signal acquired from the abdominal recordings have been introduced. This article aims to present an extensive literature survey of different non-adaptive signal processing methods applied for fetal electrocardiogram extraction and enhancement. It is limiting that a different non-adaptive method works well for each type of signal, but independent component analysis, principal component analysis and wavelet transforms are the most commonly published methods of signal processing and have good accuracy and speed of algorithms.

• Klíčová slova
• digital signal processing, fetal electrocardiogram extraction, fetal monitoring, non-adaptive filtering,
• MeSH
• algoritmy MeSH
• analýza hlavních komponent MeSH
• elektrody MeSH
• elektrokardiografie metody   MeSH
• lidé MeSH
• plod fyziologie   MeSH
• počítačové zpracování signálu * MeSH
• vlnková analýza MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Comparison and classification of organisms based on molecular data is an important task of computational biology, since at least parts of DNA sequences for many organisms are available. Unfortunately, methods for comparison are computationally very demanding, suitable only for short sequences. In this paper, we focus on the redundancy of genetic information stored in DNA sequences. We proposed rules for downsampling of DNA signals of cumulated phase. According to the length of an original sequence, we are able to significantly reduce the amount of data with only slight loss of original information. Dyadic wavelet transform was chosen for fast downsampling with minimum influence on signal shape carrying the biological information. We proved the usability of such new short signals by measuring percentage deviation of pairs of original and downsampled signals while maintaining spectral power of signals. Minimal loss of biological information was proved by measuring the Robinson-Foulds distance between pairs of phylogenetic trees reconstructed from the original and downsampled signals. The preservation of inter-species and intra-species information makes these signals suitable for fast sequence identification as well as for more detailed phylogeny reconstruction.

• Klíčová slova
• Compression, Cumulated phase, DWT, Downsampling, Genomic signal, Phylogeny, Sequence identification,
• MeSH
• fylogeneze * MeSH
• genom * MeSH
• modely genetické * MeSH
• sekvenční analýza DNA metody   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

BACKGROUND: The presence of parasite interference signals could cause serious problems in the registration of ECG signals and many works have been done to suppress electromyogram (EMG) artifacts noises and disturbances from electrocardiogram (ECG). Recently, new developed techniques based on global and local transforms have become popular such as wavelet shrinkage approaches (1995) and time-frequency dependent threshold (1998). Moreover, other techniques such as artificial neural networks (2003), energy thresholding and Gaussian kernels (2006) are used to improve previous works. This review summarizes windowed techniques of the concerned issue. METHODS AND RESULTS: We conducted a mathematical method based on two sets of information, which are dominant scale of QRS complexes and their domain. The task is proposed by using a varying-length window that is moving over the whole signals. Both the high frequency (noise) and low frequency (base-line wandering) removal tasks are evaluated for manually corrupted ECG signals and are validated for actual recorded ECG signals. CONCLUSIONS: Although, the simplicity of the method, fast implementation, and preservation of characteristics of ECG waves represent it as a suitable algorithm, there may be some difficulties due to pre-stage detection of QRS complexes and specification of algorithm's parameters for varying morphology cases.

• MeSH
• algoritmy MeSH
• elektrokardiografie * MeSH
• lidé MeSH
• počítačové zpracování signálu * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

The assessment of ECG signal quality after compression is an essential part of the compression process. Compression facilitates the signal archiving, speeds up signal transmission, and reduces the energy consumption. Conversely, lossy compression distorts the signals. Therefore, it is necessary to express the compression performance through both compression efficiency and signal quality. This paper provides an overview of objective algorithms for the assessment of both ECG signal quality after compression and compression efficiency. In this area, there is a lack of standardization, and there is no extensive review as such. 40 methods were tested in terms of their suitability for quality assessment. For this purpose, the whole CSE database was used. The tested signals were compressed using an algorithm based on SPIHT with varying efficiency. As a reference, compressed signals were manually assessed by two experts and classified into three quality groups. Owing to the experts' classification, we determined corresponding ranges of selected quality evaluation methods' values. The suitability of the methods for quality assessment was evaluated based on five criteria. For the assessment of ECG signal quality after compression, we recommend using a combination of these methods: PSim SDNN, QS, SNR1, MSE, PRDN1, MAX, STDERR, and WEDD SWT.

• MeSH
• algoritmy MeSH
• databáze faktografické MeSH
• elektrokardiografie * MeSH
• komprese dat MeSH
• počítačové zpracování signálu * MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Measures from the theory of nonlinear dynamics were applied on complex fractionated atrial electrograms (CFAEs) in order to characterize their physiological dynamic behavior. The results were obtained considering 113 short term atrial electrograms (A-EGMs) which were annotated by three experts into four classes of fractionation according to A-EGMs signal regularity. The following measures were applied on A-EGM signals: General Correlation Dimension, Approximate Entropy, Detrended Fluctuation Analysis, Lempel-Ziv Complexity, and Katz-Sevcik, Variance and Box Counting Fractal Dimension. Assessment of disorganization was evaluated by a Kruskal Wallis statistical test. Except Detrended Fluctuation Analysis and Variance Fractal Dimension, the CFAE disorganization was found statistically significant even for low significant level alpha = 0.001. Moreover, the increasing complexity of A-EGM signals was reflected by higher values of General Correlation Dimension of order 1 and Approximate Entropy.

• MeSH
• algoritmy MeSH
• analýza rozptylu MeSH
• automatizace metody   MeSH
• elektrokardiografie metody   MeSH
• entropie MeSH
• fibrilace síní patofyziologie   MeSH
• fraktály MeSH
• lidé MeSH
• srdeční síně patofyziologie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

The low density lipoprotein receptor (LDLR) is a transmembrane protein that plays a key role in cholesterol metabolism. It contains 860 amino acids including a 21 amino acid long signal sequence, which directs the protein into the endoplasmic reticulum. Mutations in the LDLR gene lead to cholesterol accumulation in the plasma and results in familial hypercholesterolemia (FH). Knowledge of the impact of a mutation on the LDLR protein structure and function is very important for the diagnosis and management of FH. Unfortunately, for a large proportion of mutations this information is still missing. In this study, we focused on the LDLR signal sequence and carried out functional and in silico analyses of two sequence changes, p.(Gly20Arg) and p.(Leu15Pro), localized in this part of the LDLR. Our results revealed that the p.(Gly20Arg) change, previously described as disease causing, has no detrimental effect on protein expression or LDL particle binding. In silico analysis supports this observation, showing that both the wt and p.(Gly20Arg) signal sequences adopt an expected α-helix structure. In contrast, the mutation p.(Leu15Pro) is not associated with functional protein expression and exhibits a structure with disrupted a α-helical arrangement in the signal sequence, which most likely affects protein folding in the endoplasmic reticulum.

• Klíčová slova
• Endoplasmic reticulum, Familial hypercholesterolemia, Fluorescence microscopy, LDL, Modeling, Mutations, Signal sequence,
• MeSH
• arginin chemie   MeSH
• CHO buňky MeSH
• Cricetulus MeSH
• endoplazmatické retikulum metabolismus   MeSH
• glycin chemie   MeSH
• heterozygot MeSH
• hyperlipoproteinemie typ II krev   genetika   MeSH
• konfokální mikroskopie MeSH
• křečci praví MeSH
• LDL-receptory genetika   metabolismus   MeSH
• leucin chemie   MeSH
• lidé MeSH
• mutace MeSH
• prolin chemie   MeSH
• proteiny - lokalizační signály genetika   MeSH
• rodokmen MeSH
• sbalování proteinů MeSH
• sekundární struktura proteinů MeSH
• zvířata MeSH
• Check Tag
• křečci praví MeSH
• lidé MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• arginin MeSH
• glycin MeSH
• LDL-receptory MeSH
• LDLR protein, human MeSH Prohlížeč
• leucin MeSH
• prolin MeSH
• proteiny - lokalizační signály MeSH

OBJECTIVE: T2 maps are more vendor independent than other MRI protocols. Multi-echo spin-echo signal decays to a non-zero offset due to imperfect refocusing pulses and Rician noise, causing T2 overestimation by the vendor's 2-parameter algorithm. The accuracy of the T2 estimate is improved, if the non-zero offset is estimated as a third parameter. Three-parameter Levenberg-Marquardt (LM) T2 estimation takes several minutes to calculate, and it is sensitive to initial values. We aimed for a 3-parameter fitting algorithm that was comparably accurate, yet substantially faster. METHODS: Our approach gains speed by converting the 3-parameter minimisation problem into an empirically unimodal univariate problem, which is quickly minimised using the golden section line search (GS). RESULTS: To enable comparison, we propose a novel noise-masking algorithm. For clinical data, the agreement between the GS and the LM fit is excellent, yet the GS algorithm is two orders of magnitude faster. For synthetic data, the accuracy of the GS algorithm is on par with that of the LM fit, and the GS algorithm is significantly faster. The GS algorithm requires no parametrisation or initialisation by the user. DISCUSSION: The new GS T2 mapping algorithm offers a fast and much more accurate off-the-shelf replacement for the inaccurate 2-parameter fit in the vendor's software.

• Klíčová slova
• Algorithms, Least-squares analysis, Software,
• MeSH
• algoritmy MeSH
• časové faktory MeSH
• fantomy radiodiagnostické MeSH
• interpretace obrazu počítačem metody   MeSH
• lidé MeSH
• magnetická rezonanční tomografie * MeSH
• metoda nejmenších čtverců MeSH
• nádory prostaty diagnostické zobrazování   MeSH
• počítačové zpracování obrazu metody   MeSH
• poměr signál - šum MeSH
• pravděpodobnost MeSH
• regresní analýza MeSH
• reprodukovatelnost výsledků MeSH
• software MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Advanced signal processing methods are one of the fastest developing scientific and technical areas of biomedical engineering with increasing usage in current clinical practice. This paper presents an extensive literature review of the methods for the digital signal processing of cardiac bioelectrical signals that are commonly applied in today's clinical practice. This work covers the definition of bioelectrical signals. It also covers to the extreme extent of classical and advanced approaches to the alleviation of noise contamination such as digital adaptive and non-adaptive filtering, signal decomposition methods based on blind source separation and wavelet transform.

• Klíčová slova
• biomedical signals, cardiac signals, electrocardiography, fetal electrocardiography, vectorcardiography,
• MeSH
• algoritmy * MeSH
• elektrokardiografie * MeSH
• lidé MeSH
• počítačové zpracování signálu MeSH
• srdce MeSH
• vlnková analýza MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH