Hybrid methods based on empirical mode decomposition for non-invasive fetal heart rate monitoring

This study focuses on fetal electrocardiogram (fECG) processing using hybrid methods that combine two or more individual methods. Combinations of independent component analysis (ICA), wavelet transform (WT), recursive least squares (RLS), and empirical mode decomposition (EMD) were used to create the individual hybrid methods. Following four hybrid methods were compared and evaluated in this study: ICA-EMD, ICA-EMD-WT, EMD-WT, and ICA-RLS-EMD. The methods were tested on two databases, the ADFECGDB database and the PhysioNet Challenge 2013 database. Extraction evaluation is based on fetal heart rate (fHR) determination. Statistical evaluation is based on determination of correct detection (ACC), sensitivity (Se), positive predictive value (PPV), and harmonic mean between Se and PPV (F1). In this study, the best results were achieved by means of the ICA-RLS-EMD hybrid method, which achieved accuracy(ACC) > 80% at 9 out of 12 recordings when tested on the ADFECGDB database, reaching an average value of ACC > 84%, Se > 87%, PPV > 92%, and F1 > 90%. When tested on the Physionet Challenge 2013 database, ACC > 80% was achieved at 12 out of 25 recordings with an average value of ACC > 64%, Se > 69%, PPV > 79%, and F1 > 72%.Web of Science8512185120

Determining the Suitable Viewing Distance for the Display with Respect to the Physiology of the Eye

Cílem této bakalářské práce je určení vhodné pozorovací vzdálenosti pro různé velikosti a rozlišení displejů vzhledem k fyziologii a optickým vlastnostem oka. V první části práce je popsána fyziologie a optická soustava oka, zahrnující popis zorného pole a nejvhodnějších úhlů pro pozorování displejů. V další části jsou popsány principy dnes nejpoužívanějších typů displejů a také jejich vlastnosti a parametry. Výpočty jsou provedeny pro tři druhy aktivit. První aktivita zahrnuje zpracování počítačové grafiky, kdy je potřeba rozlišit jednotlivé pixely. Dále jsou provedeny výpočty vzdáleností pro práci s textem. A třetí část zahrnuje výpočty pro sledování televize s cílem určit rozsah minimální a maximální vzdálenosti tak, aby oko nebylo schopno rozlišit jednotlivé pixely. Poslední část práce je věnována porovnání vypočtených hodnot s hodnotami udávanými výrobci a vytvoření programu pro výpočet vzdáleností na základě vstupních parametrů displeje.The aim of this bachelor thesis is to determine suitable viewing distance for various display sizes and resolutions with respect to the physiology and optical properties of the eye. In the first part the physiology and optical eye system are described, including a description of the visual field and the most suitable viewing angles for watching displays. In the next part the principles of today the most used displays are described and also their properties and specifications. Mathematical calculations are made for three kinds of activities. The first activity includes processing of computer graphics in case of need to distinguish individual pixels. Further are made calculations for word processing. And the third part includes calculations for watching the television with the goal of determination minimal and maximal range of distances, so that the eye would not be able to distinguish individual pixels. The last part is focused on the comparison of calculated values to the values given by the producers and creation of a program to calculate the distance based on the input parameters of the display.450 - Katedra kybernetiky a biomedicínského inženýrstvívýborn

Hybrid Methods for Fetal Electrocardiogram Extraction

Cílem této diplomové práce je neinvazivní zpracování plodového elektrokardiogramu (fEKG) pomocí hybridních metod, které kombinují dvě a více transabdominálních metod. Teoretická část práce je věnována problematice plodové elektrokardiografie, rozsáhlé rešerši již existujících hybridních metod a matematickému popisu implementovaných metod. Experimentální část je primárně zaměřena na testování a analýzu vzájemných kombinací analýzy nezávislých komponent (ICA), vlnkové transformace (WT), prahování vlnkových koeficientů (WS), empirické modální dekompozice (EMD), souboru empirické modální dekompozice (EEMD) a analýzy hlavních komponent (PCA). Hodnocení extrakce je provedeno na základě stanovení variability tepové frekvence plodu (fHRV). Použitím hybridních metod je v této práci dosaženo lepších výsledků než při samotném použití metody ICA. Výstupem práce je také implementace metod v grafickém uživatelské rozhraní v prostředí Matlab.The aim of this thesis is non-invasive processing of fetal electrocardiogram (fECG) using hybrid methods, which combine two or more transabdominal methods. The theoretical part is dedicated to the problems of fetal electrocardiography, complex overview of already existing hybrid methods and mathematical description of implemented methods. The experimental part is primarily focused on testing and analysis combinations of independent component analysis (ICA), wavelet transform (WT), wavelet shrinkage (WS), empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and principal component analysis (PCA). The evaluation of extraction quality is based on the determination of fetal heart rate variability (fHRV). The performence of hybrid methods in this thesis is better than usage of individual ICA method. The output of the thesis is also implementation of methods in the graphical user interface in Matlab.450 - Katedra kybernetiky a biomedicínského inženýrstvívýborn

A comparative study of single-channel signal processing methods in fetal phonocardiography

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.Web of Science178art. no. e026988

Nature inspired method for noninvasive fetal ECG extraction

This paper introduces a novel algorithm for effective and accurate extraction of non-invasive fetal electrocardiogram (NI-fECG). In NI-fECG based monitoring, the useful signal is measured along with other signals generated by the pregnant women's body, especially maternal electrocardiogram (mECG). These signals are more distinct in magnitude and overlap in time and frequency domains, making the fECG extraction extremely challenging. The proposed extraction method combines the Grey wolf algorithm (GWO) with sequential analysis (SA). This innovative combination, forming the GWO-SA method, optimises the parameters required to create a template that matches the mECG, which leads to an accurate elimination of the said signal from the input composite signal. The extraction system was tested on two databases consisting of real signals, namely, Labour and Pregnancy. The databases used to test the algorithms are available on a server at the generalist repositories (figshare) integrated with Matonia et al. (Sci Data 7(1):1-14, 2020). The results show that the proposed method extracts the fetal ECG signal with an outstanding efficacy. The efficacy of the results was evaluated based on accurate detection of the fQRS complexes. The parameters used to evaluate are as follows: accuracy (ACC), sensitivity (SE), positive predictive value (PPV), and F1 score. Due to the stochastic nature of the GWO algorithm, ten individual runs were performed for each record in the two databases to assure stability as well as repeatability. Using these parameters, for the Labour dataset, we achieved an average ACC of 94.60%, F1 of 96.82%, SE of 97.49%, and PPV of 98.96%. For the Pregnancy database, we achieved an average ACC of 95.66%, F1 of 97.44%, SE of 98.07%, and PPV of 97.44%. The obtained results show that the fHR related parameters were determined accurately for most of the records, outperforming the other state-of-the-art approaches. The poorer quality of certain signals have caused deviation from the estimated fHR for certain records in the databases. The proposed algorithm is compared with certain well established algorithms, and has proven to be accurate in its fECG extractions.Web of Science121art. no. 2015

A novel algorithm based on ensemble empirical mode decomposition for non-invasive fetal ECG extraction

Non-invasive fetal electrocardiography appears to be one of the most promising fetal monitoring techniques during pregnancy and delivery nowadays. This method is based on recording electrical potentials produced by the fetal heart from the surface of the maternal abdomen. Unfortunately, in addition to the useful fetal electrocardiographic signal, there are other interference signals in the abdominal recording that need to be filtered. The biggest challenge in designing filtration methods is the suppression of the maternal electrocardiographic signal. This study focuses on the extraction of fetal electrocardiographic signal from abdominal recordings using a combination of independent component analysis, recursive least squares, and ensemble empirical mode decomposition. The method was tested on two databases, the Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations and the PhysioNet Challenge 2013 database. The evaluation was performed by the assessment of the accuracy of fetal QRS complexes detection and the quality of fetal heart rate determination. The effectiveness of the method was measured by means of the statistical parameters as accuracy, sensitivity, positive predictive value, and F1-score. Using the proposed method, when testing on the Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations database, accuracy higher than 80% was achieved for 11 out of 12 recordings with an average value of accuracy 92.75% [95% confidence interval: 91.19-93.88%], sensitivity 95.09% [95% confidence interval: 93.68-96.03%], positive predictive value 96.36% [95% confidence interval: 95.05-97.17%] and F1-score 95.69% [95% confidence interval: 94.83-96.35%]. When testing on the Physionet Challenge 2013 database, accuracy higher than 80% was achieved for 17 out of 25 recordings with an average value of accuracy 78.24% [95% confidence interval: 73.44-81.85%], sensitivity 81.79% [95% confidence interval: 76.59-85.43%], positive predictive value 87.16% [95% confidence interval: 81.95-90.35%] and F1-score 84.08% [95% confidence interval: 80.75-86.64%]. Moreover, the non-invasive ST segment analysis was carried out on the records from the Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations database and achieved high accuracy in 7 from in total of 12 records (mean values mu < 0.1 and values of +/- 1.96 sigma < 0.1).Web of Science168art. no. e025615

Non-invasive fetal electrocardiogram extraction based on novel hybrid method for intrapartum ST segment analysis

This study focuses on non-invasive fetal electrocardiogram extraction based on a novel hybrid method, which combines the advantages of non-adaptive and adaptive approaches for non-invasive fetal electrocardiogram morphological analysis. Besides estimating fetal heart rate, which is the main parameter used in the clinical practice, this study provides non-invasive ST segment analysis on data from Abdominal and Direct Fetal Electrocardiogram Database consisting of simultaneous traditional - gold standard invasive fetal scalp electrode and non-invasive fetal electrocardiogram recorded during delivery. This innovative approach utilizing the combination of independent component analysis and recursive least squares algorithms has the potential to extract valuable information from non-invasive fetal electrocardiogram in order to identify eventual sign of fetal distress. This was a prospective observational study of non-invasive fetal electrocardiogram, using 4 abdominally sited electrodes, against the traditional fetal scalp electrode on 8 patients. In terms of fetal heart rate estimation, the accuracy was high for all 8 tested patients with average value equaled 0.20 beats per minute and average value of 1.96 standard deviation equaled 5.80 beats per minute. In 7 patients, it was possible to perform the ST segment analysis with high accuracy in determining T/QRS in comparison with the reference fetal scalp electrode signal with average values and 1.96 standard deviation equaled 0.008 and 0.031 respectively. This study thus demonstrates that ST segment analysis is feasible using non-invasive fECG using the proposed hybrid method.Web of Science9286312860

14. mezinárodní vědecká konference Didaktická konference 2021

Title in English: 14th International Scientific Conference Didactic Conference 2021: Proceedings Didactics of mathematics, natural sciences and vocational education represent developing areas and are a breeding ground for new ideas and approaches. In mathematics and physics, the proceedings provide an overview of the historical development of education process and the possibilities of activating students. From a practical point of view, physics and chemistry are interconnected by using simulations in teaching. Vocational education is represented from various perspectives, whether in technical education, by solving logistical problems, or educational activities in the teaching of economic subjects. Due to the current situation, there are abundant contributions on the effects of the ongoing pandemic on the educational process and distance learning

System for adaptive extraction of non-invasive fetal electrocardiogram

This study aimed to find the most suitable combination of adaptive and non-adaptive methods for extraction of non-invasive fetal electrocardiogram (NI-fECG) using signals recorded from the mother's abdomen. Among the nine methods considered, the combination of independent component analysis (ICA), fast transversal filter (FTF), and complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) proved to be the most effective for the extraction of fECG from abdominal recordings. This combined method was suitable due to both being effective in extracting fECG and being less computationally complex. Further, so far, FTF and CEEMDAN methods have not been extensively tested for fECG extraction, and in particular, have not been examined as a hybrid method. The ICA-FTF-CEEMDAN hybrid algorithm was tested on two patient databases: Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations (FECGDARHA) and PhysioNet Challenge 2013. The evaluation of the accuracy of fQRS complexes detection was performed using the following parameters: accuracy (ACC), sensitivity (SE), positive predictive value (PPV), and F1 score. The fetal heart rate (fHR) determination accuracy was evaluated using Bland-Altman plots and fHR traces. When testing on the FECGDARHA database, average values of ACC = 92.98%, SE = 95.33%, PPV = 96.4% and F1 = 95.86% for detection fQRS were achieved. The error in estimating the fHR was -1.02 +/- 7.02 (mu +/- 1.96 sigma) bpm. When testing on the Challenge 2013 database, average values of ACC = 78.47%, SE = 82.06%, PPV = 87.90% and F1 = 84.62% for fQRS detection were achieved, and the error in estimating the fHR was -6.62 +/- 10.33 (mu +/- 1.96 sigma) bpm. In addition, a non-invasive morphological analysis (ST analysis) was performed on the records from the FECGDARHA database, which was accurate in 7 of 12 records with values of mu < 0.03 and values of +/- 1.96 sigma < 0.04.Web of Science113art. no. 10794

Alternative measurement systems for recording cardiac activity in animals: a pilot study

Monitoring and assessing cardiac activity in animals, especially heart rate variability, has been gaining importance in the last few years as an indicator of animal health, well-being and physical condition. This pilot study tested the sensors based on ballistocardiography sensing the mechanical vibrations caused by the animal's cardiovascular system, which have proved useful in measuring cardiac activity in humans. To verify the accuracy of these measurement systems, the conventional measurements based on electrocardiography were carried out and the outcomes were compared. The main objectives were to verify the suitability of these sensors in measuring cardiac activity in animals, to determine the advantages and disadvantages of these sensors, and to identify future challenges. Measurements were performed on various animals, specifically a goat, a cow, a horse, and a sheep. Electrocardiographic measurement, which has demonstrated high accuracy in procedures for animals, was used as the study's gold standard. A disadvantage of this method, however, is the long time required to prepare animals and shear spots to attach electrodes. The accuracy of a ballistocardiographic sensor was compared to reference electrocardiographic signals based on Bland-Altman plots which analysed the current heart rate values. Unfortunately, the ballistocardiographic sensor was highly prone to poor adhesion to the animal's body, sensor movement when the animal was restless, and motion artefacts. Ballistocardiographic sensors were shown only to be effective with larger animals, i.e., the horse and the cow, the size of these animals allowing sufficient contact of the sensor with the animal's body. However, this method's most significant advantage over the conventional method based on electrocardiography is lower preparation time, since there is no need for precise and time-demanding fixation of the sensor itself and the necessity of shaving the animal's body.Web of Science101art. no. 1