Autor: Jeżewski, R. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Fuzzy system for evaluation of fetal heart rate signals using FIGO criteria
Autorzy:: Czabański, R.
Jeżewski, M.
Wróbel, J.
Jeżewski, J.
Horoba, K.
Powiązania:: https://bibliotekanauki.pl/articles/333142.pdf
Data publikacji:: 2009
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: monitoring płodu
tętno płodu
kryteria FIGO
fetal monitoring
fetal heart rate
signal classification
fuzzy systems
Opis:: Cardiotocography is a biophysical method of fetal monitoring during pregnancy and labour. It is mainly based on recording and analysis of fetal heart activity. The computerized fetal monitoring systems provide the quantitative description of the recorded signals but the effective methods supporting the conclusion generation are still needed. The evaluation of the signal can be made using criteria recommended by FIGO. Nevertheless, the quantitative description of the traces is inconsistent with qualitative nature of the obstetric knowledge. Therefore, we applied the fuzzy system based on Takagi-Sugeno-Kang model to evaluate and classify signals. FIGO guidelines were used for developing a set of fuzzy conditional rules defining the system performance. The proposed system was evaluated using data collected with computerized fetal surveillance system – MONAKO. The classification results confirm the improvement of the fetal state evaluation quality while using the proposed fuzzy system support.
Źródło:: Journal of Medical Informatics & Technologies; 2009, 13; 189-194
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Fuzzy prediction of fetal acidemia
Autorzy:: Czabański, R.
Roj, D.
Jeżewski, J.
Horoba, K.
Jeżewski, M.
Powiązania:: https://bibliotekanauki.pl/articles/333483.pdf
Data publikacji:: 2011
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: monitorowanie płodu
tętno płodu
klasyfikacja sygnału
systemy rozmyte
fetal monitoring
fetal heart rate
signal classification
fuzzy systems
Opis:: Cardiotocography is the primary method for biophysical assessment of a fetal state. It is based mainly on the recording and analysis of fetal heart rate signal (FHR). Computer systems for fetal monitoring provide a quantitative description of FHR signals, however the effective methods for their qualitative assessment are still needed. The measurements of hydronium ions concentration (pH) in newborn cord blood is considered as the objective indicator of the fetal state. Improper pH level is a symptom of acidemia being the result of fetal hypoxia. The paper proposes a twostep analysis of signals allowing for effective prediction of the acidemia risk. The first step consists in the fuzzy classification of FHR signals. The task of fuzzy inference is to indicate signals that according to the FIGO guidelines represent the fetal wellbeing. These recordings are eliminated from the further classification with Lagrangian Support Vector Machines. The proposed procedure was evaluated using data collected with computerized fetal surveillance system. The classification results confirmed the high quality of the proposed fuzzy method of fetal state evaluation.
Źródło:: Journal of Medical Informatics & Technologies; 2011, 17; 81-87
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Improving the efficacy of automated fetal state assessment with fuzzy analysis of delivery outcome
Autorzy:: Czabanski, R.
Jezewski, M.
Horoba, K.
Jezewski, J.
Leski, J.
Powiązania:: https://bibliotekanauki.pl/articles/333655.pdf
Data publikacji:: 2015
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: fetal monitoring
fuzzy inference
support vector machines
supervised learning
monitorowanie płodu
wnioskowanie rozmyte
maszyna wektorów nośnych
uczenie nadzorowane
Opis:: A number of methods of the qualitative assessment of fetal heart rate (FHR) signals are based on supervised learning. The classification methods based on the supervised learning require a set of training recordings accompanied by the reference interpretation. In the real data collections the class of signals related to fetal distress is usually under-represented. Too small percentage of distress patterns adversely affects the effectiveness of the automated evaluation of the fetal state. The paper presents a method of equalizing the class sizes based on the reference assessment of the fetal state with the fuzzy analysis of the newborn attributes. The supervised learning with increased number of the FHR signals, which are characterized by the highest rate of the fuzzy inference leads to significant increase of the efficacy of the qualitative assessment of the fetal state using the Lagrangian support vector machine.
Źródło:: Journal of Medical Informatics & Technologies; 2015, 24; 223-230
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Fetal state evaluation with fuzzy analysis of newborn attributes using CUDA architecture
Autorzy:: Czabański, R.
Wróbel, J.
Jeżewski, J.
Powiązania:: https://bibliotekanauki.pl/articles/333255.pdf
Data publikacji:: 2013
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: fuzzy systems
fetal monitoring
support vector machines
CUDA architecture
systemy rozmyte
monitorowanie płodu
architektura CUDA
Opis:: Cardiotocography is a biophysical method of fetal state evaluation involving the recording and analysis of the fetal heart rate (FHR). Since a proper interpretation of the signal is relatively difficult, an automatic classification is often based on computational intelligence methods. The quality of classifiers based on supervised learning algorithms depends on a proper selection of learning data. In case of the fetal state evaluation, the learning is usually based on a set of quantitative parameters of FHR signal and the corresponding reference information determined on the basis of the retrospective analysis of newborn attributes. Values of the single attribute have been used so far as a reference. As a result, a part of information on the actual neonatal outcome has always been lost. The following paper presents a method of the fuzzy reasoning leading to an evaluation of neonatal outcome as a function of three newborn attributes. The fuzzy system was used in the process of a qualitative evaluation of the fetal state based on quantitative analysis of FHR signal using a support vector machine (SVM). In order to improve computational effectiveness, the learning algorithm was implemented in Compute Unified Device Architecture (CUDA). The results of these studies confirm the effectiveness of the proposed method and indicate the possibility of practical usage of the fuzzy system in supervised learning algorithms for the qualitative evaluation of the fetal state.
Źródło:: Journal of Medical Informatics & Technologies; 2013, 22; 125-133
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: The influence of cardiotocogram signal feature selection method on fetal state assessment efficacy
Autorzy:: Jeżewski, M.
Czabański, R.
Łęski, J.
Powiązania:: https://bibliotekanauki.pl/articles/333440.pdf
Data publikacji:: 2014
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: cardiotocography
classification
feature selection
kardiotokografia
klasyfikacja
selekcja cech
Opis:: Cardiotocographic (CTG) monitoring is a method of assessing fetal state. Since visual analysis of CTG signal is difficult, methods of automated qualitative fetal state evaluation on the basis of the quantitative description of the signal are applied. The appropriate selection of learning data influences the quality of the fetal state assessment with computational intelligence methods. In the presented work we examined three different feature selection procedures based on: principal components analysis, receiver operating characteristics and guidelines of International Federation of Gynecology and Obstetrics. To investigate their influence on the fetal state assessment quality the benchmark SisPorto® dataset and the Lagrangian support vector machine were used.
Źródło:: Journal of Medical Informatics & Technologies; 2014, 23; 51-58
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: The prediction of the low fetal birth weight based on quantitative description of cardiotocographic signals
Autorzy:: Czabański, R.
Jeżewski, M.
Wróbel, J.
Kupka, T.
Łęski, J.
Jeżewski, J.
Powiązania:: https://bibliotekanauki.pl/articles/333495.pdf
Data publikacji:: 2008
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: weryfikacja podpisu online
programowanie dynamiczne
online signature verification
feature context
dynamic programming
Opis:: Cardiotocography (CTG) is a routine method of fetal condition assessment used in modern obstetrics. It is a biophysical method based on simultaneous recording and analysis of activity of fetal heart, fetal movements and maternal uterine contractions. The fetal condition is diagnosed on the basis of printed CTG trace evaluation. The correct interpretation of CTG traces from a bedside monitor is very difficult even for experienced clinicians. Therefore, computerized fetal monitoring systems are used to yield the quantitative description of the signal. However, the effective methods, aiming to support the conclusion generation, are still being searched. One of the most important features defining the state of fetal outcome is the weight of the newborn. The presented work describes an application of the Artificial Neural Network Based on Logical Interpretation of fuzzy if-then Rules (ANBLIR) to evaluate the risk of the low birth weight using a set of parameters quantitatively describing the CTG traces. The obtained results confirm that the neuro-fuzzy based CTG classification methods are very efficient for the prediction of the fetal outcome.
Źródło:: Journal of Medical Informatics & Technologies; 2008, 12; 97-102
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Influence of gestational age on neural networks interpretation of fetal monitoring signals
Autorzy:: Jeżewski, M.
Czabański, R.
Horoba, K.
Wróbel, J.
Łęski, J.
Jeżewski, J.
Powiązania:: https://bibliotekanauki.pl/articles/333505.pdf
Data publikacji:: 2008
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: monitoring płodu
kardiotokografia
klasyfikacja
sieci neuronowe
fetal monitoring
cardiotocography
classification
neural networks (NN)
Opis:: Cardiotocographic monitoring (CTG) is a primary biophysical monitoring method for assessment of the fetal state and is based on analysis of fetal heart rate, uterine contraction activity and fetal movement signals. Visual analysis of CTG traces is very difficult so computer-aided fetal monitoring systems have become a standard in clinical centres. We proposed the application of neural networks for the prediction of fetal outcome using the parameters of quantitative description of acquired signals as inputs. We focused on the influence of the gestational age (during trace recording) on the fetal outcome classification quality. We designed MLP and RBF neural networks with changing the number of neurons in the hidden layer to find the best structure. Networks were trained and tested fifty times, with random cases assignment to training, validating and testing subset. We obtained the value of sensitivity index above 0.7, what may be regarded as good result. However additional trace grouping within similar gestational age, increased classification quality in the case of MLP networks.
Źródło:: Journal of Medical Informatics & Technologies; 2008, 12; 137-142
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: Analysis of electrical uterine contractile activity for prediction of preterm delivery
Autorzy:: Horoba, K.
Jezewski, J.
Matonia, A.
Wrobel, J.
Czabanski, R.
Jezewski, M.
Powiązania:: https://bibliotekanauki.pl/articles/333763.pdf
Data publikacji:: 2015
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: electrical uterine activity
electrohysterography
preterm delivery prediction
aktywność elektryczna macicy
elektrohisterografia
przewidywanie porodu przedwczesnego
Opis:: This study is aimed at evaluation of the capability to indicate the preterm delivery risk analysing the features extracted from signals of electrical uterine activity. Free access database was used with signals acquired in two groups of pregnant women who delivered at term and preterm. Signal features comprised classical time domain and spectral parameters of contractile activity, as well as the sample entropy. Their mean values were calculated over all contraction episodes detected in each record and their statistical significance for separating the two groups of recordings was provided. Influence of electrodes location, band-pass filter settings and gestation week was investigated. The obtained results showed that a spectral parameter – the median frequency was the most promising indicator of the preterm delivery risk.
Źródło:: Journal of Medical Informatics & Technologies; 2015, 24; 199-205
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: A new approach for the clustering using pairs of prototypes
Autorzy:: Jezewski, M.
Czabanski, R.
Leski, J.
Horoba, K.
Powiązania:: https://bibliotekanauki.pl/articles/333693.pdf
Data publikacji:: 2015
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: fuzzy clustering
pairs of prototypes
fuzzy rule-based classification
grupowanie rozmyte
pary prototypów
rozmyta klasyfikacja oparta na regułach
Opis:: In the presented work two variants of the fuzzy clustering approach dedicated for determining the antecedents of the rules of the fuzzy rule-based classifier were presented. The main idea consists in adding additional prototypes (’prototypes in between’) to the ones previously obtained using the fuzzy c-means method (ordinary prototypes). The ’prototypes in between’ are determined using pairs of the ordinary prototypes, and the algorithm based on distances and densities finding such pairs was proposed. The classification accuracy obtained applying the presented clustering approaches was verified using six benchmark datasets and compared with two reference methods.
Źródło:: Journal of Medical Informatics & Technologies; 2015, 24; 113-121
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Efficiency of automated detection of uterine contraction using tocography
Autorzy:: Horoba, K.
Wrobel, J.
Jezewski, J.
Kupka, T.
Czabanski, R.
Roj, D.
Jezewski, M.
Powiązania:: https://bibliotekanauki.pl/articles/334025.pdf
Data publikacji:: 2015
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: uterine contractile activity
tocography
automated contraction detection
aktywność skurczowa macicy
tokografia
automatyczne wykrywanie skurczu
Opis:: Monitoring of uterine contractile activity enables to control the progress of labour. Automated detection of contractions is to be an integral part of the signal analysis implemented in computer aided fetal surveillance system. Evaluation of efficiency of three algorithms for automated detection of uterine contractions in the signal of uterine mechanical activity is presented. These algorithms are based generally on analysis of the frequency distribution of signal values. The reference data in form of beginning and end of contraction episodes were obtained from human expert. Obtained results showed high efficiency of the algorithms tested where the best one ensured the sensitivity and positive predictive value equal to 92.2 and 97.2, respectively.
Źródło:: Journal of Medical Informatics & Technologies; 2015, 24; 207-214
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 11.

Tytuł:: Improving the quality of the fetal state assessment with epsilon-insensitive learning methods
Autorzy:: Czabański, R.
Wróbel, J.
Jeżewski, J.
Łęski, J.
Powiązania:: https://bibliotekanauki.pl/articles/333468.pdf
Data publikacji:: 2014
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: fetal monitoring
fuzzy implication
epsilon-insensitive learning
monitorowanie płodu
implikacja rozmyta
Opis:: Recording and analysis of fetal heart rate (FHR) signal is nowadays the primary method for the biophysical assessment of the fetal state. Since the correct interpretation of crucial FHR characteristics is difficult, methods of automated quantitative signal evaluation are still the subject of the research studies. In the following paper we investigated the possibility of improvement of the fetal state evaluation on the basis of the epsilon-insensitive learning (eIL). We examined two eIL procedures integrated with fuzzy clustering algorithms as well as different methods of logical interpretation of the fuzzy conditional statements. The quality of the FHR signal classification was evaluated using the data collected with the computerized fetal surveillance system. The learning performance was measured with the number of correct classification (CC) and overall quality index (QI) defined as a geometric mean of sensitivity and specificity. The obtained results (CC = 88 % and QI = 87 %) show a high efficiency of the fetal state assessment using the epsilon-insensitive learning based methods.
Źródło:: Journal of Medical Informatics & Technologies; 2014, 23; 19-26
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 12.

Tytuł:: Evaluation of predictive capabilities of quantitative cardiotocographic signal features
Autorzy:: Czabański, R.
Jeżewski, M.
Roj, D.
Szaszkowski, Z.
Kupka, T.
Wróbel, J.
Powiązania:: https://bibliotekanauki.pl/articles/332937.pdf
Data publikacji:: 2010
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: monitorowanie płodu
tętno płodu
klasyfikacja sygnału
fetal monitoring
fetal heart rate
signal classification
ROC analysis
Opis:: Cardiotocography (CTG) is the main method of assessment of the fetal state during pregnancy and labour used in clinical practice. It is based on quantitative analysis of fetal heart rate, fetal movements and uterine contractions signals. The evaluation of the CTG signals can be made using criteria recommended by International Federation of Obstetrics and Gynecology. Nevertheless, the diagnosis verification is possible only after the delivery on the basis of newborn assessment. In the proposed work we evaluated the capacity of quantitative analysis of CTG traces in predicting fetal outcome. The relationship between CTG signal features and attributes of fetal outcome was assessed on the basis of ROC curves analysis. The obtained results indicate the adequate predictive capabilities of the selected CTG features especially for fetal outcome assessed with Apgar score and suggest the necessity of applying the criteria for the CTG traces evaluation that are related to the gestational age. Our study also shows the value of the CTG monitoring as a screening procedure providing appropriate confirmation of fetal wellbeing.
Źródło:: Journal of Medical Informatics & Technologies; 2010, 16; 11-17
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 13.

Tytuł:: A routing protocol for wireless network of bedside monitors in fetal surveillance system
Autorzy:: Seredynski, R.
Horoba, K.
Roj, D.
Bernys, M.
Przybyla, T.
Jezewski, J.
Powiązania:: https://bibliotekanauki.pl/articles/333626.pdf
Data publikacji:: 2012
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: monitorowanie płodu
tętno płodu
sieci bezprzewodowe
protokoły rutowania
symulacja
fetal monitoring
fetal heart rate
wireless networks
routing protocol
simulation
Opis:: The paper presents the methodology of wireless network design, developed according to the requirements originating from existing wired fetal surveillance systems. The proposed network structure is based on popular radio frequency modules, operating in 433/866MHz band. The described solution is a simple and cost effective alternative to the wired networks, and it will vastly increase the mobility of fetal monitors. The authors also describe software tools which were designed for this purpose and the results of simulations performed on their basis.
Źródło:: Journal of Medical Informatics & Technologies; 2012, 21; 27-33
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 14.

Tytuł:: Detection of human fall episodes based on coordinates of body tags and numerical differentiation
Autorzy:: Momot, M.
Momot, A.
Nowak, G.
Seredynski, R.
Jezewski, J.
Kupka, T.
Powiązania:: https://bibliotekanauki.pl/articles/333630.pdf
Data publikacji:: 2012
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: otoczenie
wspieranie życia
dane nieregularne objęte próbą
zróżniczkowanie numeryczne
ambient
assisted living
fall detection
irregular sampled data
numerical differentiation
Opis:: This paper presents a new method for detection of changes in alignment of the human body, particularly the fall, on the basis of signals acquired from the position sensors placed on the body of the monitored person. The sensors are located on the cuffs, waist and chest. Transformation of data sequence collected from sensors is proposed in order to best distinguish between the collapse from the normal movement. It is based on nonlinear combination of the first two derivatives of the signals being read. Because data from the sensors is sent asynchronously, a numerical algorithm for unevenly sampled data differentiation is proposed. Derivative values are calculated in equidistant nodes through differentiation of a polynomial, which is adjusted by minimizing the mean square error. The developed method can be used in home care telemedicine systems, where it is necessary to long term monitor of multiple vital parameters of people under care.
Źródło:: Journal of Medical Informatics & Technologies; 2012, 21; 11-17
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 15.

Tytuł:: Reconstruction of FHR series recorded via ultrasound - method validation using abdominal fetal electrocardiography
Autorzy:: Kupka, T.
Horoba, K.
Roj, D.
Matonia, A.
Czabanski, R.
Jezewski, M.
Powiązania:: https://bibliotekanauki.pl/articles/333726.pdf
Data publikacji:: 2013
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: fetal heart rate variability
time event series
sampled signal
duplicated sample
zmienność rytmu serca płodu
sygnał próbny
powielona próbka
Opis:: Analysis of variability of the fetal heart rate (FHR) is very important for fetal wellbeing assessment. The beat-to-beat variability is described quantitatively by the indices originated from invasive fetal electrocardiography which provides the FHR signal in a form of time event series. Nowadays, monitoring instrumentation is based on Doppler ultrasound technology. The fetal monitors provide the output signal in a form of evenly spaced measurements. The goal of this work is to present a new method for the FHR signal processing, which enables extraction of time series of consecutive heartbeat intervals from the evenly repeated values. The proposed correction algorithm enables recognition and removal of the duplicated measurements. Reliable evaluation of the algorithm requires the reference event series, thus the FHR signals were obtained from abdominal fetal electrocardiograms to be used in this research study.
Źródło:: Journal of Medical Informatics & Technologies; 2013, 22; 135-141
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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