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:: 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: 4.

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: 5.

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: 6.

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: 7.

Tytuł:: Projective filtering based on L1-norm PC
Autorzy:: Przybyła, T.
Wróbel, J.
Pander, T.
Czabański, R.
Jeżewski, J.
Matonia, A.
Powiązania:: https://bibliotekanauki.pl/articles/332906.pdf
Data publikacji:: 2013
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: embedded space
projective filtering
nonlinear noise reduction
PCA
L1-norm PCA
przestrzeń osadzona
filtrowanie rzutowe
nieliniowa redukcja szumów
norma L1 PCA
Opis:: The paper presents a modification of nonlinear state-space projections (NSSP) method. The proposed approach deals with the sub-space estimation problem. In the original NSSP method, the principal component analysis (PCA) is used for the subspace determination. The classical PCA uses L2-norm. It is well known that the L2-norm is sensitive to outliers. Thus, in this paper the L1-norm PCA is proposed a subspace determination. In numerical experiments an analytic signal and real ECG signals are processed with the proposed method. The signals are contaminated with Gaussian distributed noise with different signal to noise ratio (SNR). Obtained results confirm the usefulness of the proposed modification.
Źródło:: Journal of Medical Informatics & Technologies; 2013, 22; 79-86
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: Data stream processing in fetal monitoring system: I. algebra and query language
Autorzy:: Widera, M.
Jeżewski, J.
Winiarczyk, R.
Wróbel, J.
Horoba, K.
Gacek, A.
Powiązania:: https://bibliotekanauki.pl/articles/333189.pdf
Data publikacji:: 2003
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: język zapytań
przetwarzanie strumienia danych
system zarządzania bazami danych
monitorowanie płodu
query language
data stream processing
database management system
fetal monitoring
Opis:: The paper presents the algebra and declarative query language developed for fetal monitoring system MONAKO. At present, the system architecture is centralised. Recording, analyzing and visualization of data are carrying out in the central unit. Therefore, the system cannot scale in a simple manner. Presented solution enables to define query based on data streams that makes the updated answers currently available. Applying database management system that carries out its tasks based on presented assumptions enables the construction of monitoring system of distributed architecture
Źródło:: Journal of Medical Informatics & Technologies; 2003, 5; MI83-90
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Data stream processing in fetal monitoring system: II. Application to signal processing
Autorzy:: Jeżewski, J.
Widera, M.
Winiarczyk, R.
Matonia, A.
Kupka, T.
Gacek, A.
Powiązania:: https://bibliotekanauki.pl/articles/334015.pdf
Data publikacji:: 2003
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: język zapytań
przetwarzanie strumienia danych
system zarządzania bazami danych
monitorowanie płodu
query language
data stream processing
database management system
fetal monitoring
Opis:: Fetal monitoring system belongs to signal processing system class. The main functions of the system are signal acquisition from bedside monitors, on-line trace analysis and dynamic presentation of incoming data. Collected data set is controlled by centralised application. Relational database management system cannot process samples of high frequency biomedical signals on-line. Therefore, we decide to build our own data management system dedicated to stream processing that support continuous query. This paper describes a method of building a query plan based on proposed algebra. The presented example of application enables implementation of algorithm determining long- and short-term indices for fetal heart rate variability assessment on the basis of declarative query language. Our solution enables to define query based on data streams that make the updated answers currently available.
Źródło:: Journal of Medical Informatics & Technologies; 2003, 6; IT35-42
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Design challenges for home telemonitoring of pregnancy as a medical cyber-physical system
Autorzy:: Horoba, K.
Jeżewski, J.
Wróbel, J.
Pawlak, A.
Czabański, R.
Porwik, P.
Penkala, P.
Powiązania:: https://bibliotekanauki.pl/articles/333007.pdf
Data publikacji:: 2014
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: pregnancy monitoring
telemonitoring at home
Medical Cyber Physical Systems
monitorowanie ciąży
telemonitoring w domu
systemy medyczne
Opis:: The paper introduces the problem of designing a telemedical system for pregnancy monitoring at home. It focuses on design challenges concerning embedded computing and networking, requirements modelling, and presents the architecture and solutions when based on new class Medical Cyber-Physical Systems (MCPS). The proposed system consists of a Body Area Network (BAN) of advanced sensors that are interconnected on a body of a pregnant woman, a Personal Area Network (PAN) that is responsible for embedded processing of physical signals, smart alarms, data transmission and communication with the Surveillance Centre located in hospital. It is expected that this dependable telemedical system will provide a high societal value to women with high-risk pregnancy.
Źródło:: Journal of Medical Informatics & Technologies; 2014, 23; 59-66
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 11.

Tytuł:: Smart selection of signal analysis algorithms for telecare of high-risk pregnancy
Autorzy:: Wróbel, J.
Matonia, A.
Horoba, K.
Jeżewski, J.
Czabański, R.
Pawlak, A.
Porwik, P.
Powiązania:: https://bibliotekanauki.pl/articles/333593.pdf
Data publikacji:: 2014
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: fetal monitoring
abdominal fetal electrocardiogram
smart signal processing
telemedicine
monitorowanie płodu
brzuszne EKG płodu
inteligentne przetwarzanie sygnałów
telemedycyna
Opis:: Telemedical system for fetal home monitoring with smart selection of signal analysis algorithms is presented in this paper. Fetal monitoring signals are provided by a mobile instrumentation consisting of bioelectrical signal recorder and tablet PC which retrieves and processes the data as well as provides wireless data transmission based on Internet. The fetal surveillance system enables analysis, dynamic presentation and archiving of acquired signals and medical data. Novelty of the proposed approach relies on smart fitting of the algorithms for analysis of the abdominal signals in mobile instrumentation, as well as on controlling of the fetal monitoring session from the surveillance center. These actions are performed automatically through continuous analyzing of the signal quality and the reliability of the quantitative parameters determined for the acquired signals. Using that approach the amount and content of data transmitted through remote channels to the surveillance center can be controlled to ensure the most reliable assessment of the fetal well-being.
Źródło:: Journal of Medical Informatics & Technologies; 2014, 23; 27-33
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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