Wyniki wyszukiwania - BazTech

1

The influence of signal loss episodes on fetal heart rate variability measures

Wróbel J., Roj D., Jeżewski J., Horoba K., Kupka T., Jeżewski M.

Journal of Medical Informatics & Technologies

|

2014

|

Vol. 23

35--42

EN

The most important features indicating appropriate fetal development are the measures of instantaneous variability of a fetal heart rate (FHR), describing fluctuations of the beat-to-beat heart intervals. The most popular method for the FHR acquisition is the Doppler ultrasound technique. However, it is very sensitive to various motion artifacts distorting the signal being acquired. The aim of our work was to evaluate the influence of signal loss episodes on the parameters quantitatively describing the instantaneous variability of the FHR. For this purpose we artificially inserted signal loss episodes to the recordings, in different patterns and percentage, in accordance with the real characteristics of the signal loss segments. We particularly would like to answer the question if the signals with significant amount of signal loss can be reliably evaluated by means of instantaneous variability measures, and which of these measures (numerical indices) are more robust to the missing values.

2

The influence of cardiotocogram signal feature selection method on fetal state assessment efficacy

Jeżewski M., Czabański R., Łęski J.

Journal of Medical Informatics & Technologies

|

2014

|

Vol. 23

51--58

EN

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.

3

Fetal state assessment using fuzzy analysis of fetal heart rate signals - Agreement with the neonatal outcome

Czabański R., Jeżewski J., Horoba K., Jeżewski M.

Biocybernetics and Biomedical Engineering

|

2013

|

Vol. 33, no. 3

145--155

EN

Fetal monitoring is based on analysis of fetal heart rate signal. Visual interpretation is difficult so computer-aided systems for quantitative analysis are commonly used. The clinical interpretation guidelines provided by FIGO (Fédération Internationale de Gynécologie et d'Obstétrique) were used to develop the weighted fuzzy scoring system for qualitative assessment of the fetal state. In this work, agreement of the fuzzy classification system with the neonatal outcome assessment was analyzed. Various datasets were evaluated, depending on interpretation method of the signals which were recorded from patients. The obtained results confirmed possibility of the efficient fetal state assessment using the fuzzy inference method proposed.

4

Filtering of two-dimensional digital images using weighted averaging for adaptive selection of weights

Momot A., Wrobel J., Horoba K., Jeżewski M., Bernys M.

Journal of Medical Informatics & Technologies

|

2012

|

Vol. 20

93--99

EN

Many digital images, especially in biomedical fields, contain some disturbances. The image analysis depends on quality of the images that is why reduction or elimination (if it is possible) the disturbances is the key issue. There are many methods of improvement in the quality of the images and thus improve the quality of the image analysis, among them one of the simplest method is low-pass filtering such as arithmetic mean or its generalization, weighted mean. The basic problem of the weighted mean is the proper selection of the weights. This can be done using adaptive algorithms. This paper presents several such algorithms which are modifications of the existing weighted averaging methods created originally for noise reduction in electrocardiographic signal. The description of the new filtering methods and a few results of its application are also presented with comparison to existing arithmetic average filtering.

5

Comparison of instantaneous fetal heart rate extracted from abdominal and direct fetal electrocardiograms

Matonia A., Kupka T., Jezewski J., Momot A., Jeżewski M., Bernys M.

Journal of Medical Informatics & Technologies

|

2012

|

Vol. 19

101--107

EN

This work is an attempt to assess the reliability of indirect abdominal electrocardiography as an alternative technique of fetal monitoring. As a reference signal we used the simultaneously acquired direct fetal electrocardiogram. Each recording consisted of four signals acquired from maternal abdomen and the reference signal acquired directly from fetal head. The first stage of our study concerned the signal loss episodes. In order to reduce the influence of incorrectly detected R-waves, some certain validation rules were applied. In the second stage, the corresponding intervals determined on basis of both acquisition methods were matched and the accuracy of fetal heart rate measurement was evaluated. Although the accuracy of abdominal electrocardiography turned out to be slightly lower than reported for ultrasound method, it still has some unique features deciding of its prevalence in a certain circumstances.

6

Clustering algorithm for classification methods

Łęski J., Jeżewski M.

Journal of Medical Informatics & Technologies

|

2012

|

Vol. 20

11--18

EN

Classification plays an important role in many fields of life, including medical diagnosis support. In the paper, fuzzy clustering algorithm dedicated to classification methods is proposed. Its goal is to find pairs of prototypes located near boundaries of both classes of objects. The minimization procedure of the proposed criterion function is described. The algorithm for determining the value of the clustering parameter is also presented. Presented results (synthetic dataset) confirm correctness of clustering - most of final prototypes, determined based on obtained pairs, are located between boundary of two classes.

7

Fuzzy prediction of fetal acidemia

Czabański R., Roj D., Jeżewski J., Horoba K., Jeżewski M.

Journal of Medical Informatics & Technologies

|

2011

|

Vol. 17

81--87

EN

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.

8

Application of modified fuzzy clustering to medical data classification

Jeżewski M.

Journal of Medical Informatics & Technologies

|

2011

|

Vol. 17

51--57

EN

Classification plays very important role in medical diagnosis. This paper presents fuzzy clustering method dedicated to classification algorithms. It focuses on two additional sub-methods modifying obtained clustering prototypes and leading to final prototypes, which are used for creating the classifier fuzzy if-then rules. The main goal of that work was to examine a performance of the classifier which uses such rules. Commonly used including medical benchmark databases were applied. In order to validate the results, each database was represented by 100 pairs of learning and testing subsets. The obtained classification quality was better in relation to the one of the best classifiers - Lagrangian SVM and suggests that presented clustering with additional sub-methods are appropriate to application to classification algorithms.

9

Evaluation of predictive capabilities of quantitative cardiotocographic signal features

Czabański R., Jeżewski M., Roj D., Szaszkowski Z., Kupka T., Wróbel J.

Journal of Medical Informatics & Technologies

|

2010

|

Vol. 16

11--17

EN

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.

10

Analysis of extracted cardiotocographic signal features to improve automated prediction of fetal outcome

Jeżewski M., Czabański R., Wróbel J., Horoba K.

Biocybernetics and Biomedical Engineering

|

2010

|

Vol. 30, no. 4

29-47

EN

Cardiotocographic monitoring based on automated analysis of the fetal heart rate (FHR) signal is widely used for fetal assessment. However, the conclusion generation system is still needed to improve the abnormal fetal outcome prediction. Classification of the signals according to the predicted fetal outcome by means of neural networks is presented in this paper. Multi-layer perceptron neural networks were learned through seventeen time-domain signal features extracted during computerized analysis of 749 traces from 103 patients. The analysis included estimation of the FHR baseline, detection of acceleration and deceleration patterns as well as measurement of the instantaneous FHR variability. All the traces were retrospectively verified by the real fetal outcome defined by newborn delivery data. Influence of numerical and categorical representation of the input signal features, different data sets during learning, and gestational age as additional information, were investigated. We achieved the best sensitivity and specificity for the neural networks fed with numerical input variables together with additional information on the gestational age in the categorical form.

11

Fuzzy system for evaluation of fetal heart rate signals using FIGO criteria

Czabański R., Jeżewski M., Wróbel J., Jeżewski J., Horoba K.

Journal of Medical Informatics & Technologies

|

2009

|

Vol. 13

189--194

EN

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.

12

Lightweight ceramsite concrete used as an additional protection of fuel oil tanks on ships

Jeżewski M., Krasowski C.

Polish Maritime Research

|

2008

|

S 1

14-17

EN

Introduction of the semi-elastic barrier into ship fuel tanks requires of use of core material which will play role of carrier for elastic, fuel resistant layer. Such core material should be ligth, non reactive with water and fuel, fire resistant, corrosion neutral and finally easy applicable and relatively cheap. In paper the different problems like components, preparation, application as well as surface treatment for using of the light concrete as core material are presented.

13

The prediction of the low fetal birth weight based on quantitative description of cardiotocographic signals

Czabański R., Jeżewski M., Wróbel J., Kupka T., Łęski J., Jeżewski J.

Journal of Medical Informatics & Technologies

|

2008

|

Vol. 12

97--102

EN

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.

14

The influence of window size of autocorrelation function on fetal heart rate variability measurement using the Doppler ultrasound signal

Roj D., Fuchs T., Przybyła T., Jeżewski M., Matonia A., Gacek A.

Journal of Medical Informatics & Technologies

|

2008

|

Vol. 12

111--116

EN

Commonly used noninvasive fetal monitoring is based on fetal heart rate (FHR) variability analysis of the Doppler ultrasound signal coming from the mechanical activity of the fetal heart. Estimation of periodicity of acquired signals using the autocorrelation technique is very important. The determination of cardiac intervals using the Doppler signal is more difficult than in electrocardiography, where the R-waves are evident. We investigated the influence of the autocorrelation window size on the FHR variability analysis. The indices describing the FHR variability calculated for signals obtained using two different autocorrelation techniques with various window lengths were compared with the reference ones obtained from fetal electrocardiogram. The optimal window was a compromise between artifacts resistance and the averaging level of instantaneous variability.

15

Influence of gestational age on neural networks interpretation of fetal monitoring signals

Jeżewski M., Czabański R., Horoba K., Wróbel J., Łęski J., Jeżewski J.

Journal of Medical Informatics & Technologies

|

2008

|

Vol. 12

137--142

EN

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.

16

Indexing biomedical streams in data management system

Widera M., Wróbel J., Matonia A., Jeżewski M., Horoba K., Kupka T.

Journal of Medical Informatics & Technologies

|

2005

|

Vol. 9

107--112

EN

We are developing Data Stream Management System that can be applied in medical monitoring system. One of the problems is how to support efficient data access methods. This paper considers indexing issues in data management system. The indexing is a commonly used method of data access acceleration. Classical and new streaming methods of indexing have been presented. The method was developed in data stream management system and first applied in a centralized neonatal monitoring system.