Autor: Momot, M. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Characteristic points detection in ECG signal using Bayesian learning and fuzzy system
Autorzy:: Momot, M.
Momot, A.
Powiązania:: https://bibliotekanauki.pl/articles/333840.pdf
Data publikacji:: 2007
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: sygnał EKG
systemy rozmyte
ECG signal
fuzzy systems
bayesian learning
Opis:: Characteristic points detection such as beginnings and ends of P-wave, T-wave or QRS complex is one of primary aims in automated analysis of ECG signal. The paper presents one possible approach based on Bayesian inference to design of kernel based classifier. The classification function is constructed using the probability distribution function of standard normal distribution and independent Gaussian random variables. The parameters of such variables are computed using iterative Expectation-Maximization algorithm. This approach is used to calculate parameters of classification function to modelling Takagi-Sugeno-Kang fuzzy systems. Numerical experiment of characteristic points detection in ECG signal using CTS database is also presented.
Źródło:: Journal of Medical Informatics & Technologies; 2007, 11; 171-176
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Granular representation of biomedical signals using numerical differentiation methods
Autorzy:: Momot, M.
Momot, A.
Gacek, A.
Powiązania:: https://bibliotekanauki.pl/articles/332925.pdf
Data publikacji:: 2010
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: grupowanie
liczby rozmyte
granulacja informacji
interpolacja
kryterium odbudowy
clustering
fuzzy number
information granulation
interpolation
reconstruction criterion
Opis:: This work presents the general idea of granular description of temporal signal, particularly biomedical signal sampled with constant frequency. The main idea of presented method is based on using triangular fuzzy numbers as information granules in temporal and amplitude spaces. The amplitude space contains values of first few derivatives of underlying signal. The construction of data granules is performed using the optimization method according to some objective function, which balances the high coverage ability and the low support of fuzzy numbers. The granules (descriptors) undergo the clustering process, namely fuzzy c-means. The centroids of created clusters form a granular vocabulary and the quality of description is quantitatively assessed by reconstruction criterion. There are presented results of experiments with the electrocardiographic signal, digitally sampled and stored in MIT-BIH database. The method of numerical differentiation of function based on finite set of its values is employed, which incorporates polynomial interpolation. The paper presents results of numerical experiments which show the impact of method parameters, such as temporal window length, degree of polynomial, fuzzification parameter, on the reconstruction ability of presented method.
Źródło:: Journal of Medical Informatics & Technologies; 2010, 16; 43-49
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Segmentation of images using gradient methods and polynomial approximation
Autorzy:: Piekar, E.
Momot, M.
Momot, A.
Powiązania:: https://bibliotekanauki.pl/articles/333120.pdf
Data publikacji:: 2014
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: segmentation
gradient methods
polynomial approximation
segmentacja
metody gradientowe
przybliżenie wielomianowe
Opis:: The paper presents a method for segmentation of images using region growing, with modification through the use of a correction coefficient based on the variation of intensity (brightness) in the neighborhood of the pixel of the interest. A method for the quantification of variability is based on differences in intensity, as well as the differences in intensity gradients in the surrounding pixels [10]. Evaluation of the gradients were determined by means of numerical differentiation, using the polynomial approximation [11]. The article presents the effects of application of developed methods for segmentation of images of the brain, lungs and heart.
Źródło:: Journal of Medical Informatics & Technologies; 2014, 23; 95-102
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Empirical Bayesian averaging method and its application to noise reduction in ECG signal
Autorzy:: Momot, A.
Momot, M.
Łęski, J.
Powiązania:: https://bibliotekanauki.pl/articles/333575.pdf
Data publikacji:: 2006
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: sygnał EKG
średnia ważona
wnioskowanie bayesowskie
ECG signal
weighted averaging
Bayesian inference
Opis:: An electrocardiogram (ECG) is the prime tool in non-invasive cardiac electrophysiology and has a prime function in the screening and diagnosis of cardiovascular diseases. However one of the greatest problems is that usually recording an electrical activity of the heart is performed in the presence of noise. The paper presents empirical Bayesian approach to problem of signal averaging which is commonly used to extract a useful signal distorted by a noise. The averaging is especially useful for biomedical signal such as ECG signal, where the spectra of the signal and noise significantly overlap. In reality the variability of noise can be observed, with power from cycle to cycle, which is motivation for weighted averaging methods usage. It is demonstrated that by exploiting a probabilistic Bayesian learning framework, it can be derived accurate prediction models offering significant additional advantage, namely automatic estimation of 'nuisance' parameters. Performance of the new method is experimentally compared to the traditional averaging by using arithmetic mean and weighted averaging method based on criterion function minimization.
Źródło:: Journal of Medical Informatics & Technologies; 2006, 10; 93-101
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: The Fuzzy Relevance Vector Machine and its application to noise reduction in ECG signal
Autorzy:: Momot, A.
Momot, M.
Łęski, J.
Powiązania:: https://bibliotekanauki.pl/articles/333828.pdf
Data publikacji:: 2005
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: systemy rozmyte
wnioskowanie bayesowskie
sygnał EKG
fuzzy systems
Bayesian inference
ECG signal
Opis:: The paper presents new method called the Fuzzy Relevance Vector Machine (FRVM), a modification of the relevance vector machine, introduced by M. Tipping, applied to learning Takagi-Sugeno-Kang (TSK) fuzzy system. Moreover it describes application of the FRVM to noise reduction in ECG signal. The results of the process are compared to those obtained using both Least Squares method for learning output functions in TSK rules and commonly used method using a low-pass moving average filter.
Źródło:: Journal of Medical Informatics & Technologies; 2005, 9; 99-105
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Weighted averaging of ECG signals based on partition of input set in time domain
Autorzy:: Momot, A.
Momot, M.
Łęski, J.
Powiązania:: https://bibliotekanauki.pl/articles/333836.pdf
Data publikacji:: 2007
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: sygnał EKG
ważone uśrednianie
redukcja hałasu
ECG signal
weighted averaging
noise reduction
Opis:: The paper presents new approach to problem of signal averaging which is commonly used to extract a useful signal distorted by a noise. The averaging is especially useful for biomedical signal such as ECG signal, where the spectra of the signal and noise significantly overlap. In reality can be observed variability of noise power from cycle to cycle which is motivation for using methods of weighted averaging. Performance of the new method, based on partition of input set in time domain and criterion function minimization, is experimentally compared with the traditional averaging by using arithmetic mean, weighted averaging method based on empirical Bayesian approach and weighted averaging method based on criterion function minimization.
Źródło:: Journal of Medical Informatics & Technologies; 2007, 11; 165-170
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

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: 8.

Tytuł:: Sparse Bayesian learning in classifying face feature vectors
Autorzy:: Momot, A.
Kawulok, M.
Powiązania:: https://bibliotekanauki.pl/articles/333794.pdf
Data publikacji:: 2005
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: wnioskowanie bayesowskie
rozpoznanie twarzy
supervised learning
Bayesian inference
face recognition
Opis:: The Relevance Vector Machine (RVM), a Bayesian treatment of generalized linear model of identical functional form to the Support Vector Machine (SVM), is the recently developed machine learning framework capable of building simple models from large sets of candidate features. The paper describes the application of the RVM to a classification algorithm of face feature vectors, obtained by Eigenfaces method. Moreover, the results of the RVM classification are compared with those obtained by using both the Support Vector Machine method and the method based on the Euclidean distance.
Źródło:: Journal of Medical Informatics & Technologies; 2005, 9; 151-158
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Filtering of two-dimensional digital images using weighted averaging for adaptive selection of weights
Autorzy:: Momot, A.
Wrobel, J.
Horoba, K.
Jeżewski, M.
Bernys, M.
Powiązania:: https://bibliotekanauki.pl/articles/951702.pdf
Data publikacji:: 2012
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: filtracja obrazów
ważone uśrednianie
image filtering
weighted averaging
adaptive selection of weights
Opis:: 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.
Źródło:: Journal of Medical Informatics & Technologies; 2012, 20; 93-99
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Comparison of instantaneous fetal heart rate extracted from abdominal and direct fetal electrocardiograms
Autorzy:: Matonia, A.
Kupka, T.
Jezewski, J.
Momot, A.
Jeżewski, M.
Bernys, M.
Powiązania:: https://bibliotekanauki.pl/articles/333262.pdf
Data publikacji:: 2012
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: monitorowanie płodu
elektrokardiografia płodu
tętno płodu
fetal monitoring
fetal electrocardiography
fetal heart rate
Opis:: 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.
Źródło:: Journal of Medical Informatics & Technologies; 2012, 19; 101-107
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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