Wyniki wyszukiwania - Biblioteka Nauki

1

A new approach to adaptive threshold based method for QRS detection with fuzzy clustering

100%

Pander T.

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tom Vol. 42, no. 1

404--425

EN

The most crucial requirements for a QRS complex detection algorithm are accuracy, precision and repeatability. Most methods of detecting QRS complexes use the approach based on exceeding a certain amplitude threshold. However, the presence of noise in the electro-cardiographic signal can inhibit the accuracy and precision of detection especially for low amplitude QRS-complexes. The proposed algorithm uses a new approach for the amplitude threshold determination and in the decision stage. The fuzzy c-median clustering method is used to determine the amplitude threshold values for each sliding window across the composed detection function waveform. It allows us to adjust threshold value to noise variations in the ECG signal. When a specified amplitude threshold is exceeded by the detection function and finding the peaks in its waveform, potential QRS complexes can be identified. Then the identified peaks are evaluated on the basis of the speed of rising and falling slopes of detection function peak. It enables identification of only those peaks of the detection function whose location corresponds to QRS complexes. ECG recordings taken from the standard-available eight databases are used to evaluate the performance quality of the proposed method. The proposed QRS detector achieved sensitivity of 99.82%, positive predictivity of 99.88% over the validation MIT-BIH Arrhythmia Database. The overall sensitivity and positive predictivity are respectively 99.81% and 99.67%. Advantages of the proposed method are the robustness against noise, the accuracy and the simplicity of the algorithm that evaluates the candidate peaks of the detection function which indicate the QRS complexes.

2

Video summarization using color features and efficient adaptive threshold technique

100%

Cvetkovic S. , Jelenkovic M. , Nikolic S. V.

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tom R. 89, nr 2a

247--250

EN

Most of the methods for video summarization relay on complicated clustering algorithms that makes them too computationaly complex for real time applications. In this paper we propose an efficient approach for video summary generation that does not relay on complex clustering algorithms and does not require frame length as a parameter. Our method combines MPEG-7 Color Layout Descriptors with adaptive threshold technique to detect shot boundaries. For each shot a keyframe is extracted and similar keyframes are eliminated in a simple manner. A MOS measure evaluation on a standard dataset show that the method produces video summaries of highest visual quality.

PL

W artykule zaproponowano nieskomplikowany algorytm do tworzenia skrótów materiałów wideo. Metoda łączy w sobie deskryptor warstwy koloru MPEG-7 z techniką progu adaptacyjnego, co pozwala na wykrywanie granic stopklatki. Dla wielu takich samych lub podobnych klatek, pozostawiana jest tylko jedna z nich.

3

GOP Structure Adaptable to the Location of Shot Cuts

100%

Krulikovská L. , Polec J.

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tom Vol. 58, No. 2

129-134

EN

In this paper we present a novel two stage algorithm for improving video coding efficiency. The proposed method combines video cut detection and adaptive GOP structure. At first, we have proposed a new technique of frames' comparison for the shot cut detection. The majority of existing methods compare pairs of successive frames. We compare actual frame with its motion estimated prediction. We also present adaptive threshold. The efficiency of novel technique for video cut detection was confirmed through experiment and compared to the commonly used ones in the terms of recall and precision. The next step is to situate I frames to the positions of detected cuts during the process of video encoding. Finally the proposed method is verified by simulations and the obtained results are compared with fixed GOP structures of sizes 4, 8, 12, 16, 32, 64, 128 and GOP structure with length of entire video. Proposed method achieved the gain in bit rate from 15,33% to 50,59%, while not degrading PSNR in comparison to simulated fixed GOP structures.

4

Failure identification and isolation of DC-DC boost converter using a sliding mode controller and adaptive threshold

84%

Khater F. , Aibeche A. , Fellag S. A. , Doghmane M. Z. , Akroum H.

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2024

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tom Vol. 25, No. 3

art. no. 2024303

EN

DC-DC converters have become essential components in various industrial applications, including aerospace, electric vehicles, and renewable energy systems. However, ensuring enhanced reliability remains a critical challenge for these converters. Fault diagnosis and reliability analysis are crucial for preventing damage and minimizing maintenance costs. This study focuses on investigating the operational behavior of DC-DC boost converters under normal and faulty conditions, precisely targeting open-circuit and short-circuit faults in converter switches. To achieve this, an adaptive threshold approach is introduced for effective fault detection. The adaptive threshold value is calculated based on measured voltage and current signals, along with their corresponding reference signals from the primary control system. The research is structured into two parts: the first part addresses sliding mode control aspects, ensuring regulated output voltages, output currents, and capacitor voltage for sustained converter operation. The second part investigates fault diagnosis, analyzing the impact of defective DC-DC converters on the overall electrical system functionality. The proposed algorithm's performance is evaluated and validated through simulations in MATLAB/Simulink environment. Furthermore, based on the results’ comparison, the proposed approach of the sliding mode controller and adaptive threshold contributes to enhancing the reliability of DC-DC converters and enables effective fault detection and isolation.

5

QRS complex detection in noisy holter ECG based on wavelet singularity analysis

59%

Tadejko P. , Rakowski W.

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tom Z. 6

95-111

EN

In this paper, we propose a QRS complex detector based on the Mallat and Hwang singularity analysis algorithm which uses dyadic wavelet transform. We design a spline wavelet that is suitable for QRS detection. The scales of this decomposition are chosen based on the spectral characteristics of electrocardiogram records. By proceeding with the multiscale analysis we can find the location of a rapid change of a signal, and hence the location of the QRS complex. The performance of the algorithm was tested using the records of the MIT-BIH Arrhythmia Database. The method is less sensitive to timevarying QRS complex morphology, minimizes the problems associated with baseline drift, motion artifacts and muscular noise, and allows R waves to be differentiated from large T and P waves. We propose an original, new approach to adaptive threshold algorithm that exploits statistical properties of the observed signal and additional heuristic. The threshold is independent for each successive ECG signal window and the algorithm uses the properties of a series of distribution with a compartments class. The noise sensitivity of the new proposed adaptive thresholding QRS detector was also tested using clinical Holter ECG records from the Medical University of Bialystok.We illustrate the performance of the wavelet-based QRS detector by considering problematic ECG signals from a Holter device. We have compared this algorithm with the commercial Holter system - Del Mar’s Reynolds Pathfinder on the special episodes selected by cardiologist.

PL

Praca przedstawia algorytm detekcji zespołu QRS oparty na falkowej analizie osobliwości sygnału Mallata i Hwanga, wykorzystujący diadyczna˛ transformatę falkową. Filtry cyfrowe analizy falkowej odpowiadają falce i funkcji skalującej w postaci tzw. splineów bramkowych drugiego stopnia o zwartym i krótkim nośniku. Dzięki temu podczas analizy sygnału i detekcji osobliwości możemy dokładniej kontrolować parametry procesu separacji wybranych częstotliwości. Dzięki analizie wieloskalowej możliwe jest zlokalizowanie miejsca gwałtownej zmiany sygnału, a tym samym lokalizacji zespołu QRS. Metoda posiada mniejszą wrażliwość na zmiany morfologii kolejnych zespołów QRS, minimalizuje problemy związane z występowaniem składowej wolnozmiennej, artefaktów ruchu i napięcia mięśni oraz pozwala na łatwiejszą separację załamka R w stosunku do załamków P i T. W niniejszej pracy zaproponowano oryginalny, adaptacyjny sposób wyznaczania progu detekcji przy użyciu właściwości statystycznych obserwowanego sygnału oraz dodatkowych heurystyk. Metoda wyznaczania progu jest niezależna dla każdego kolejnego okna sygnału, składającego sie˛ z kilkunastu cykli EKG. Algorytm wyznacza wartość progu na podstawie analizy własności szeregu rozdzielczego z przedziałami klasowymi. Działanie algorytmu zostało przetestowane przy użyciu zapisów z bazy MIT-BIH Arytmia Database. Dodatkowo, wrażliwość na zakłócenia adaptacyjnego detektora QRS była przetestowana przy użyciu, specjalnie wyselekcjonowanych przez kardiologa, epizodów EKG z systemu Holtera z Uniwersytetu Medycznego w Białymstoku. Porównania wyników dokonano z komercyjnym systemem Pathfinder firmy Del Mar Reynolds.