Relevant bibliographies by topics / Processing of cyclic electrocardiographic signals

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Processing of cyclic electrocardiographic signals'

Author: Grafiati
Published: 28 May 2022

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Journal articles on the topic "Processing of cyclic electrocardiographic signals"

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Widasari, Edita Rosana, Koichi Tanno, and Hiroki Tamura. "Automatic Sleep Disorders Classification Using Ensemble of Bagged Tree Based on Sleep Quality Features." Electronics 9, no. 3 (2020): 512. http://dx.doi.org/10.3390/electronics9030512.

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Sleep disorder is a medical disease of the sleep patterns, which commonly suffered by the elderly. Sleep disorders diagnosis and treatment are considered to be challenging due to a time-consuming and inconvenient process for the patient. Moreover, the use of Polysomnography (PSG) in sleep disorder diagnosis is a high-cost process. Therefore, we propose an efficient classification method of sleep disorder by merely using electrocardiography (ECG) signals to simplify the sleep disorders diagnosis process. Different from many current related studies that applied a five-minute epoch to observe the
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Abdullaev, N. T., O. A. Dyshin, and G. T. Khasmamedova. "Spectral Analysis of Electrocardiographic Signals Based on Wavelet-Packet Processing." Biomedical Engineering 44, no. 1 (2010): 27–31. http://dx.doi.org/10.1007/s10527-010-9149-x.

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Lupenko, Serhii, Iaroslav Lytvynenko, Volodymyr Hotovych, Andrii Zozulia, Nnamene Chizoba, and Oleksandr Volyanyk. "Concept of design, requirements and generalized architectures of components of the integrated onto-oriented information environment of simulation and processing of cyclic signals." Scientific journal of the Ternopil national technical university 102, no. 2 (2021): 147–60. http://dx.doi.org/10.33108/visnyk_tntu2021.02.147.

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The article gives the reasoning to the relevance of developing a generalized architecture of integrated onto-oriented information environment for simulation and processing of cyclic signals based on the theory of cyclic functional relations, as well as formulates the general requirements to it and its developingt. The research deals with statement of and creating the generalized architectures of the components of the integrated onto-oriented information environment for simulation and processing of cyclic signals, namely, for information-oriented reference system in the field of simulation and
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Castillo, E., D. P. Morales, A. García, F. Martínez-Martí, L. Parrilla, and A. J. Palma. "Noise Suppression in ECG Signals through Efficient One-Step Wavelet Processing Techniques." Journal of Applied Mathematics 2013 (2013): 1–13. http://dx.doi.org/10.1155/2013/763903.

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This paper illustrates the application of the discrete wavelet transform (DWT) for wandering and noise suppression in electrocardiographic (ECG) signals. A novel one-step implementation is presented, which allows improving the overall denoising process. In addition an exhaustive study is carried out, defining threshold limits and thresholding rules for optimal wavelet denoising using this presented technique. The system has been tested using synthetic ECG signals, which allow accurately measuring the effect of the proposed processing. Moreover, results from real abdominal ECG signals acquired
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Coccia, Armando, Federica Amitrano, Leandro Donisi, et al. "Design and validation of an e-textile-based wearable system for remote health monitoring." ACTA IMEKO 10, no. 2 (2021): 220. http://dx.doi.org/10.21014/acta_imeko.v10i2.912.

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<p class="Abstract">The paper presents a new e-textile-based system, named SWEET Shirt, for the remote monitoring of biomedical signals. The system includes a textile sensing shirt, an electronic unit for data transmission, a custom-made Android application for real-time signal visualisation and a software desktop for advanced digital signal processing. The device allows for the acquisition of electrocardiographic, bicep electromyographic and trunk acceleration signals. The sensors, electrodes, and bus structures are all integrated within the textile garment, without any discomfort for u
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Fedotov, A. A. "Analysis of parameters for smoothing electrocardiographic signals Aleksandr A. Fedotov." Izmeritel`naya Tekhnika, no. 12 (December 2019): 47–51. http://dx.doi.org/10.32446/0368-1025it.2019-12-47-51.

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The article is devoted to the consideration of the features of smoothing filtering of ECG signal against the background of electromyographic distortions of various magnitude. The main goal of the research is comparative analysis of various options for the implementation of smoothing filtering of an ECG signal contaminated by myographic interference in order to determine the optimal approach in terms of minimizing biosignal distortions and measurement errors of its amplitude-time characteristics. To obtain quantitative characteristics of effectiveness of various methods for smoothing filtering
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Patel, Santosh I., Michael J. Souter, David S. Warner, and Mark A. Warner. "Equipment-related Electrocardiographic Artifacts." Anesthesiology 108, no. 1 (2008): 138–48. http://dx.doi.org/10.1097/01.anes.0000296537.62905.25.

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Interference of the monitored or recorded electrocardiogram is common within operating room and intensive care unit environments. Artifactual signals, which corrupt the normal cardiac signal, may arise from internal or external sources. Electrical devices used in the clinical setting can induce artifacts by various different mechanisms. Newer diagnostic and therapeutic modalities may generate artifactual changes. These artifacts may be nonspecific or may resemble serious arrhythmia. Clinical signs, along with monitored waveforms from other simultaneously monitored parameters, may provide the c
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Barbosa Casanova, Giovanny, Darwin Orlando Cardozo Sarmiento, Mario Joaquin Illera Bustos, Andrés Orozco Duque, and Henry Andrade Caicedo. "Techniques of Acquisition and Processing of Electrocardiographic Signals in the Detection of Cardiac Arrhythmias." Respuestas 24, no. 2 (2019): 91–100. http://dx.doi.org/10.22463/0122820x.1835.

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The development of ambulatory monitoring systems and its electrocardiographic (ECG) signal processing techniques has become an important field of investigation, due to its relevance in the early detection of cardiovascular diseases such as the arrhythmias. The current trend of this technology is oriented to the use of portable equipment and mobile devices such as Smartphones, which have been widely accepted due to the technical characteristics and common integration in daily life. A fundamental characteristic of these systems is their ability to reduce the most common types of noise by means o
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Vucic, D., and M. Eric. "Cyclic Spectral Analysis of UWB-IR Signals." IEEE Signal Processing Letters 16, no. 8 (2009): 723–26. http://dx.doi.org/10.1109/lsp.2009.2023949.

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Costa Junior, José Dilermando, José Manoel de Seixas, and Antonio Mauricio Ferreira Leite Miranda de Sá. "A template subtraction method for reducing electrocardiographic artifacts in EMG signals of low intensity." Biomedical Signal Processing and Control 47 (January 2019): 380–86. http://dx.doi.org/10.1016/j.bspc.2018.09.004.

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Dissertations / Theses on the topic "Processing of cyclic electrocardiographic signals"

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Вівчарик, Валентин Степанович, та Valentyn Stepanovich Vivcharyk. "Методи та засоби віддаленої інженерії в задачах моделювання та опрацювання циклічних сигналів". Master's thesis, Тернопільський національний технічний університет імені Івана Пулюя, 2020. http://elartu.tntu.edu.ua/handle/lib/33266.

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В кваліфікаційній роботі магістра досліджено методи та інструментальні засоби віддаленої інженерії для створення системи, що буде використовувати функціонал віддаленої лабораторії для моделювання та опрацювання циклічних електрокардіосигналів. Розглянуто детерміновані та стохастичні моделі циклічних сигналів, а також віддалена лабораторія, з якою методами віддаленої інженерії було інтегровано написаний веб сайт, який слугує представленням роботи комп’ютерної системи по обробці циклічних сигналів серця, що використовує вже заготовлену функціональність готової лабораторії. Розглянуто осно
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Lutsyk, Nadiia. "Modeling and methods of biomechanical heart signals processing using the conditional cyclic random process." Thesis, Clermont-Ferrand 2, 2016. http://www.theses.fr/2016CLF22726.

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Ce travail a été réalisé en cotutelle entre l'Université Nationale de Technologie de Ternopil Ivan Pul'uj (TNTU, Ukraine) et l’Université Blaise Pascal (France). Il appartient au domaine scientifique de la biomécanique et de l'informatique. Le but de l'étude est de développer les modèles et les méthodes de traitement des signaux biomécaniques cardiaques par les systèmes de diagnostic assisté par ordinateur avec une précision accrue, informativité et de la complexité de calcul inférieure. La méthode d'analyse statistique du rythme cardiaque a été mise au point. Cette méthode possède une plus gr
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Ннамене, Крістофер Чізоба. "Комп’ютерна онтологія предметної області «Моделювання та опрацювання циклічних сигналів»". Diss., Тернопільський національний технічний університет ім. Івана Пулюя, 2021. http://elartu.tntu.edu.ua/handle/lib/36019.

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Дисертація присвячена вирішенню актуального наукового завдання розробки концептуальних, формальних та машинно-інтерпретовних моделей подання та організації знань в інтегрованому онтоорієнтованому інформаційному середовищі для моделювання та опрацювання циклічних сигналів в рамках теорії циклічних функціональних відношень, а також побудові на їх основі прототипу комп’ютерної онтології предметної області «Моделювання та опрацювання циклічних сигналів», що є ядром бази знань таких онтоорієнтованих інформаційних систем як інформаційна довідкова система, експертна система підтримки прийняття рішень
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Литвиненко, Ярослав Володимирович, Я. В. Литвиненко та I. V. Lytvynenko. "Методи ідентифікації сегментної та ритмічної структур циклічних сигналів в системах цифрової обробки даних". Diss., Тернопільський національний технічний університет ім. Івана Пулюя, 2019. http://elartu.tntu.edu.ua/handle/lib/29099.

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Дисертація на здобуття наукового ступеня доктора технічних наук за спеціальністю 01.05.02 – «Математичне моделювання та обчислювальні методи». – Тернопільський національний технічний університет імені Івана Пулюя, Тернопіль, 2019. Дисертація присвячена вирішенню проблеми ідентифікації сегментних і ритмічних структур циклічних сигналів, що підвищують точність їх опрацювання та комп’ютерного моделювання в автоматизованих системах цифрової обробки даних. Створено методологію побудови методів сегментації різних циклічних сигналів, м
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Books on the topic "Processing of cyclic electrocardiographic signals"

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Alcocer, P. R. C. Optical processing of electrocardiographic signals. 1994.

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Book chapters on the topic "Processing of cyclic electrocardiographic signals"

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Micó, Pau, David Cuesta, and Daniel Novák. "Clustering Improvement for Electrocardiographic Signals." In Image Analysis and Processing – ICIAP 2005. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11553595_109.

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Verma, Rishendra, Rini Mehrotra, and Vikrant Bhateja. "A New Morphological Filtering Algorithm for Pre-Processing of Electrocardiographic Signals." In Lecture Notes in Electrical Engineering. Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-0997-3_18.

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Georgieva-Tsaneva, Galya Nikolova. "Mathematical Processing of Cardiological Signals and Organization of Access to Holter Databases." In Advances in Systems Analysis, Software Engineering, and High Performance Computing. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7879-6.ch012.

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The study of human cardiovascular activity is one of the main methods for assessing the health of the human. It is performed in clinical conditions via electrocardiographic devices and in the daily life of a individuals through Holter monitoring. An important diagnostic parameter that can be determined by an electrocardiogram, taking into account the difference between successive heartbeat is heart rate variability – a widely used non-invasive method of measuring heart rate. This parameter makes it possible to assess the risk of various cardiac diseases such as angina, cardiac infarction, life-threatening arrhythmias, etc. This chapter presents the morphological bases of the cardio records, heart rate variability, and its impact on the healthy status of the individual. It describes the created cardiology base of prolongated Holter recordings for the purposes of scientific research project. Presented are internationally approved standards to provide web accessibility to internet-based data bases and other resources for people with disabilities.
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Wu, Yunfeng, and Rangaraj M. Rangayyan. "Noise Cancellation in ECG Signals with an Unbiased Adaptive Filter." In Transdisciplinary Advancements in Cognitive Mechanisms and Human Information Processing. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-60960-553-7.ch022.

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The electrocardiographic (ECG) signal is a transthoracic manifestation of the electrical activity of the heart and is widely used in clinical applications. This chapter describes an unbiased linear adaptive filter (ULAF) to attenuate high-frequency random noise present in ECG signals. The ULAF does not contain a bias in its summation unit and the filter coefficients are normalized. During the adaptation process, the normalized coefficients are updated with the steepest-descent algorithm to achieve efficient filtering of noisy ECG signals. A total of 16 ECG signals were tested in the adaptive filtering experiments with the ULAF, the least-mean-square (LMS), and the recursive-least-squares (RLS) adaptive filters. The filtering performance was quantified in terms of the root-mean-squared error (RMSE), normalized correlation coefficient (NCC), and filtered noise entropy (FNE). A template derived from each ECG signal was used as the reference to compute the measures of filtering performance. The results indicated that the ULAF was able to provide noise-free ECG signals with an average RMSE of 0.0287, which was lower than the second-best RMSE obtained with the LMS filter. With respect to waveform fidelity, the ULAF provided the highest average NCC (0.9964) among the three filters studied. In addition, the ULAF effectively removed more noise, measured by FNE, in comparison with the LMS and RLS filters in most of the ECG signals tested. The issues of adaptive filter setting for noise reduction in ECG signals are discussed at the end of this chapter.
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Conference papers on the topic "Processing of cyclic electrocardiographic signals"

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Rezgui, Dhouha, and Zied Lachiri. "Integrating EMD attributes for person identification from electrocardiographic signals." In 2016 2nd International Conference on Advanced Technologies for Signal and Image Processing (ATSIP). IEEE, 2016. http://dx.doi.org/10.1109/atsip.2016.7523121.

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Molero Alabau, Rubén, Andreu M. Climent, and Maria de la Salud Guillem Sánchez. "Post-Processing of Electrocardiographic Imaging Signals to Identify Atrial Fibrillation Drivers." In 2020 Computing in Cardiology Conference. Computing in Cardiology, 2020. http://dx.doi.org/10.22489/cinc.2020.113.

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Serhii, Lupenko, Orobchuk Oleksandra, Stadnik Nataliya, and Zozulya Andrii. "Modeling and Signals Processing Using Cyclic Random Functions." In 2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT). IEEE, 2018. http://dx.doi.org/10.1109/stc-csit.2018.8526653.

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Wang, Qingyuan, Zhidong Xie, Jing Hu, and Gengxin Zhang. "Blind detection of satellite communication signals based on cyclic spectrum." In 2015 International Conference on Wireless Communications & Signal Processing (WCSP). IEEE, 2015. http://dx.doi.org/10.1109/wcsp.2015.7341216.

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Jin, Yan, and Hongbing Ji. "Cyclic Statistic Based Blind Parameter Estimation of BPSK and QPSK Signals." In 2006 8th international Conference on Signal Processing. IEEE, 2006. http://dx.doi.org/10.1109/icosp.2006.344452.

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Manimohan, V. B., and W. J. Fitzgerald. "Direction estimation using conjugate cyclic cross-correlation: more signals than sensors." In 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258). IEEE, 1999. http://dx.doi.org/10.1109/icassp.1999.761363.

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Zaichenko, Kirill V., and Boris V. Gurevich. "Early diagnostics of ischemia by means of electrocardiographic signals processing using acousto-optic Fourier processors with time integration." In Novel Biophotonics Techniques and Applications, edited by Arjen Amelink and Seemantini K. Nadkarni. SPIE, 2019. http://dx.doi.org/10.1117/12.2535709.

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Ghosh, Ribhu D., and D. K. Mehra. "Cyclostationary spectrum sensing for OFDM signals in the presence of cyclic frequency offset." In 2014 International Conference on Signal Processing and Communications (SPCOM). IEEE, 2014. http://dx.doi.org/10.1109/spcom.2014.6983990.

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Morelande, M. "Optimal phase parameter estimation of random amplitude linear FM signals using cyclic moments." In 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258). IEEE, 1999. http://dx.doi.org/10.1109/icassp.1999.756283.

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Hikosaka, Yuichiro, Teruo Kawamura, Nobuhiko Miki, and Mamoru Sawahashi. "Hybrid reference signal multiplexing using combination of block spread and cyclic shift CDMA for uplink control signals in DFT-precoded OFDMA." In Signal Processing (WCSP 2011). IEEE, 2011. http://dx.doi.org/10.1109/wcsp.2011.6096890.

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