Relevant bibliographies by topics / Detection of QRS complexes

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

Academic literature on the topic 'Detection of QRS complexes'

Author: Grafiati
Published: 28 June 2021
Last updated: 29 July 2025

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Journal articles on the topic "Detection of QRS complexes"

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Salih, Sameer Kleban, S. A. Aljunid, Oteh Maskon, Syed M. Aljunid, and Abid Yahya. "A Robust Approach for Detecting QRS Complexes of Electrocardiogram Signal with Different Morphologies." Key Engineering Materials 594-595 (December 2013): 972–79. http://dx.doi.org/10.4028/www.scientific.net/kem.594-595.972.

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In this paper a robust approach for detecting QRS complexes and computing related R-R intervals of ECG signals named (RDQR) has been proposed. It reliably recognizes QRS complexes based on the deflection occurred between R & S waves as a large positive and negative amplitude differences in comparison with respect to other ECG signal (P and T) waves. The proposed detection approach applies the new direct algorithm applied on the entire ECG itself without any additional transform like (wavelet, cosine, Walsh transform, etc.). According to the strategy based on positive and negative deflectio
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Wei, Wei, Chun Xia Zhang, and Wei Lin. "A QRS Wave Detection Algorithm Based on Complex Wavelet Transform." Applied Mechanics and Materials 239-240 (December 2012): 1284–88. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.1284.

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Objective to introduce a method that use complex valued wavelet transform algorithm for QRS wave group detection in Electrocardiogram signal. It presents a method of marking the crest value and detecting QRS wave group by combining Fbsp wavelet with mexh wavelet. The method is proved to be precise and rapid by applied to detect 10 pieces of the QRS complexes of the ECG 30min-records provided by MIT-BIH Arrhythmia Database.
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Al-Ghabban, Ahmed Saad. "Predominant Peak Detection of QRS Complexes." International Journal of Medical Imaging 2, no. 6 (2014): 133. http://dx.doi.org/10.11648/j.ijmi.20140206.12.

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Sharma, Tanushree, and Kamalesh K. Sharma. "A new method for QRS detection in ECG signals using QRS-preserving filtering techniques." Biomedical Engineering / Biomedizinische Technik 63, no. 2 (2018): 207–17. http://dx.doi.org/10.1515/bmt-2016-0072.

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AbstractDetection of QRS complexes in ECG signals is required for various purposes such as determination of heart rate, feature extraction and classification. The problem of automatic QRS detection in ECG signals is complicated by the presence of noise spectrally overlapping with the QRS frequency range. As a solution to this problem, we propose the use of least-squares-optimisation-based smoothing techniques that suppress the noise peaks in the ECG while preserving the QRS complexes. We also propose a novel nonlinear transformation technique that is applied after the smoothing operations, whi
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Śmigiel, Sandra, Krzysztof Pałczyński, and Damian Ledziński. "Deep Learning Techniques in the Classification of ECG Signals Using R-Peak Detection Based on the PTB-XL Dataset." Sensors 21, no. 24 (2021): 8174. http://dx.doi.org/10.3390/s21248174.

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Deep Neural Networks (DNNs) are state-of-the-art machine learning algorithms, the application of which in electrocardiographic signals is gaining importance. So far, limited studies or optimizations using DNN can be found using ECG databases. To explore and achieve effective ECG recognition, this paper presents a convolutional neural network to perform the encoding of a single QRS complex with the addition of entropy-based features. This study aims to determine what combination of signal information provides the best result for classification purposes. The analyzed information included the raw
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SLIMANE, Z. E. HADJ, and F. BEREKSI REGUIG. "NEW ALGORITHM FOR QRS COMPLEX DETECTION." Journal of Mechanics in Medicine and Biology 05, no. 04 (2005): 507–15. http://dx.doi.org/10.1142/s0219519405001692.

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The Electrocardiogram (ECG), represents the electrical activity of the heart. It is characterized by a number of waves P, QRS, T which are correlated to the status of the heart activity. The most predominant wave set is the QRS complex. In this paper, we have developed a new algorithm for the detection of the QRS complexes. The algorithm consists of several steps: signal to noise enhancement, differentiation, first-order backward difference, non linear transform, moving window integrator and QRS detection. This algorithm is tested on ECG signals from the universal MIT-BIH arrhythmia database a
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Tariq, M. Younes, Alkhedher Mohammad, Al Khawaldeh Mohamad, Nawash Jalal, and Al-Abbas Ibrahim. "Less computational approach to detect QRS complexes in ECG rhythms." Computer Science and Information Technologies 2, no. 3 (2021): 113–20. https://doi.org/10.11591/csit.v2i3.p113-120.

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Electrocardiogram (ECG) signals are normally affected by artifacts that require manual assessment or use of other reference signals. Currently, Cardiographs are used to achieve basic necessary heart rate monitoring in real conditions. This work aims to study and identify main ECG features, QRS complexes, as one of the steps of a comprehensive ECG signal analysis. The proposed algorithm suggested an automatic recognition of QRS complexes in ECG rhythm. This method is designed based on several filter structure composes low pass, difference and summation filters. The filtered signal is fed to an
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Beyramienanlou, Hamed, and Nasser Lotfivand. "An Efficient Teager Energy Operator-Based Automated QRS Complex Detection." Journal of Healthcare Engineering 2018 (September 18, 2018): 1–11. http://dx.doi.org/10.1155/2018/8360475.

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Database. The efficiency and robustness of the proposed method has been tested on Fantasia Database (FTD), MIT-BIH Arrhythmia Database (MIT-AD), and MIT-BIH Normal Sinus Rhythm Database (MIT-NSD). Aim. Because of the importance of QRS complex in the diagnosis of cardiovascular diseases, improvement in accuracy of its measurement has been set as a target. The present study provides an algorithm for automatic detection of QRS complex on the ECG signal, with the benefit of energy and reduced impact of noise on the ECG signal. Method. The method is basically based on the Teager energy operator (TE
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Lee, Seungmin, Yoosoo Jeong, Daejin Park, Byoung-Ju Yun, and Kil Park. "Efficient Fiducial Point Detection of ECG QRS Complex Based on Polygonal Approximation." Sensors 18, no. 12 (2018): 4502. http://dx.doi.org/10.3390/s18124502.

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Electrocardiogram signal analysis is based on detecting a fiducial point consisting of the onset, offset, and peak of each waveform. The accurate diagnosis of arrhythmias depends on the accuracy of fiducial point detection. Detecting the onset and offset fiducial points is ambiguous because the feature values are similar to those of the surrounding sample. To improve the accuracy of this paper’s fiducial point detection, the signal is represented by a small number of vertices through a curvature-based vertex selection technique using polygonal approximation. The proposed method minimizes the n
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Kotas, M., J. Jezewski, A. Matonia, and T. Kupka. "Towards noise immune detection of fetal QRS complexes." Computer Methods and Programs in Biomedicine 97, no. 3 (2010): 241–56. http://dx.doi.org/10.1016/j.cmpb.2009.09.005.

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Dissertations / Theses on the topic "Detection of QRS complexes"

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Koc, Bengi. "Detection And Classification Of Qrs Complexes From The Ecg Recordings." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/2/12610328/index.pdf.

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Electrocardiography (ECG) is the most important noninvasive tool used for diagnosing heart diseases. An ECG interpretation program can help the physician state the diagnosis correctly and take the corrective action. Detection of the QRS complexes from the ECG signal is usually the first step for an interpretation tool. The main goal in this thesis was to develop robust and high performance QRS detection algorithms, and using the results of the QRS detection step, to classify these beats according to their different pathologies. In order to evaluate the performances, these algorithms were teste
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Malina, Ondřej. "Detekce začátku a konce komplexu QRS s využitím hlubokého učení." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442595.

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This thesis deals with the issue of automatic measurement of the duration of QRS complexes in ECG signals. Special emphasis is then placed on the possibility of automatic detection of QRS complexes while exciting cardiac tissue with a pacemaker. The content of this work is divided into four logical units, where the first part deals with the heart as an organ. It describes the origin and spread of excitement in the heart, its possible pathologies and their manifestations in ECG recording, it also deals with pacing and measuring ECG recording during simultaneous pacing. The second part of the th
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Hráček, Roman. "Softwarový balík pro frekvenční metody detekce QRS komplexu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-221390.

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Engström, Magnus, and Nadia Soheily. "EKG-analys och presentation." Thesis, KTH, Data- och elektroteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-154539.

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Tolkningen av EKG är en viktig metod vid diagnostisering av onormala hjärttillstånd och kan användas i förebyggande syfte att upptäcka tidigare okända hjärtproblem. Att enkelt kunna mäta sitt EKG och få det analyserat och presenterat på ett pedagogiskt sätt utan att behöva rådfråga en läkare är något det finns ett konsumentbehov av. Denna rapport beskriver hur en EKG-signal behandlas med olika algoritmer och metoder i syfte att detektera hjärtslag och dess olika parametrar. Denna information används till att klassificera varje hjärtslag för sig och därmed avgöra om användaren har en normal ell
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Klingspor, Måns. "Hilbert Transform : Mathematical Theory and Applications to Signal processing." Thesis, Linköpings universitet, Matematik och tillämpad matematik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-122736.

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The Hilbert transform is a widely used transform in signal processing. In this thesis we explore its use for three different applications: electrocardiography, the Hilbert-Huang transform and modulation. For electrocardiography, we examine how and why the Hilbert transform can be used for QRS complex detection. Also, what are the advantages and limitations of this method? The Hilbert-Huang transform is a very popular method for spectral analysis for nonlinear and/or nonstationary processes. We examine its connection with the Hilbert transform and show limitations of the method. Lastly, the con
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Brandejs, Jakub. "Detekce parametrů repolarizace ze signálu EKG." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220848.

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A T wave peak and offset detector based on an unpublished lead transformation that can be briefly described as multilead linear regression was proposed and implemented afterwards. Potential of the transformation as a useful QRS detection tool was revealed later on. Proposed QRS detector was put to the test of CSE database. Results were compared with work of other authors. Results of T wave peak and offset detector were introduced in visual way.
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Hanzelka, Adam. "Rozměřování experimentálních záznamů EKG." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220063.

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This master's thesis deals with an analysis of principles of ECG signals detection and delineation. The theoretical part describes heart electrophysiology and electrocardiography basics. Next, the most important QRS detection and ECG delineation algorithms are introduced. Especially the wavelet transform methods are described. In the practical part proper delineation algoriythm was realized. It was tested on the standard CSE database, then it was modified on data of isolated rabbit heartsand the results are published in the conclusion.
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Bajgar, Jiří. "Detekce P vlny v EKG signálech." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-221317.

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The aim of this diploma thesis is to introduce methods of detection of the QRS complex and the subsequent detection of P waves. The intention is to create a program by specified method in the software Matlab which will be able to implement this method. The thesis describes the basic and important methods of detection and subsequent algorithm to detect P waves. Solution of the algorithm is tested on real data. It also describes the automatic signal evaluation and the results of this automatic function.
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Bucsuházy, Kateřina. "Rozměření experimentálních záznamů EKG." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-221318.

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This master thesis deals with QRS complex detection and ECG delineation. The theoretical part of this work describes wavelet transform, some of QRS detection approaches and some of ECG delineation approaches. For algorithm realization in Matlab is used redundant dyadic discrete wavelet transform. Algorithm is designed for experimental electrocardiograms of isolated rabbit hearts and it is evaluated through manually determined references.
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Zaeid, Jabar, and Andreas Lind. "Utveckling av ny teknik för hjärtpulsdetektion." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-211571.

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In this thesis we suggest a technique for detecting pulses by signal processing of a raw ECG signal registered from 4 electrodes located on the left upper arm. The signal processing is performed in Matlab and consists of normalization, lowpass filtering, highpass filtering, derivation, squaring and a moving average window to reduce interference. The technology is capable of extracting periods between heartbeats after an implemented detection algorithm. The thesis also includes reflections on the types of interferences that may affect an electrical development equipment and also methods of how
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Books on the topic "Detection of QRS complexes"

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Jones, Michael, Norman Qureshi, and Kim Rajappan. Atrioventricular nodal re-entrant tachycardia. Edited by Patrick Davey and David Sprigings. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199568741.003.0114.

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Atrioventricular nodal re-entrant tachycardia (abbreviated as AVNRT) is one of the five subtypes of supraventricular tachycardia, manifesting most commonly as a regular, narrow QRS complex tachycardia, rate 150–250 min−1 (usually 160–180 min−1), occurring paroxysmally, with P waves either not apparent, or seen to follow the QRS complexes.
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Jones, Michael, Norman Qureshi, and Kim Rajappan. Ventricular tachyarrhythmias: Ventricular tachycardia and ventricular fibrillation. Edited by Patrick Davey and David Sprigings. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199568741.003.0118.

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Ventricular tachyarrhythmias are abnormal patterns of electrical activity arising from the ventricular tissue (myocardium and conduction tissue). Ventricular tachycardia (VT) is an abnormal rapid heart rhythm originating from the ventricles. The rhythm may arise from the ventricular myocardium and/or from the distal conduction system. The normal heart rate is usually regular, between 60 and 100 bpm, and there is synchronized atrial and ventricular contraction. In VT, the ventricles contract at a rate greater than 120 bpm and typically from 150 to 300 bpm, and are no longer coordinated with the
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Jones, Michael, Norman Qureshi, and Kim Rajappan. Atrial flutter. Edited by Patrick Davey and David Sprigings. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199568741.003.0117.

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Atrial flutter is the term given to one of the four types of supraventricular tachycardia; in it, atrial activation occurs as a consequence of a continuous ‘short circuit’: a defined and fixed anatomical route, resulting in a fairly uniform atrial rate, and uniform atrial flutter waves on the ECG. The ventricles are not a part of this arrhythmia circuit, and ventricular activation is variable, dependent on atrioventricular (AV) nodal conduction. Given that the atrial rate is essentially uniform (e.g. 300 min−1), ventricular activation tends to be regular (i.e. 150 min−1, 100 min−1, 75 min−1, e
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Muche, Marion, and Seema Baid-Agrawal. Hepatitis B. Edited by Vivekanand Jha. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0185_update_001.

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Hepatitis B virus (HBV) has been causally linked to a variety of renal diseases, the most common being glomerular diseases and systemic autoimmune disease. Membranous nephropathy (MN) is the commonest HBV-associated glomerulonephritis (HBV-GN), followed by membranoproliferative glomerulonephritis (MPGN), mesangial proliferative glomerulonephritis, immunoglobulin (Ig)-A nephropathy, and focal segmental glomerulosclerosis (FSGS). Polyarteritis nodosa is a rare manifestation. The incidence of HBV-associated renal diseases seems to be decreasing with the introduction of vaccination programmes.HBV-
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Book chapters on the topic "Detection of QRS complexes"

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Yoo, Kil-sang, and Won-hyung Lee. "QRS Complexes Detection in Electrocardiogram Signals Based on Multiresolution Analysis." In Lecture Notes in Electrical Engineering. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-5064-7_23.

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Höher, Martin, Siegfried Bauer, and Hans A. Kestler. "Detection of QRS-Variability." In Advances in Noninvasive Electrocardiographic Monitoring Techniques. Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-011-4090-4_10.

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Pander, Tomasz, and Tomasz Przybyła. "Fuzzy-Based Algorithm for QRS Detection." In Advances and New Developments in Fuzzy Logic and Technology. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77716-6_19.

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Domazet, Ervin, and Marjan Gusev. "Amplitude Rescaling Influence on QRS Detection." In Communications in Computer and Information Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00825-3_22.

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Bing, Lu, Xiaolei Han, and Wen Si. "RVM for Recognition of QRS Complexes in Electrocardiogram." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69096-4_17.

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Gupta, Lalita. "QRS Complex Detection Algorithm for Wearable Devices." In Lecture Notes in Electrical Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7031-5_16.

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Liu, Feifei, Chengyu Liu, Xinge Jiang, et al. "A Decision-Making Fusion Method for Accurately Locating QRS Complexes from the Multiple QRS Detectors." In IFMBE Proceedings. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-9038-7_66.

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Liao, Lijuan, Wei Zhong, Xuemei Guo, and Guoli Wang. "A Mixed Approach for Fetal QRS Complex Detection." In Proceedings of 2018 Chinese Intelligent Systems Conference. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2288-4_38.

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Silva, Pedro, Eduardo Luz, Elizabeth Wanner, David Menotti, and Gladston Moreira. "QRS Detection in ECG Signal with Convolutional Network." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13469-3_93.

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Gusev, Marjan, and Ervin Domazet. "Optimizing the Impact of Resampling on QRS Detection." In Communications in Computer and Information Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00825-3_10.

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Conference papers on the topic "Detection of QRS complexes"

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Battula, Krishna Tirumala, Bhavan S. Valavala, and Aruna Kukkala. "QRS Complex Detection Using Tahar Differentiator." In 2024 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia). IEEE, 2024. https://doi.org/10.1109/icce-asia63397.2024.10773771.

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Deák, Krisztián. "Discrete Wavelet Transform and Multiresolution Analysis for the R-Peak Detection of the QRS Complex of ECG Signals." In 10th International Scientific Conference on Advances in Mechanical Engineering. Trans Tech Publications Ltd, 2025. https://doi.org/10.4028/p-kajn3w.

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This paper shows the application of discrete wavelet transform in the analysis of ECG signals to detect R-peaks of the QRS complex. The proper analysis of the ECG signal is crucial to reveal the changes in the waveform to detect heart related diseases. The detection of the P-wave, T-wave, QRS complex is important and the wavelet transform offers a good possibility to recognize the abnormalities. Three different wavelets, Symlet, Coiflet and Daubechies are used for the detection and are compared to choose the most efficient one to identify the R-peaks. Multiresolution analysis (MRA) is used to
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Jain, Juhi, Chandan Kumar Roy, Rishab Pastariya, Avita Fuskele, V. Kishore Kumar, and Harshit Dubey. "ECG Signal Analysis with QRS Complex Detection for Accurate Cardiac Abnormality Diagnosis." In 2024 IEEE 4th International Conference on ICT in Business Industry & Government (ICTBIG). IEEE, 2024. https://doi.org/10.1109/ictbig64922.2024.10911213.

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Zhao, Ziheng, Baitao Lyu, Yang Xu, Yining Sun, and Xianjun Yang. "Exploiting Fuzzy Classification of Time and Amplitude for Efficient QRS Complex Detection." In 2024 4th International Conference on Artificial Intelligence, Robotics, and Communication (ICAIRC). IEEE, 2024. https://doi.org/10.1109/icairc64177.2024.10900062.

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Ngo, Binh Tan, Nghi Hoang Huu Thai, Hoai Luan Pham, and Thi Diem Tran. "A High-Performance FPGA Based on Convolutional Neural Network for QRS Complex Detection." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10724773.

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N, Revanth, and M. Anto Bennet. "Detection of QRS Complexes in ECG Signal." In 2023 IEEE International Conference on Integrated Circuits and Communication Systems (ICICACS). IEEE, 2023. http://dx.doi.org/10.1109/icicacs57338.2023.10100203.

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Kotas, Marian, Janusz Jezewski, Tomasz Kupka, and Krzysztof Horoba. "Detection of low amplitude fetal QRS complexes." In 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2008. http://dx.doi.org/10.1109/iembs.2008.4650278.

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Paralic, Martin. "Detection of QRS Complexes Using Convolutional Neural Network." In 2019 42nd International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2019. http://dx.doi.org/10.1109/tsp.2019.8768867.

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Shuyan, Wang. "Automatic Detection of QRS Complexes using Quantum Neural Networks." In 2008 International Conference on Biomedical Engineering And Informatics (BMEI). IEEE, 2008. http://dx.doi.org/10.1109/bmei.2008.19.

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Xiuyu Zheng, Zhen Li, LinLin Shen, and Zhen Ji. "Detection of QRS Complexes Based on Biorthogonal Spline Wavelet." In 2008 International Symposium on Information Science and Engineering (ISISE). IEEE, 2008. http://dx.doi.org/10.1109/isise.2008.61.

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Reports on the topic "Detection of QRS complexes"

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Leeladee, Pannee. Cooperative small-molecule activation toward sustainable catalysis. Faculty of Science, Chulalongkorn University, 2018. https://doi.org/10.58837/chula.res.2018.47.

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In this research, a series of copper complexes containing polypyridyl ligands were designed to study the influence from ligands, nuclearity, solvents and secondary coordination on reactivity toward small-molecule activation. This structure-reactivity relationship was used in investigation for oxygen reduction reactions (ORR), and applied in detection of ascorbic acid (AsH₂). Firstly, copper (II) complexes containing polypyridyl derivatives ligands (i.e., Cu(dpa), Cu(adpa) and Cu₂ (addpa)) were synthesized and fully characterized by elemental analysis, mass spectrometry and X-ray crystallograph
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Sessa, Guido, and Gregory Martin. role of FLS3 and BSK830 in pattern-triggered immunity in tomato. United States Department of Agriculture, 2016. http://dx.doi.org/10.32747/2016.7604270.bard.

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Pattern-recognition receptors (PRRs) located on the plant cell surface initiate immune responses by perceiving conserved pathogen molecules known as pathogen-associated molecular patterns (PAMPs). PRRs typically function in multiprotein complexes that include transmembrane and cytoplasmickinases and contribute to the initiation and signaling of pattern-triggered immunity (PTI). An important challenge is to identify molecular components of PRR complexes and downstream signaling pathways, and to understand the molecular mechanisms that mediate their function. In research activities supported by
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Sessa, Guido, and Gregory B. Martin. molecular link from PAMP perception to a MAPK cascade associated with tomato disease resistance. United States Department of Agriculture, 2012. http://dx.doi.org/10.32747/2012.7597918.bard.

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The research problem: The detection of pathogen-associated molecular patterns (PAMPs) by plant pattern recognition receptors (PRRs) is a key mechanism by which plants activate an effective immune response against pathogen attack. MAPK cascades are important signaling components downstream of PRRs that transduce the PAMP signal to activate various defense responses. Preliminary experiments suggested that the receptor-like cytoplasmickinase (RLCK) Mai5 plays a positive role in pattern-triggered immunity (PTI) and interacts with the MAPKKK M3Kε. We thus hypothesized that Mai5, as other RLCKs, fun
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Journal articles Dissertations / Theses
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