Auswahl der wissenschaftlichen Literatur zum Thema „Premature ventricular contraction“

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Zeitschriftenartikel zum Thema "Premature ventricular contraction"

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Oner, Taliha, Rahmi Ozdemir, Onder Doksöz, Dildar B. Genc, Baris Guven, Savas Demirpence, Murat M. Yilmazer, Yilmaz Yozgat, Timur Mese und Vedide Tavli. „Cardiac function in children with premature ventricular contractions: the effect of omega-3 polyunsaturated fatty acid supplementation“. Cardiology in the Young 28, Nr. 7 (15.05.2018): 949–54. http://dx.doi.org/10.1017/s1047951118000574.

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AbstractBackgroundPremature ventricular contractions are accepted as benign in structurally normal hearts. However, reversible cardiomyopathy can sometimes develop. Omega-3 polyunsaturated fatty acids have anti-arrhythmic properties in animals and humans.AimWe evaluated left ventricular function in children with premature ventricular contractions with normal cardiac anatomy and assessed the impact of omega-3 fatty acid supplementation on left ventricular function in a prospective trial.MethodsA total of 25 patients with premature ventricular contraction, with more than 2% premature ventricular contractions on 24-hour Holter electrocardiography, and 30 healthy patients were included into study. All patients underwent electrocardiography, left ventricular M-mode echocardiography, and myocardial performance index testing. Patients with premature ventricular contraction were given omega-3 fatty acids at a dose of 1 g/day for 3 months, and control echocardiography and 24-hour Holter electrocardiography were performed. Neither placebo nor omega-3 fatty acids were given to the control group.ResultsCompared with the values of the control group, the patients with premature ventricular contraction had significantly lower fractional shortening. The myocardial performance index decreased markedly in the patient groups. The mean heart rate and mean premature ventricular contraction percentage of Group 2 significantly decreased in comparison with their baseline values after the omega-3 supplementation.ConclusionIn conclusion, premature ventricular contractions can lead to systolic cardiac dysfunction in children. Omega-3 supplementation may improve cardiac function in children with premature ventricular contractions. This is the first study conducted in children to investigate the possible role of omega-3 fatty acid supplementation on treatment of premature ventricular contractions.
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Baranov, Alexander A., Elena S. Vasichkina, Roza A. Ildarova, Dmitry S. Lebedev, Leyla S. Namazova-Baranova, Evgeniy A. Pokushalov, Sergey V. Popov, Sergey A. Termosesov und Maria A. Shkolnikova. „Premature Ventricular Contraction in Children“. Pediatric pharmacology 15, Nr. 6 (20.02.2019): 435–46. http://dx.doi.org/10.15690/pf.v15i6.1981.

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The article presents updated data on the problem of premature ventricular contractions in children based on the clinical guidelines of the Russian Society of Cardiology and the Union of Pediatricians of Russia for the diagnosis, treatment and management of pediatric patients with premature ventricular contraction. The issues of diagnosis and treatment based on the principles of evidence-based medicine as well as important aspects of prevention of exacerbations and follow-up have been clarified in detail. The criteria for assessing the quality of care for patients with premature ventricular contractions have been presented.CONFLICT OF INTEREST. Not declared.
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Spector, Zebulon Z., und Stephen P. Seslar. „Premature ventricular contraction-induced cardiomyopathy in children“. Cardiology in the Young 26, Nr. 4 (17.06.2015): 711–17. http://dx.doi.org/10.1017/s1047951115001110.

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AbstractBackgroundAdults with high premature ventricular contraction burden can develop left ventricular dilation, dysfunction, and strain, consistent with a cardiomyopathy, which is reversible with radiofrequency ablation of the premature ventricular contractions. Evidence in children with similar ectopy burden is limited. We performed a single-centre retrospective review to examine the prevalence of premature ventricular contraction-induced cardiomyopathy, natural history of ventricular ectopy, and progression to ventricular tachycardia in children with frequent premature ventricular contractions.MethodsChildren aged between 6 months and 18 years, with premature ventricular contractions comprising at least 20% of rhythm on 24-hour Holter monitor, were included in our study. Those with significant structural heart disease, ventricular tachycardia greater than 1% of rhythm at the time of premature ventricular contraction diagnosis, or family history of cardiomyopathy – except tachycardia-induced – were excluded. Cardiomyopathy was defined by echocardiographic assessment.ResultsA total of 36 children met the study criteria; seven patients (19.4%, 95% CI 6.2–32.6%) met the criteria for cardiomyopathy, mostly at initial presentation. Ectopy decreased to <10% of beats without intervention in 16.7% (95% CI 4.3–29.1%) of the patients. No patient progressed to having ventricular tachycardia as more than 1% of beats on follow-up Holter. Radiofrequency ablation was performed in three patients without cardiomyopathy.ConclusionsOur study demonstrates a higher prevalence of cardiomyopathy among children with high premature ventricular contraction burden than that previously shown. Ectopy tended to persist throughout follow-up. These trends suggest the need for a multi-centre study on frequent premature ventricular contractions in children. In the interim, regular follow-up with imaging to evaluate for cardiomyopathy is warranted.
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Latchamsetty, Rakesh, und Frank Bogun. „Premature Ventricular Contraction Ablation“. Cardiac Electrophysiology Clinics 4, Nr. 3 (September 2012): 439–45. http://dx.doi.org/10.1016/j.ccep.2012.05.009.

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Callans, David J. „Premature Ventricular Contraction-induced Cardiomyopathy“. Arrhythmia & Electrophysiology Review 6, Nr. 4 (2017): 153. http://dx.doi.org/10.15420/aer.2017/6.4/eo1.

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Premature ventricular contractions (PVCs) are very common and usually do not require treatment. However, in the clinical setting of troublesome symptoms, or when PVCs trigger polymorphic ventricular tachycardia or cause cardiomyopathy, proper treatment is critical. In this review, the clinical syndrome of PVC-induced cardiomyopathy, including risk factors for development and treatment, is discussed. Although PVC-induced cardiomyopathy is typically associated with frequent PVCs there are also patients with this burden that do not develop cardiomyopathy, suggesting a differential susceptibility. Treatment often consists of catheter ablation, although antiarrhythmic medications may also provide both reduction in PVC frequency and resolution of left ventricular dysfunction.
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Saurav, Alok, Aiman Smer, Ahmed Abuzaid, Ojas Bansal und Hussam Abuissa. „Premature Ventricular Contraction-Induced Cardiomyopathy“. Clinical Cardiology 38, Nr. 4 (10.02.2015): 251–58. http://dx.doi.org/10.1002/clc.22371.

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Lee, Andrea K. Y., und Marc W. Deyell. „Premature ventricular contraction-induced cardiomyopathy“. Current Opinion in Cardiology 31, Nr. 1 (Januar 2016): 1–10. http://dx.doi.org/10.1097/hco.0000000000000236.

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Cha, Yong-Mei, Glenn K. Lee, Kyle W. Klarich und Martha Grogan. „Premature Ventricular Contraction-Induced Cardiomyopathy“. Circulation: Arrhythmia and Electrophysiology 5, Nr. 1 (Februar 2012): 229–36. http://dx.doi.org/10.1161/circep.111.963348.

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Hutchinson, Mathew D. „Idiopathic Premature Ventricular Contraction Ablation“. JACC: Clinical Electrophysiology 1, Nr. 3 (Juni 2015): 124–26. http://dx.doi.org/10.1016/j.jacep.2015.05.001.

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Kanemori, Tetsuzou, Hideshi Ishii, Hideo Matsuhisa, Takuya Fujita, Youhei Tada, Syou Yagi, Chinami Miyazaki et al. „Premature Ventricular Contraction Originating from Posteroseptum“. Journal of Arrhythmia 27, Supplement (2011): PJ2_081. http://dx.doi.org/10.4020/jhrs.27.pj2_081.

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Dissertationen zum Thema "Premature ventricular contraction"

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Shelly, Iris Lynn. „Algorithm for Premature Ventricular Contraction Detection from a Subcutaneous Electrocardiogram Signal“. PDXScholar, 2016. http://pdxscholar.library.pdx.edu/open_access_etds/3313.

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Cardiac arrhythmias occur when the normal pattern of electrical signals in the heart breaks down. A premature ventricular contraction (PVC) is a common type of arrhythmia that occurs when a heartbeat originates from an ectopic focus within the ventricles rather than from the sinus node in the right atrium. This and other arrhythmias are often diagnosed with the help of an electrocardiogram, or ECG, which records the electrical activity of the heart using electrodes placed on the skin. In an ECG signal, a PVC is characterized by both timing and morphological differences from a normal sinus beat. An implantable cardiac monitor (ICM) is a device used to help physicians diagnose and monitor infrequent cardiac arrhythmias that may not be observed during an ECG recording performed during a normal clinic visit. These devices are implanted under the skin of the chest and simply monitor and record the electrical activity of the heart. The recorded signal is referred to as a subcutaneous electrocardiogram, or SECG. This thesis proposes and tests a novel algorithm that uses an SECG signal to perform PVC detection and is suitable for implementation within an implantable cardiac monitoring device. The proposed algorithm uses a combination of morphological and timing criteria to identify PVCs in near real time. Current commercially-available ICMs do not provide a PVC detection feature, so the proposed algorithm could help provide physicians with valuable additional diagnostic information about a clinically-significant arrhythmia.
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Imramovská, Klára. „Detekce komorových extrasystol v EKG“. Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442489.

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The thesis deals with problems of automatic detection of premature ventricular contractions in ECG records. One detection method which uses a convolutional neural network and LSTM units is implemented in the Python language. Cardiac cycles extracted from one-lead ECG were used for detection. F1 score for binary classification (PVC and normal beat) on the test dataset reached 96,41 % and 81,76 % for three-class classification (PVC, normal beat and other arrhythmias). Lastly, the accuracy of the classification is evaluated and discussed, the achieved results for binary classification are comparable to the results of methods described in different papers.
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Tzeng, De Jeng, und 曾德正. „An FPGA Sensor Platform for Heart Rate and Ventricular Premature Contraction Detection“. Thesis, 2009. http://ndltd.ncl.edu.tw/handle/47769116633319316409.

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碩士
長庚大學
電機工程學研究所
97
This research implemented an System on chip (S.O.C) biomedical information platform base on Xilinx Field-Programmable Gate Array (FPGA).This platform has been use for an IP which detect whether Ventricular Premature Contraction (VPC) happened or not. Base on Power PC 405, this system include of ADC for data acquisitions, codec for AC97 signal source , CF (compact flash) card for data storage and General purpose I/O. After data acquisition, data could storage in CF card, transfer to PC or analyzed in some user defined algorithm IP. Power PC and bus operate on same rate 100 Mhz for power consideration. This system has great expandable space . Whether PLB or OPB, user can insert more user defined devices or algorithms for this platform if hardware resource allow. In software, Consider it used of scheduled lightly. This platform used stand alone OS. For analyzing feasibility of platform. We implemented a VPC detection IP. This IP is to combine Phase-Space[1] algorithm and Pan-Tompkins[2] algorithm to analysis data. Then analysis data’s characteristics to detect whether VPC or not.
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Chen, Kuan-Yi, und 陳冠伊. „A Premature Ventricular Contraction (PVC) Detection Scheme Based on Heart Rate Variability (HRV) Statistics“. Thesis, 2012. http://ndltd.ncl.edu.tw/handle/54808895333661762857.

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碩士
國立中正大學
通訊工程研究所
100
With the rapid development of science and technology, people get more pressure from their daily lives. An important sign of being unhealthy is having heart arrhythmia. Diagnosis for the arrhythmia is important technique to saving people's life. In particular, people's heart beats are affected by autonomic nervous system and physiological hormone. The Heart Rate Variability (HRV) is used to measure the changes of the heart beat rates, and we can study the strength of autonomic nervous system by analyzing it. The database of arrhythmia used in this thesis is from MIT-BIH. We also applied the Cubic Spline interpolation to derive the HRV parameters. The Statistical Product and Service Solutions (SPSS) is used to analyze the relation between parameters of HRV and a typical arrhythmia called Premature Ventricular Contraction (PVC). Results showed that the very low frequency power (VLFP), low frequency power(LFP), high frequency power(HFP) in HRV can be used to determine the PVC arrhythmia.
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Chen, Shiue Ru, und 陳學儒. „A High-Precision Real-Time Premature Ventricular Contraction (PVC) Detection System Based on Wavelet Transform“. Thesis, 2011. http://ndltd.ncl.edu.tw/handle/ke94a2.

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碩士
國立中興大學
電機工程學系所
99
In Taiwan, heart disease has been in the top ten causes of death for a long time, and even at the second place in recent years, Thus the diagnosis of heart disease and how to prevent it is particularly important.Currently, Electrocardiogram (ECG) is the most reliable way to determine heart activity by record relevant electrical signal, which can be drawn on electrocardiogram paper to produce ECG. Doctor can diagnose whether there is abnormal, and further assess or treat.A lot of heart diseases occur in a moment or a very short time, and it will cause the patients to feel uncomfortable and then to go to the hospital to do ECG examination, but can not check out the reason so that the doctors can not assess and treat. Therefore, a high-precision real-time detection system is urgently needed to prevent the above situation.The focus of this thesis is to propose a high-precision real-time Premature Ventricular Contraction (PVC) detection system. We will use wavelet transform to detect R wave peaks and propose a new PVC detection algorithms that combines two methods to detect and determine whether the occurrence of PVC. The first method is the sum of trough and the second one is the sum of R_peak and minimum. If the morbid state happens, a warning message will be sent to the user.We simulate and verify the proposed system by using MIT-BIH Arrhythmia Database (mitdb). Finally, our system is implemented by FPGA.
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Buchteile zum Thema "Premature ventricular contraction"

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Enriquez, Andres, und Fermin Garcia. „Idiopathic Premature Ventricular Contraction Ablation“. In Cardiac Electrophysiology, 373–74. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-28533-3_90.

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Cowan, Mitchell A., und Karin Chia. „Right Ventricular Outflow Tract Premature Ventricular Contraction Mapping“. In Cardiac Electrophysiology, 369–71. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-28533-3_89.

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Saenz, Luis, Carlos Tapias und Fermin Garcia. „Premature Ventricular Contraction from the Left Ventricular Summit“. In Cardiac Electrophysiology, 389–93. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-28533-3_94.

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Tapias, Carlos, Fermin Garcia und Luis Saenz. „Premature Ventricular Contraction Arising from the Left Ventricular Summit“. In Cardiac Electrophysiology, 375–78. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-28533-3_91.

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Chen, Hao, Jiaqi Bai, Luning Mao, Jieying Wei, Jiangling Song und Rui Zhang. „Automatic Identification of Premature Ventricular Contraction Using ECGs“. In Health Information Science, 143–55. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32962-4_14.

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Saenz, Luis. „Premature Ventricular Contraction from Right-Left Coronary Cusp Commissure“. In Cardiac Electrophysiology, 401–4. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-28533-3_97.

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Dohnálek, Pavel, Petr Gajdoš, Tomáš Peterek und Lukáš Zaorálek. „Orthogonal Matching Pursuit Based Classifier for Premature Ventricular Contraction Detection“. In Advances in Intelligent Systems and Computing, 201–10. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-01854-6_21.

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Theera-Umpon, Nipon, Panyaphon Phiphatkhunarnon und Sansanee Auephanwiriyakul. „Linear Prediction-Based Reconstruction of Electrocardiogram with Premature Ventricular Contraction for Heart Rate Variability Analysis“. In Lecture Notes in Electrical Engineering, 273–81. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6516-0_30.

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Braun-Falco, Markus, Henry J. Mankin, Sharon L. Wenger, Markus Braun-Falco, Stephan DiSean Kendall, Gerard C. Blobe, Christoph K. Weber et al. „Premature Ventricular Contractions“. In Encyclopedia of Molecular Mechanisms of Disease, 1717. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-29676-8_8472.

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Burkhardt, J. David. „Papillary Premature Ventricular Contractions“. In Cardiac Electrophysiology, 367–68. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-28533-3_88.

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Konferenzberichte zum Thema "Premature ventricular contraction"

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Ribeiro, B. R., J. H. Henirques, A. M. Marques und M. A. Antunes. „Manifold learning for premature ventricular contraction detection“. In 2008 35th Annual Computers in Cardiology Conference. IEEE, 2008. http://dx.doi.org/10.1109/cic.2008.4749192.

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Solosenko, Andrius, und Vaidotas Marozas. „Automatic Premature Ventricular Contraction detection in photoplethysmographic signals“. In 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS). IEEE, 2014. http://dx.doi.org/10.1109/biocas.2014.6981642.

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Adnane, Mourad, und Adel Belouchrani. „Premature ventricular contraction arrhythmia detection using wavelet coefficients“. In 2013 8th InternationalWorkshop on Systems, Signal Processing and their Applications (WoSSPA). IEEE, 2013. http://dx.doi.org/10.1109/wosspa.2013.6602356.

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De Marco, Fabiola, Dewar Finlay und Raymond Bond. „Classification of Premature Ventricular Contraction Using Deep Learning“. In 2020 Computing in Cardiology Conference. Computing in Cardiology, 2020. http://dx.doi.org/10.22489/cinc.2020.311.

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Jun, Tae Joon, Hyun Ji Park, Nguyen Hoang Minh, Daeyoung Kim und Young-Hak Kim. „Premature Ventricular Contraction Beat Detection with Deep Neural Networks“. In 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, 2016. http://dx.doi.org/10.1109/icmla.2016.0154.

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Ittatirut, Supat, Apiwat Lek-uthai und Arporn Teeramongkonrasmee. „Detection of Premature Ventricular Contraction for real-time applications“. In 2013 10th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON 2013). IEEE, 2013. http://dx.doi.org/10.1109/ecticon.2013.6559531.

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Kobayashi, K., und Y. Uchikawa. „Frequency analysis of premature ventricular contraction using 3D MCG measurements“. In IEEE International Magnetics Conference. IEEE, 1999. http://dx.doi.org/10.1109/intmag.1999.837330.

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Lek-uthai, Apiwat, Supat Ittatirut und Arporn Teeramongkonrasmee. „Algorithm development for real-time detection of premature ventricular contraction“. In TENCON 2014 - 2014 IEEE Region 10 Conference. IEEE, 2014. http://dx.doi.org/10.1109/tencon.2014.7022418.

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Kaya, Yasin, und Huseyin Pehlivan. „Feature selection using genetic algorithms for premature ventricular contraction classification“. In 2015 9th International Conference on Electrical and Electronics Engineering (ELECO). IEEE, 2015. http://dx.doi.org/10.1109/eleco.2015.7394628.

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Akin, Zahide Elif, und Suleyman Bilgin. „Classification of normal beat, atrial premature contraction and ventricular premature contraction based on discrete wavelet transform and artificial neural networks“. In 2017 Medical Technologies National Congress (TIPTEKNO). IEEE, 2017. http://dx.doi.org/10.1109/tiptekno.2017.8238027.

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Berichte der Organisationen zum Thema "Premature ventricular contraction"

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Shelly, Iris. Algorithm for Premature Ventricular Contraction Detection from a Subcutaneous Electrocardiogram Signal. Portland State University Library, Januar 2000. http://dx.doi.org/10.15760/etd.3293.

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Li, Yezi, Haibin Zhao, Tianyuan Jiang, Zihao Ren und Hongyan Jiang. Efficacy and safety of yiqi yangyin therapy for premature ventricular contractions: A systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, Januar 2021. http://dx.doi.org/10.37766/inplasy2021.1.0007.

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