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Auswahl der wissenschaftlichen Literatur zum Thema „Premature ventricular contraction“
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Zeitschriftenartikel zum Thema "Premature ventricular contraction"
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.
Der volle Inhalt der QuelleBaranov, 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.
Der volle Inhalt der QuelleSpector, 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.
Der volle Inhalt der QuelleLatchamsetty, 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.
Der volle Inhalt der QuelleCallans, 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.
Der volle Inhalt der QuelleSaurav, 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.
Der volle Inhalt der QuelleLee, 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.
Der volle Inhalt der QuelleCha, 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.
Der volle Inhalt der QuelleHutchinson, 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.
Der volle Inhalt der QuelleKanemori, 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.
Der volle Inhalt der QuelleDissertationen zum Thema "Premature ventricular contraction"
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.
Der volle Inhalt der QuelleImramovská, 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.
Der volle Inhalt der QuelleTzeng, 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.
Der volle Inhalt der Quelle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.
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.
Der volle Inhalt der Quelle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.
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.
Der volle Inhalt der Quelle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.
Buchteile zum Thema "Premature ventricular contraction"
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.
Der volle Inhalt der QuelleCowan, 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.
Der volle Inhalt der QuelleSaenz, 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.
Der volle Inhalt der QuelleTapias, 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.
Der volle Inhalt der QuelleChen, 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.
Der volle Inhalt der QuelleSaenz, 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.
Der volle Inhalt der QuelleDohnálek, 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.
Der volle Inhalt der QuelleTheera-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.
Der volle Inhalt der QuelleBraun-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.
Der volle Inhalt der QuelleBurkhardt, 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.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Premature ventricular contraction"
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.
Der volle Inhalt der QuelleSolosenko, 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.
Der volle Inhalt der QuelleAdnane, 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.
Der volle Inhalt der QuelleDe 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.
Der volle Inhalt der QuelleJun, 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.
Der volle Inhalt der QuelleIttatirut, 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.
Der volle Inhalt der QuelleKobayashi, 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.
Der volle Inhalt der QuelleLek-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.
Der volle Inhalt der QuelleKaya, 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.
Der volle Inhalt der QuelleAkin, 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.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Premature ventricular contraction"
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.
Der volle Inhalt der QuelleLi, 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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