Academic literature on the topic 'Extrasystolie'

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Journal articles on the topic "Extrasystolie"

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Enevoldsen, Johannes, Cristhian Potes, Minnan Xu-Wilson, and Simon T. Vistisen. "Prevalence and Temporal Distribution of Extrasystoles in Septic ICU Patients: The Feasibility of Predicting Fluid Responsiveness Using Extrasystoles." Critical Care Research and Practice 2018 (October 1, 2018): 1–8. http://dx.doi.org/10.1155/2018/5697092.

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Background. Extrasystoles may be useful for predicting the response to fluid therapy in hemodynamically unstable patients but their prevalence is unknown. The aim of this study was to estimate the availability of extrasystoles in intensive care unit patients diagnosed with sepsis. The study aim was not to validate the fluid responsiveness prediction ability of extrasystoles. Methods. Twenty-four-hour ECG recordings from a convenience sample of 50 patients diagnosed with sepsis were extracted from the MIMIC-II waveform database, and ECGs were visually examined for correct QRS complex detection.
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Albinni, S., D. Luckner, and M. Marx. "Die Extrasystolie." Kinder- und Jugendmedizin 13, no. 01 (2013): 21–27. http://dx.doi.org/10.1055/s-0038-1629316.

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ZusammenfassungExtrasystolen (ES) treten in jedem Lebensalter auf und sind damit ein häufiger Vorstellungsgrund bei Kinderkardiologen. SVES entspringen aus den Vorhöfen oder seltener aus der AV-Knotenregion, sehr frühzeitig einfallende SVES werden entweder blockiert oder sie treffen auf noch teilweise refraktäres Gewebe und werden aberrant und damit schenkelblockartig übergeleitet. VES entspringen zu 2/3 aus dem Ausflusstrakt des rechten (RV) oder linken Ventrikels (LV) und sind dann zumeist monomorph. Können VES aus dem LV spontan weniger werden, trifft dies für VES aus dem RV kaum zu. Eine E
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Geller, J. Christoph. "Ventrikuläre Extrasystolie." DoctorConsult - The Journal. Wissen für Klinik und Praxis 2, no. 2 (2011): e105-e111. http://dx.doi.org/10.1016/j.dcjwkp.2011.07.009.

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Böning, U., S. Brodherr-Heberlein, R. Schreiber, G. Schumacher, and K. Bühlmeyer*. "Extrasystolie im Neugeborenenalter." Geburtshilfe und Frauenheilkunde 45, no. 11 (1985): 803–8. http://dx.doi.org/10.1055/s-2008-1036652.

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Seipel, L., and G. Breithardt. "Diagnostik der ventrikulären Extrasystolie*." DMW - Deutsche Medizinische Wochenschrift 114, no. 40 (2008): 1532–35. http://dx.doi.org/10.1055/s-2008-1066793.

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Seipel, L. "Therapie der ventrikulären Extrasystolie*." DMW - Deutsche Medizinische Wochenschrift 114, no. 41 (2008): 1571–75. http://dx.doi.org/10.1055/s-2007-1024470.

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von Garssen, C., U. Gembruch, D. A. Redel, R. Bald, and M. Hansmann. "Fetale Extrasystolie — Diagnose und Management." Archives of Gynecology and Obstetrics 245, no. 1-4 (1989): 59–60. http://dx.doi.org/10.1007/bf02417169.

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Leschowski, Robert, and Carsten Boltze. "Extrasystolie – mehr als ein Herzstolpern?" retten! 10, no. 03 (2021): 190–98. http://dx.doi.org/10.1055/a-1214-1257.

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Germanova, O. A., V. A. Germanov, Yu V. Shchukin, A. V. Germanov, and M. V. Piskunov. "Extrasystoles: adverse effects of the first postextrasystolic contraction." Bulletin of the Medical Institute "REAVIZ" (REHABILITATION, DOCTOR AND HEALTH), no. 6 (March 31, 2021): 89–97. http://dx.doi.org/10.20340/vmi-rvz.2020.6.11.

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Aim. To determine the changes of parameters of heart biomechanics and kinetics of arteries, to reveal the adverse events of first post-extrasystolic contraction.Materials and methods. In our investigation we included 286 patients. We excluded all the main traditional risk factors of the atherosclerosis. All the patients were branched into two main groups in accordance to the quantity of extrasystoles per 24 hours: I group – less than 3000, II group – more than 3000 extrasystoles per 24 hours. We took the data about complaints, anamnesis, made laboratory and instrumental investigations to revea
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Bossard, Matthias, Michael Kühne, and David Conen. "Der arrhythmische Puls – differentialdiagnostische Überlegungen." Therapeutische Umschau 70, no. 5 (2013): 278–83. http://dx.doi.org/10.1024/0040-5930/a000403.

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Der Zufallsbefund des asymptomatischen arrhythmischen Pulses in der klinischen oder technisch gestützten Untersuchung ist häufig. Die zugrunde liegenden Rhythmusstörungen werden vom Alter, der kardialen Vorgeschichte sowie sonstigen Begleiterkrankungen bestimmt. Vermeintliche benigne Befunde müssen von möglicherweise komplikationsreichen rhythmologischen Pathologien diskriminiert werden. Die primäre Diagnostik stützt sich auf die klinische Untersuchung und auf die elektrokardiographische Dokumentation. Je nach Befund ist eine weiterführende Abklärung mittels Laboranalytik, Langzeit-EKG und kar
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Dissertations / Theses on the topic "Extrasystolie"

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MOYAL, CHARLES. "Extrasystolie ventriculaire complexe : interet de la stimulation electrique." Aix-Marseille 2, 1988. http://www.theses.fr/1988AIX20391.

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Seidel, Tobias Verfasser], and Michael [Akademischer Betreuer] [Böhm. "Wirkung einer sympathischen Nierenarteriendenervation auf Herzfrequenz, Extrasystolie und Herzfrequenzvariabilität bei resistenter arterieller Hypertonie / Tobias Seidel ; Betreuer: Michael Böhm." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2018. http://d-nb.info/1205314261/34.

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Seidel, Tobias [Verfasser], and Michael [Akademischer Betreuer] Böhm. "Wirkung einer sympathischen Nierenarteriendenervation auf Herzfrequenz, Extrasystolie und Herzfrequenzvariabilität bei resistenter arterieller Hypertonie / Tobias Seidel ; Betreuer: Michael Böhm." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2018. http://d-nb.info/1205314261/34.

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Duehmke, Rudolf Martin. "Extrasystolic excitation, conduction and arrhythmogenesis in murine hearts." Thesis, University of Cambridge, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.709513.

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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 compara
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Weber-Guskar, Joachim. "Die heart rate turbulence nach repetitiven Extrasystolen." [S.l.] : [s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=974167177.

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Honoré, Alain. "Les extrasystoles ventriculaires chez le personnel naviguant." Université Claude Bernard - Lyon I, 1994. http://www.theses.fr/1994LYO1M255.

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Svánovská, Zuzana. "Expertní systém pro detekci místa vzniku komorových extrasystol." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-221378.

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Ventricular premature beats are ectopic changes in the ECG signal. Detection of ventricular extrasystoles on 12leads ECG was created in MATLAB. At first my work involves whether the ventricular premature beats comes from the right or the left ventricle. Another algorithm evaluates the incidence outflow tract of the chamber. If the previous algorithm shows signs of indecision, another algorithm is used for detection of ventricular extrasystoles at another location in the left ventricle. The last step is to narrow the area of detection which makes it easier to find the place of origin.
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Veit, Gudrun. "Veränderung der Herzfrequenz nach ventrikulärer Extrasystole eine prospektive Studie bei herzgesunden Probanden /." [S.l.] : [s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=974396990.

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Chase, Katharina [Verfasser]. "Langzeitoutcome von Kindern mit intrauterin diagnostizierten supraventrikulären Extrasystolen / Katharina Chase." Lübeck : Zentrale Hochschulbibliothek Lübeck, 2012. http://d-nb.info/1023624990/34.

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Books on the topic "Extrasystolie"

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El-Kadri, Moutaz, and George Hart. Extrasystoles. Edited by Patrick Davey and David Sprigings. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199568741.003.0110.

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An extrasystole is a cardiac electrical impulse (often premature) which is not part of the normal heart rhythm. Extrasystoles most frequently arise from the ventricles and are then called ventricular extrasystoles, or premature ventricular complexes. Less often, they originate from the atria, the atrioventricular junction or, rarely, from the sinus node—these are termed supraventricular extrasystoles. The term ‘bigeminy’ refers to an extrasystole every second beat, and ‘trigeminy’, every third beat. Two successive extrasystoles are called a ‘couplet’; three are called a ‘triplet’. Extrasystole
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The effects of aerobic exercise conditioning on premature cardiac contractions in unconditioned, healthy men. 1987.

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The effects of aerobic exercise conditioning on premature cardiac contractions in unconditioned, healthy men. 1986.

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Barold, S. Serge. Atrioventricular conduction abnormalities and atrioventricular blocks: ECG patterns and diagnosis. Edited by Giuseppe Boriani. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198784906.003.0453.

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The diagnosis of first-degree and third-degree atrioventricular (AV) block is straightforward but that of second-degree AV block is more involved. Type I block and type II second-degree AV block are electrocardiographic patterns that refer to the behaviour of the PR intervals (in sinus rhythm) in sequences (with at least two consecutive conducted PR intervals) where a single P wave fails to conduct to the ventricles. Type I second-degree AV block describes visible, differing, and generally decremental AV conduction. Type II second-degree AV block describes what appears to be an all-or-none con
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Book chapters on the topic "Extrasystolie"

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Tebbenjohanns, J., and B. Lüderitz. "Extrasystolie." In Kompendium der praktischen Medizin. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-59754-1_9.

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Soliman, Esam. "‘Overslaan’/extrasystolie." In Kleine kwalen in de huisartsenpraktijk. Bohn Stafleu van Loghum, 2018. http://dx.doi.org/10.1007/978-90-368-2251-0_17.

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Soliman, E. "72 ‘Overslaan’/extrasystolie." In Kleine kwalen in de huisartsenpraktijk. Bohn Stafleu van Loghum, 2016. http://dx.doi.org/10.1007/978-90-368-1386-0_72.

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von Garssen, C., U. Gembruch, D. A. Redel, R. Bald, and M. Hansmann. "Fetale Extrasystolie — Diagnose und Management." In Gynäkologie und Geburtshilfe 1988. Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-74784-7_23.

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Sesto, Fred. "Welches sind die Parameter zur Differentialdiagnose zwischen einer aberrierenden Leitung und einer ventrikulären Extrasystolie?" In Arrhythmie-Kompendium IV. Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-93378-3_40.

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Inai, Kei, Alexander K. C. Leung, Jouni Uitto, et al. "Extrasystoles." In Encyclopedia of Molecular Mechanisms of Disease. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-29676-8_597.

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Jelliffe, Roger W. "Extrasystoles." In Fundamentals of Electrocardiography. Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4613-8972-9_5.

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de Jongh, T. O. H., and H. C. P. M. van Weert. "Overslaan van het hart (extrasystole)." In Therapie van alledaagse klachten. Bohn Stafleu van Loghum, 2017. http://dx.doi.org/10.1007/978-90-368-1922-0_20.

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Solosenko, A., and V. Marozas. "Automatic Extrasystole Detection Using Photoplethysmographic Signals." In IFMBE Proceedings. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-00846-2_244.

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Abedin, Zainul, and Robert Conner. "Concealed Conduction and Concealed Extrasystoles." In Developments in Cardiovascular Medicine. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4607-8_14.

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Conference papers on the topic "Extrasystolie"

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Anisimov, Aleksei, Zafar Yuldashev, Anastasiya Sutyagina, and Ekaterina Lyakhova. "Extrasystole Episodes Detection Algorithm in Real Time Mode." In 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT). IEEE, 2019. http://dx.doi.org/10.1109/usbereit.2019.8736612.

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Batchvarov, V. N., I. I. Christov, G. Bortolan, I. I. Simova, and A. J. Camm. "Post-extrasystolic changes of the vectorcardiographic T loop in healthy subjects." In 2007 34th Annual Computers in Cardiology Conference. IEEE, 2007. http://dx.doi.org/10.1109/cic.2007.4745519.

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Telksnys, Laimutis, and Jonas Kaukenas. "Accuracy estimation of detection of extrasystoles in heart rate sequences." In 2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom 2012). IEEE, 2012. http://dx.doi.org/10.1109/healthcom.2012.6379377.

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Coskun, Huseyin, Tuncay Yigit, and Omer Deperlioglu. "Effect of filter selection on classification of extrasystole heart sounds via mobile devices." In 2016 IEEE 10th International Conference on Application of Information and Communication Technologies (AICT). IEEE, 2016. http://dx.doi.org/10.1109/icaict.2016.7991820.

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Coskun, Huseyin, Omer Deperlioglu, and Tuncay Yigit. "Classification of extrasystole heart sounds with MFCC features by using Artificial Neural Network." In 2017 25th Signal Processing and Communications Applications Conference (SIU). IEEE, 2017. http://dx.doi.org/10.1109/siu.2017.7960252.

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Coskun, Huseyin, Omer Deperlioglu, and Tuncay Yigit. "Implementation of wavelet transform extrasystole heart sound with convolution method for feature extraction." In 2017 25th Signal Processing and Communications Applications Conference (SIU). IEEE, 2017. http://dx.doi.org/10.1109/siu.2017.7960300.

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Abubakar, Mohammed Mansur, and Taner Tuncer. "Heart Sounds Classification Using Hybrid CNN Architecture." In International Students Science Congress. Izmir International Guest Student Association, 2021. http://dx.doi.org/10.52460/issc.2021.023.

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In this paper, we propose a hybrid model for diagnosing heart conditions by analyzing heart sounds and signals. The Hybrid CNN (Convolutional Neural Network) model is trained to classify distinguishable pathological heart sounds into three classes; normal, murmur, and extrasystole. Scalogram images of heart sounds were obtained by applying wavelet transform to heart sound signals. Images are inputs for Resnet50 and Resnet101 CNN models. The feature vectors of these architectures in the fc1000 layer are combined. Relief feature selection algorithm was applied to the obtained feature vector, and
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NODA, TAKASHI, WATARU SHIMIZU, ATSUSHI TAGUCHI, et al. "IDIOPATHIC VENTRICULAR FIBRILLATION INITIATED BY PREMATURE EXTRASYSTOLES ORIGINATING FROM RIGHT VENTRICULAR OUTFLOW TRACT." In Proceedings of the 31st International Congress on Electrocardiology. WORLD SCIENTIFIC, 2005. http://dx.doi.org/10.1142/9789812702234_0125.

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Yazawa, Toru. "Everyday Life Quantification Using mDFA: Heart Health Monitoring and Structural Health Monitoring." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-48018.

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The aim of this study was to make a method usable in an early detection of malfunction, e.g., abnormal vibration/fluctuation in recorded signals. We conducted experimentations of heart health and structural health monitoring. We collected natural world signals, e.g., heartbeat fluctuation and mechanical vibration. For the analysis, we used modified detrended fluctuation analysis (mDFA) method that we have made recently. mDFA calculated the scaling exponent (SI, the acronym SI is derived from the scaling indices) from the time series data, e.g., R-R interval time series obtained from electrocar
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