Relevant bibliographies by topics / Electrocardiogram

Academic literature on the topic 'Electrocardiogram'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 July 2024

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Journal articles on the topic "Electrocardiogram"

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Wei, Ying Chieh, Ying Yu Wei, Shaang Tzuu Wey, and Ling Sheng Jang. "Design of a Programmable ECG Generator Using a Dynamical Model." Applied Mechanics and Materials 311 (February 2013): 485–90. http://dx.doi.org/10.4028/www.scientific.net/amm.311.485.

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This article is to design and develop a programming electrocardiogram (ECG) generator. It can be used to test the efficiency of algorithms and to calibration and maintenance of electrocardiograph equipment. We simplified and modified the three coupled ordinary differential equations of McSharry’s model to single differential equation to generate the synthetic ECG waveforms. This generator can provide the adjusted amplitude, heart rate, QRS-complex slopes, and P- and T-wave position parameters. The system can set the rage of the average gear rate from 20 to 120 beat per minute (BPM) with an adjustable variation of 1 BPM. The parameters of the adjusted synthetic ECG model can be stored in Flash memory of the system through Universal Serial Bus (USB) 2.0 interface. The results were generated four different ECG waveforms for test which are Lead I, Lead II, hyperkalaemia and left bundle branch block. According to the experimental results, the system can not only generate the ECG waveforms of the setting heart rate but also can adjust the different types of ECG waveforms. ECG generator will generate the synthetic electrocardiograms for testing the electrocardiogram analytic algorithms. ECG generator will generate the synthetic electrocardiograms for testing the electrocardiogram analytic algorithms.
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Peshkin, E. A., and A. S. Gulyaeva. "The electrocardiogram of ferrets during early postnatal ontogenesis." International bulletin of Veterinary Medicine, no. 4 (December 30, 2021): 151–56. http://dx.doi.org/10.52419/issn2072-2419.2021.4.151.

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In experimental researches, ferrets are used as model animals – an alternative to larger predators and rodents in studying various pathologies. Ferrets are exotic pets, and the effect of their domestication manifests itself in the development of various cardiovascular diseases. An electrocardiographic study allows to reveal already acquired heart pathologies such as arrhythmias in adult small animals. The most striking physiological adaptation to new living conditions is observed in ferrets in the early postnatal period. Knowledge of characteristics of the ferrets’ electrocardiogram during this period will help to identify congenital cardiac diseases. The aim of the study was to examine electrocardiograms of ferrets at the age of one month and compare the results obtained with adult small animals. Electrocardiograms were recorded in standard bipolar limb leads on a 12-channel computer electrocardiograph in the sternal body position. The analysis of the morphology of the P-wave, QRS complex, and T-wave was carried out, the characteristics of the amplitude indicators and time intervals was presented. It was revealed that the P-wave was predominantly peaked with the highest amplitude in the second lead, the complex of initial ventricular activity was represented by a singlephase R-wave; in some animals, the T-wave was biphasic in leads II and III. A high elevation of the ST segment was recorded on the electrocardiogram of all the small animals. The results obtained showed that significant changes were not observed in the electrocardiogram of one-month-old ferrets in comparison with adult healthy small animals, so their electrocardiogram described can be considered normal for their age.
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Colombo, Jamie N., Ricardo A. Samson, Santiago O. Valdes, Omar Meziab, David Sisk, and Scott E. Klewer. "Decreased false-positive adolescent pre-athletic screening with Seattle Criteria-interpreted electrocardiograms." Cardiology in the Young 27, no. 3 (June 20, 2016): 512–17. http://dx.doi.org/10.1017/s104795111600086x.

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AbstractSudden cardiac arrest is a rare but devastating cause of death in young adults. Electrocardiograms may detect many causes of sudden cardiac arrest, but are not routinely included in pre-athletic screening in the United States of America partly because of high rates of false-positive interpretation. To improve electrocardiogram specificity for identifying cardiac conditions associated with sudden cardiac arrest, an expert panel developed refined criteria known as the Seattle Criteria. Ours is the first study to compare standard electrocardiogram criteria with Seattle Criteria in 11- to 13-year-olds. In total, 1424 students completed the pre-athletic screening and electrocardiogram; those with a positive screen or abnormal electrocardiogram interpreted by a paediatric electrophysiologist completed further work-up. Electrocardiograms referred for additional evaluation were re-interpreted by a paediatric electrophysiologist using Seattle Criteria. Electrocardiogram abnormalities were identified in 98 (6.9%); Seattle Criteria identified 28 (2.0%). Formal evaluation confirmed four students at risk for sudden cardiac arrest (0.3%): long QT syndrome (n=2), Wolff–Parkinson–White (n=1), and pulmonary hypertension (n=1). All students with at-risk phenotypes for sudden cardiac arrest were identified by both standard electrophysiologist and Seattle Criteria. The false-positive interpretation rate decreased from 6.6 to 1.7% with Seattle Criteria. Downstream costs associated with screening using standard paediatric electrocardiogram interpretations and Seattle Criteria were projected at $24 versus $7, respectively. In conclusion, using Seattle Criteria for electrocardiogram interpretation decreases the rate of false-positive results compared with standard interpretation without omitting true-positive electrocardiogram findings. This may decrease unnecessary referrals and costs associated with formal cardiology evaluation.
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Oslopov, V. N., A. R. Sadykova, and T. S. Fedoseeva. "Limitations of automated computer electrocardiogram analysis." Kazan medical journal 93, no. 4 (August 15, 2012): 687–91. http://dx.doi.org/10.17816/kmj1574.

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Aim. To draw the attention of physicians to the need for careful analysis of electrocardiograms, especially those obtained by using an automatic analyzer, with the obligatory account of the clinical picture of the disease. Methods. Normal electrocardiography, electrocardiography with the usage of a diagnostic system «Valenta», echocardiography, clinical examination of a patient with fibrosing alveolitis. Results. In the patient with fibrosing alveolitis the automatic analyzer of electrocardiograms «Valenta» misinterpreted the 3S-type of the electrocardiogram as a left anterior fascicular bundle branch block, and the doctor-functionalist did not notice the error. Taking into account the clinical picture of disease and monitoring of the dynamics of electrocardiogram the misinterpretation error was corrected. Presented were the arguments for understanding the pathogenesis of changes in the electrocardiogram in a patient with progressive Hamman-Rich disease. Conclusion. Diagnostic algorithms for automated interpretation of the electrocardiogram have limitations in terms of universal recognition of heart disease; the electrocardiogram report, even in the presence of the auto-interpretation, must be a formulated by a physician taking into account both the clinical picture of the disease as well as other diagnostic methods of patient examination.
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Wei, Yanli, Ying Zhu, Xin Wen, Qing Rui, and Wei Hu. "Intracavitary Electrocardiogram Guidance Aids Excavation of Rhythm Abnormalities in Patients with Occult Heart Disease." Journal of Healthcare Engineering 2021 (October 15, 2021): 1–11. http://dx.doi.org/10.1155/2021/2230383.

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In this paper, the analysis of intracavitary electrocardiograms is used to guide the mining of abnormal cardiac rhythms in patients with hidden heart disease, and the algorithm is improved to address the data imbalance problem existing in the abnormal electrocardiogram signals, and a weight-based automatic classification algorithm for deep convolutional neural network electrocardiogram signals is proposed. By preprocessing the electrocardiogram data from the MIT-BIH arrhythmia database, the experimental dataset training algorithm model is obtained, and the algorithm model is migrated into the project. In terms of system design and implementation, by comparing the advantages and disadvantages of the electrocardiogram monitoring system platform, the overall design of the system was carried out in terms of functional and performance requirements according to the system realization goal, and a mobile platform system capable of classifying common abnormal electrocardiogram signals was developed. The system is capable of long-term monitoring and can invoke the automatic classification algorithm model of electrocardiogram signals for analysis. In this paper, the functional logic test and performance test were conducted on the main functional modules of the system. The test results show that the system can run stably and monitor electrocardiogram signals for a long time and can correctly call the deep convolutional neural network-based automatic electrocardiogram signal classification algorithm to analyze the electrocardiogram signals and achieve the requirements of displaying the electrocardiogram signal waveform, analyzing the heartbeat type, and calculating the average heart rate, which achieves the goal of real-time continuous monitoring and analysis of the electrocardiogram signals.
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Popov, A. O., O. YE Kirkach, and T. R. Montrin. "Application of wavelet analysis in the detection of R-teeth electrocardiograms to assess heart rate variability." Electronics and Communications 15, no. 5 (March 29, 2010): 132–36. http://dx.doi.org/10.20535/2312-1807.2010.58.5.285102.

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This work considers preliminary processing of electrocardiography signals for heart rate variability analysis. The main attention is paid to the methods of R-peaks’ time-localization in electrocardiogram. The method of R-peaks’ search based on wavelet transform of the electrocardiogram is proposed. As a result of using this method 98% of R-peaks in the real electrocardiograms were detected correctly
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Skuratova, N. A. "REPOLARIZATION DISORDERS ON ELECTROCARDIOGRAM IN ADOLESCENTS." Health and Ecology Issues, no. 3 (September 28, 2017): 90–96. http://dx.doi.org/10.51523/2708-6011.2017-14-3-20.

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Objective: to demonstrate clinical cases using fragments of electrocardiograms in adolescents with repolarization disorders on the electrocardiogram. Material and methods. Clinical cases and fragments of ECG of children with repolarization disorders on the electrocardiogram have been presented. Results. Various functional tests make it possible to get important information for the differential diagnosis between the norm and pathology. Conclusion. Repolarization disorders in adolescents may be due to a number of reasons, so in-depth cardiac examination may be needed.
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Arunamata, Alisa A., Charles T. Nguyen, Scott R. Ceresnak, Anne M. Dubin, Inger L. Olson, Daniel J. Murphy, and Elif S. Selamet Tierney. "Utility of serial 12-lead electrocardiograms in children with Marfan syndrome." Cardiology in the Young 28, no. 8 (July 4, 2018): 1009–13. http://dx.doi.org/10.1017/s1047951118000707.

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AbstractObjectivesThe goal of this study was to assess the utility of serial electrocardiograms in routine follow-up of paediatric Marfan patients.MethodsChildren ⩽18 years who met the revised Ghent criteria for Marfan syndrome and received a 12-lead electrocardiogram and echocardiogram within a 3-month period were included. Controls were matched by age, body surface area, gender, race, and ethnicity, and consisted of patients assessed in clinic with a normal cardiac evaluation. Demographic, clinical, echocardiographic, and electrocardiographic data were collected.ResultsA total of 45 Marfan patients (10.8 [2.4–17.1] years) and 37 controls (12.8 [1.3–17.1] years) were included. Left atrial enlargement and left ventricular hypertrophy were more frequently present on 12-lead electrocardiogram of Marfan patients compared with controls (12 (27%) versus 0 (0%), p<0.001; and 8 (18%) versus 0 (0%), p=0.008, respectively); however, only two patients with left atrial enlargement on 12-lead electrocardiogram were confirmed to have left atrial enlargement by echocardiogram, and one patient had mild left ventricular hypertrophy by echocardiogram, not appreciated on 12-lead electrocardiogram. QTc interval was longer in Marfan patients compared with controls (427±16 versus 417±22 ms, p=0.03), with four Marfan patients demonstrating borderline prolonged QTc intervals for gender.ConclusionsWhile Marfan patients exhibited a higher frequency of left atrial enlargement and left ventricular hypertrophy on 12-lead electrocardiograms compared with controls, these findings were not supported by echocardiography. Serial 12-lead electrocardiograms in routine follow-up of asymptomatic paediatric Marfan patients may be more appropriate for a subgroup of Marfan patients only, specifically those with prolonged QTc interval at their baseline visit.
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Chen, Zongwei, Hong Tan, Xuemei Liu, and Minghua Tang. "Application of 24 h Dynamic Electrocardiography in the Diagnosis of Asymptomatic Myocardial Ischemia with Arrhythmia in Elderly Patients with Coronary Heart Disease." Emergency Medicine International 2022 (November 11, 2022): 1–5. http://dx.doi.org/10.1155/2022/3228023.

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Objective. To investigate the application effect of 24 h dynamic electrocardiogram in the diagnosis of asymptomatic myocardial ischemia with arrhythmia in elderly patients with coronary heart disease. Methods. A total of 206 elderly patients suspected of coronary heart disease (CHD) with asymptomatic myocardial ischemia and arrhythmia were selected as the research subjects. 24 h dynamic electrocardiogram and conventional electrocardiogram examinations were conducted. Coronary angiography was used as the gold standard to observe the performance of the two examination methods in the diagnosis of asymptomatic myocardial ischemia with arrhythmia in elderly patients with CHD. Results. Coronary angiography showed 174 positive cases and 32 negative cases among the 206 patients. The diagnostic results of a conventional electrocardiogram showed 150 positive cases and 20 negative cases. Its sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 86.21%, 62.50%, 82.52%, 92.59%, and 45.45%, respectively. The diagnostic results of 24 h dynamic electrocardiograms showed 168 positive cases and 29 negative cases. Its sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 96.55%, 96.63%, 95.63%, 98.25%, and 82.86%, respectively. The above results indicated that 24 h dynamic electrocardiogram was significantly better ( P < 0.05 ). The detection rate of arrhythmia types by 24-hour dynamic electrocardiogram was significantly higher than that of conventional electrocardiogram ( P < 0.05 ). Conclusion. 24 h dynamic electrocardiogram is helpful for the diagnosis of asymptomatic myocardial ischemia with arrhythmia in elderly patients with CHD and can improve the detection rate, thereby providing a basis for clinical diagnosis and treatment.
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Filatova, Anna Yevhenivna, Anatoliy Ivanovych Povoroznyuk, Bohdan Petrovych Nosachenko, and Mohamad Fahs. "Synthesis of an integral signal for solving the problem of morphological analysis of electrocardiograms." Herald of Advanced Information Technology 5, no. 4 (December 28, 2022): 263–74. http://dx.doi.org/10.15276/hait.05.2022.19.

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This work is devoted to solving the scientific and practical problem of morphological analysis of electrocardiograms based on an integral biomedical signal with locally concentrated features. In modern conditions of introduction of telemedicine in the health care system of Ukraine the creation of cardiological decision support systems based on automatic morphological analysis of electrocardiogram is of particular importance. The authors proposed a method for synthesizing an integral electrocardiogram in the frontal plane from all limb leads, taking into account the lead angle in the hexaxial reference system and the position of the heart’s electrical axis, since integral electrocardiological signals allow to obtain more accurate results compared to conventional electrocardiogram, because they take into account the individual characteristics of patients, a wide variety of electrocardiogram waveforms and complexes, which is associated not only with the presence of pathological processes in the myocardium, but also with the position of the electrical axis of the heart, in particular, the electrocardiogram will not register a low-amplitude P wave in the II department in the case of a horizontal electrical axis, but it will be clearly visible on the integral signal. To implement the method proposed in the article, a program was written in the MATLAB language, , the high speed of computation and good optimization of which allow to obtain results much faster and more accurate than using traditional approaches, and using the MATLAB Runtime library, which does not require licensing and is distributed free of charge, it was possible to provide more economical development, as well as to implement interaction with popular operating systems, which makes it more accessible and versatile. Verification of the results was carried out using a database of electrocardiograms, which were recorded using a transtelephone digital 12-channel electrocardiological complex “Telecard”, which is part of the medical diagnostic complex “TREDEX”. The paper shows that the proposed method for the synthesis of an integral signal with locally concentrated features will improve the quality of morphological analysis of electrocardiograms in cardiological decision support systems.
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Dissertations / Theses on the topic "Electrocardiogram"

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Aston, R., and Jean Croce Hemphill. "The Electrocardiogram." Digital Commons @ East Tennessee State University, 1994. https://dc.etsu.edu/etsu-works/7572.

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Mahrousa, Zakria Zaki. "Computerised electrocardiogram classification." Thesis, Cardiff University, 2004. http://orca.cf.ac.uk/55932/.

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Advances in computing have resulted in many engineering processes being automated. Electrocardiogram (ECG) classification is one such process. The analysis of ECGs can benefit from the wide availability and power of modern computers. This study presents the usage of computer technology in the field of computerised ECG classification. Computerised electrocardiogram classification can help to reduce healthcare costs by enabling suitably equipped general practitioners to refer to hospital only those people with serious heart problems. Computerised ECG classification can also be very useful in shortening hospital waiting lists and saving life by discovering heart diseases early. The thesis investigates the automatic classification of ECGs into different disease categories using Artificial Intelligence (AI) techniques. A comparison of the use of different feature sets and AI classifiers is presented. The feature sets include conventional cardiological features, as well as features taken directly from time domain samples of an ECG. The benchmark AI classifiers tested include those based on neural network, k-Nearest Neighbour and inductive learning techniques. The research proposes two modifications to the learning vector quantisation (LVQ) neural network, namely the All Weights Updating-LVQ (AWU-LVQ) algorithm and the Neighbouring Weights Updating-LVQ (NWU-LVQ) algorithm, yielding an "intelligent" diagnostic heart system with higher accuracy and reduced training time compared to existing AI techniques.
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Marques, Jefferson Luiz Brum. "High-resolution electrocardiogram analysis." Thesis, University of Sheffield, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263558.

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Mihailovici, Manuela. "Statistical analysis of electrocardiogram data." Thesis, McGill University, 1995. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=22860.

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An overview of the statistical procedures used in the analysis of electrocardiogram traces is presented in this thesis.
The purpose of these procedures is twofold: (i) they may suggest underlying mechanisms that influence heart rate (ii) they may be used as a means of classifying one or more patients into disease categories, by using objective criteria rather than the subjective approaches prevalent in current practice.
In an attempt to apply the methods discussed in this thesis, a selected group of patients was analyzed using spectral analysis.
Lack of information and of control of the patients' activities while they were being monitored precluded the possibility of obtaining definitive results.
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Abrishami, Hedayat. "Deep Learning Based Electrocardiogram Delineation." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1563525992210273.

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Jiménez-Pérez, Guillermo. "Deep learning and unsupervised machine learning for the quantification and interpretation of electrocardiographic signals." Doctoral thesis, Universitat Pompeu Fabra, 2022. http://hdl.handle.net/10803/673555.

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Las señales electrocardiográficas, ya sea adquiridas en la piel del paciente (electrocardiogamas de superficie, ECG) o de forma invasiva mediante cateterismo (electrocardiogramas intracavitarios, iECG) ayudan a explorar la condición y función cardíacas del paciente, dada su capacidad para representar la actividad eléctrica del corazón. Sin embargo, la interpretación de las señales de ECG e iECG es una tarea difícil que requiere años de experiencia, con criterios diagnósticos complejos para personal clínico no especialista, que en muchos casos deben ser interpretados durante situaciones de gran estrés o carga de trabajo como en la unidad de cuidados intensivos, o durante procedimientos de ablación por radiofrecuencia (ARF) donde el cardiólogo tiene que interpretar cientos o miles de señales individuales. Desde el punto de vista computacional, el desarrollo de herramientas de alto rendimiento mediante técnicas de análisis basadas en datos adolece de la falta de bases de datos anotadas a gran escala y de la naturaleza de “caja negra” que están asociados con los algoritmos considerados estado del arte en la actualidad. Esta tesis trata sobre el entrenamiento de algoritmos de aprendizaje automático que ayuden al personal clínico en la interpretación automática de ECG e iECG. Esta tesis tiene cuatro contribuciones principales. En primer lugar, se ha desarrollado una herramienta de delineación del ECG para la predicción de los inicios y finales de las principales ondas cardíacas (ondas P, QRS y T) en registros compuestos de cualquier configuración de derivaciones. En segundo lugar, se ha desarrollado un algoritmo de generación de datos sintéticos que es capaz de paliar el impacto del reducido tamaño de las bases de datos existentes para el desarrollo de algoritmos de delineación. En tercer lugar, la metodología de análisis de datos de ECG se aplicó a datos similares, en registros electrocardiográficos intracavitarios, con el mismo objetivo de marcar inicios y finales de activaciones locales y de campo lejano para facilitar la localización de sitios de ablación adecuados en procedimientos de ARF. Para este propósito, el algoritmo de delineación del ECG de superficie desarrollado previamente fue empleado para preprocesar los datos y marcar la detección del complejo QRS. En cuarto y último lugar, el algoritmo de delineación de ECG de superficie fue empleado, junto con un algoritmo de reducción de dimensionalidad, Multiple Kernel Learning, para agregar la información del ECG de 12 derivaciones y lograr la identificación de marcadores que permitan la estratificación del riesgo de muerte súbita cardíaca en pacientes con cardiomiopatía hipertrófica.
Electrocardiographic signals, either acquired on the patient’s skin (surface electrocardiogam, ECG) or invasively through catheterization (intracavitary electrocardiogram, iECG) offer a rich insight into the patient’s cardiac condition and function given their ability to represent the electrical activity of the heart. However, the interpretation of ECG and iECG signals is a complex task that requires years of experience, difficulting the correct diagnosis for non-specialists, during stress-related situations such as in the intensive care unit, or in radiofrequency ablation (RFA) procedures where the physician has to interpret hundreds or thousands of individual signals. From the computational point of view, the development of high-performing pipelines from data analysis suffer from lack of large-scale annotated databases and from the “black-box” nature of state-of-the-art analysis approaches. This thesis attempts at developing machine learning-based algorithms that aid physicians in the task of automatic ECG and iECG interpretation. The contributions of this thesis are fourfold. Firstly, an ECG delineation tool has been developed for the markup of the onsets and offsets of the main cardiac waves (P, QRS and T waves) in recordings comprising any configuration of leads. Secondly, a novel synthetic data augmentation algorithm has been developed for palliating the impact of small-scale datasets in the development of robust delineation algorithms. Thirdly, this methodology was applied to similar data, intracavitary electrocardiographic recordings, with the objective of marking the onsets and offsets of events for facilitating the localization of suitable ablation sites. For this purpose, the ECG delineation algorithm previously developed was employed to pre-process the data and mark the QRS detection fiducials. Finally, the ECG delineation approach was employed alongside a dimensionality reduction algorithm, Multiple Kernel Learning, for aggregating the information of 12-lead ECGs with the objective of developing a pipeline for risk stratification of sudden cardiac death in patients with hypertrophic cardiomyopathy.
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Dong, Cheng. "Electrocardiogram parameter extract and analysis system." Thesis, University of Macau, 2011. http://umaclib3.umac.mo/record=b2549897.

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Crittenden, Mark E. "Real-time intrapartum fetal electrocardiogram analysis." Thesis, University of Nottingham, 1997. http://eprints.nottingham.ac.uk/27969/.

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The research within this thesis concerns the monitoring of the fetus during labour, using the fetal electrocardiogram (FECG). A versatile FECG analysis system was developed for the Microsoft Windows environment, to allow various FECG parameters to be extracted. Algorithms, currently used in other FECG analysis systems, were implemented using Object Oriented Programming, thus allowing new algorithms to be easily added at a later stage. Although these current algorithms have been demonstrated by several authors, it was felt that they had been used with only partial investigation of their limitations, and with failure to fully determine their accuracy in controlled conditions. These factors are fully addressed within this thesis. By developing a FECG simulator, in which heart-rate, morphology, and noise levels could be varied, the ability of the analysis algorithms to extract the parameters, and the accuracy of these parameters under different noise conditions, were thoroughly checked. Both ability and accuracy were shown to be very good in ideal noiseless conditions; but, with the addition of noise, there exists a compromise between parameter accuracy when the morphology is static, and parameter accuracy when the morphology is changing. The accuracies of the most common indices in this field (the Conduction Index, and the T/QRS ratio) were determined for different levels of simulated noise, and their values demonstrated for data previously recorded from the fetal scalp. Errors as large as 0.3 in the CI and 0.05 in the T/QRS suggested that in the clinical environment, an indication of the accuracy of each index ought to be displayed, and this may be estimated from the measured level of noise. Furthermore, this analysis system allows the direct comparison of both indices. Finally, in order to design a more effective front-end filter, it is important to be aware of the frequency content of the underlying FECG. The Integral Pulse Frequency Modulation (IPFM) model, combined with Pulse Amplitude Modulation (PAM), was used to estimate realistic frequency components within the FECG signal. The effects of filtering could then easily be modelled to show the distortion of both the FECG and any parameters taken from it. For a FECG frontend filter, distortion was found to be insignificant provided that, above 1 Hz, both the gain remained constant and there was no phase-distortion.
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Peasgood, William. "Enhancement of the abdominal fetal electrocardiogram." Thesis, University of Nottingham, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.335851.

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Murray, Henry G. "Evaluation of the fetal electrocardiogram (ECG)." Thesis, University of Nottingham, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.297895.

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Books on the topic "Electrocardiogram"

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Rautaharju, Pentti M. The Female Electrocardiogram. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15293-6.

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Rowlands, Derek J. Understanding the electrocardiogram. Manchester: Imperial Chemical Industries, 1987.

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Jackson, Graham. The electrocardiogram: An introduction. London: Education in Practice, 1989.

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Schamroth, Leo. The 12 lead electrocardiogram. Oxford: Blackwell Scientific, 1989.

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Tueller, Steuble Barbara, ed. Electrocardiogram interpretation and emergency intervention. Springhouse, Pa: Springhouse Corp., 1991.

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The electrocardiogram: An illustrated manual. Stuttgart: Thieme, 1988.

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P, Clements Ian, ed. The electrocardiogram in acute myocardial infarction. Armonk, N.Y: Futura Pub. Co., 1998.

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Generation and interpretation of the electrocardiogram. Philadelphia: Lea & Febiger, 1988.

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Kumar, Ashish, Manjeet Kumar, and Rama S. Komaragiri. High Performance and Power Efficient Electrocardiogram Detectors. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-5303-3.

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Araoye, Matthew Akinyemi. The normal electrocardiogram (ECG) in adult Nigerians. [Ilorin, Nigeria: University of Ilorin, 1986.

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Book chapters on the topic "Electrocardiogram"

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Chen, Wenxi. "Electrocardiogram." In Seamless Healthcare Monitoring, 3–44. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69362-0_1.

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Cooley, Laura A., Daniel G. Bausch, Marija Stojkovic, Waldemar Hosch, Thomas Junghanss, Marija Stojkovic, Waldemar Hosch, et al. "Electrocardiogram." In Encyclopedia of Intensive Care Medicine, 825–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-00418-6_200.

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Cannon, Bryan. "Electrocardiogram." In Visual Guide to Neonatal Cardiology, 80–84. Chichester, UK: John Wiley & Sons Ltd, 2018. http://dx.doi.org/10.1002/9781118635520.ch12.

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Pagliaro, Pasquale, Claudia Penna, and Raffaella Rastaldo. "Electrocardiogram." In Basic Cardiovascular Physiology, 181–236. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003337294-10.

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Park, Kwang Suk. "Electrocardiogram." In Humans and Electricity, 149–72. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-20784-6_7.

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Cheung, Yiu-fai. "Electrocardiogram." In Congenital and Paediatric Acquired Heart Disease in Practice, 47–52. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2862-0_5.

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Rodriguez, Alexis P. "The Electrocardiogram." In Cardiology Procedures, 157–62. London: Springer London, 2016. http://dx.doi.org/10.1007/978-1-4471-7290-1_18.

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Abedin, Zainul, and Robert Conner. "The Electrocardiogram." In Developments in Cardiovascular Medicine, 1–10. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4607-8_1.

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Carroll, Douglas. "Electrocardiogram (EKG)." In Encyclopedia of Behavioral Medicine, 740–41. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39903-0_452.

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LaCaille, Lara, Anna Maria Patino-Fernandez, Jane Monaco, Ding Ding, C. Renn Upchurch Sweeney, Colin D. Butler, Colin L. Soskolne, et al. "Electrocardiogram (EKG)." In Encyclopedia of Behavioral Medicine, 665–66. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_452.

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Conference papers on the topic "Electrocardiogram"

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Pardeshi, Prajakta M., and Ganesh Ramachandran. "Electrocardiogram telemetry." In 2011 3rd International Conference on Electronics Computer Technology (ICECT). IEEE, 2011. http://dx.doi.org/10.1109/icectech.2011.5941571.

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Septiyani, Friescha, Nuryani, Anto Satriyo Nugroho, Aida Noor Indrawati, and Trio Pambudi Utomo. "Fetal Electrocardiogram Extraction From Abdominal Electrocardiogram Using Wavelet." In The 2nd International Seminar on Science and Technology (ISSTEC 2019). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/assehr.k.201010.032.

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Zhou, Qunyi. "The Electrocardiogram Classification Research on Electrocardiogram RR Interval Variation." In 2009 Second International Symposium on Computational Intelligence and Design (ISCID 2009). IEEE, 2009. http://dx.doi.org/10.1109/iscid.2009.270.

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Iliev, Ivo Tsvetanov, Serafim Dimitrov Tabakov, and Irena Ilieva Jekova. "Paced electrocardiogram simulation." In 2018 IEEE XXVII International Scientific Conference Electronics (ET). IEEE, 2018. http://dx.doi.org/10.1109/et.2018.8549612.

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Khan, Muhammad Umar, Muhammad Saad, Sumair Aziz, Javeria Mumtaz Ch., Syed Zohaib Hassan Naqvi, and Muhammad Adnan Qasim. "Electrocardiogram based Gender Classification." In 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE). IEEE, 2020. http://dx.doi.org/10.1109/icecce49384.2020.9179305.

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Reddy. "Digital Model For Electrocardiogram." In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1992. http://dx.doi.org/10.1109/iembs.1992.595748.

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Reddy, M. R. S. "Digital model for electrocardiogram." In 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1992. http://dx.doi.org/10.1109/iembs.1992.5761140.

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Bedrossian, Pascal, Frederic Oweijane, Kyo Hyo Kim, and Falih Ahmad. "On Denoising Electrocardiogram Signals." In International Engineering Science Technology Online Conference. CLOUD PUBLICATIONS, 2019. http://dx.doi.org/10.23953/cloud.iestoc.418.

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WEI, DAMING. "TWELVE-LEAD ELECTROCARDIOGRAM TELEMONITORING." In Proceedings of the 31st International Congress on Electrocardiology. WORLD SCIENTIFIC, 2005. http://dx.doi.org/10.1142/9789812702234_0179.

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V, Chithra, RETESH M, KIRAN S, SAKTHI VIGNESH R, Tharun D, and Surya R. "Smart Mobile Electrocardiogram Monitor." In 2023 Intelligent Computing and Control for Engineering and Business Systems (ICCEBS). IEEE, 2023. http://dx.doi.org/10.1109/iccebs58601.2023.10449146.

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Reports on the topic "Electrocardiogram"

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Anant, K. S. Wavelet transform analysis of transient signals: the seismogram and the electrocardiogram. Office of Scientific and Technical Information (OSTI), June 1997. http://dx.doi.org/10.2172/611772.

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

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Clapp, N. E., L. M. Hively, and R. E. Stickney. Heart pathology determination from electrocardiogram signals by application of deterministic chaos mathematics. CRADA final report. Office of Scientific and Technical Information (OSTI), March 1999. http://dx.doi.org/10.2172/325739.

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Weng, JIeqiong, Jingfang Zhang, Ke Xu, Mengfei Yuan, Tingting Yao, Xinyu Wang, and Xiaoxu Shen. Efficacy of Shexiang Baoxin Pills Combined with Statins on Blood Lipid Profile in Patients with Coronary Heart Disease: A systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, September 2022. http://dx.doi.org/10.37766/inplasy2022.9.0100.

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Review question / Objective: P（Population) ：Patients with coronary heart disease; I（Intervention) : Statins treatment in combination with Shexiang Baoxin pill; C（Comparison): Statins alone; O（Outcome）: Improvement of symptoms and blood lipids; S（Study design）：Clinical randomized trials. Eligibility criteria: To be included, trials were required to meet the following criteria: (1) patients were included in the studies according to diagnostic criteria of coronary heart disease established by the WHO, InternationalSociety of Cardiology and Association (ISCA), Internal Medicine, 7th edition ( IM-7th), Practice of InternalMedicine, 14th edition ( PIM-14th), Guidelines for the Diagnosis of Cardiovascular Diseases in InternalMedicine, 3rd edition (GIM-3rd) or conventional diagnostic criteria (CDC) including assessment of anginapectoris and electrocardiogram (ECG) results; (2) the study was conducted as a randomized controlled trial.
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Zhou, Ruhua, Jingjing Xu, Jiaochen Luan, Weiyun Wang, Xinzhi Tang, Yanling Huang, Ziwen Su, Lei Yang, and Zejuan Gu. The Predictive Role of C-Reactive Protein on Sudden Death: A meta-analysis of prospective studies. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2021. http://dx.doi.org/10.37766/inplasy2021.11.0074.

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This study was a diagnostic research, so the content was decomposed according to PIRO : P: Patients diagnosed with sudden death; I: C-reactive protein; R: There is no gold standard for sudden death, and the definition of sudden death varies from literature to literature. The World Health Organization defines sudden death: "Patients who are normally healthy or seemingly healthy die suddenly due to natural diseases in an unexpectedly short period of time." In our study, sudden death is determined by the history, symptoms, physical examination and electrocardiogram results assesed by doctor. If death events were collected from the patients’ medical records, deaths coded using the International Classification of Diseases-9th Revision, codes 410 to 414 for non-SCD and 798.1 for SCD; or the International Classification of Diseases-10th Revision, codes I20 to I25 for non-SCD and I46 for SCD. All deaths registered as sudden deaths were confirmed in interviews with the patient’s physician or family members again. O: sudden death.
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Doerschuk, Peter C., Robert R. Tenney, and Alan S. Willsky. Modeling Electrocardiograms Using Interacting Markov Chains. Fort Belvoir, VA: Defense Technical Information Center, July 1985. http://dx.doi.org/10.21236/ada162758.

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Peidro, Roberto Maximino, Graciela Beatriz Brión, Martín Bruzzese, and Gustavo Castiello. La repolarización temprana en el electrocardiograma del futbolista. Buenos Aires: siicsalud.com, October 2015. http://dx.doi.org/10.21840/siic/148275.

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Tang, Menglin, Wenyi Gan, Lin Hu, and Yulan Luo. Impact of peripherally inserted central venous catheter associated phlebitis in Neonate guided by intracavitary electrocardiogram：A Systematic Review and Meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, August 2022. http://dx.doi.org/10.37766/inplasy2022.8.0012.

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Palomino Potes, Heidys, and Catalina Olaya-López. Rol de enfermería en las alteraciones electrocardiográficas. Ediciones Universidad Cooperativa de Colombia, December 2021. http://dx.doi.org/10.16925/gcgp.39.

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El profesional de enfermería que se desempeña en el ámbito clínico o comunitario se enfrenta diariamente a la atención de personas con múltiples alteraciones en su estado de salud, lo cual requiere acciones complejas de cuidado. En muchas ocasiones, el equipo interdisciplinario de enfermería es el primero en detectar una alteración electrocardiográfica y su actuación puede ser fundamental en la evolución del paciente. El electrocardiograma ECG de 12 derivaciones es una herramienta útil para el diagnóstico de síndromes coronarios agudos y arritmias en el servicio de urgencias. Cada alteración electrocardiográfica supone roles y acciones de cuidado particulares que pueden significar la diferencia entre la vida y la muerte del paciente. La presente nota de clase abordará cuatro unidades cuyos contenidos se relacionan con el rol de enfermería con alteraciones electrocardiográficas, una situación compleja de salud.
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Fontecha Castro, Paola Andrea, and Myriam Leonor Torres Pérez. Puesta en marcha de telemedicina para el aumento de la resolutividad en ocho (8) municipios beneficiarios a partir de una plataforma de telesalud. Universidad Nacional Abierta y a Distancia - UNAD, 2021. http://dx.doi.org/10.22490/ecisa.4761.

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La Universidad Nacional Abierta y a Distancia UNAD dando alcance al proyecto de investigación con impacto social denominado PRISMA de la Escuela de Ciencias de la salud se ha propuesto un plan de penetración territorial que tiene como propósito garantizar el acceso de las instituciones prestadoras de servicios de salud de diferentes departamentos del país a la tecnología necesaria para la prestación de servicios médicos en la modalidad de telemedicina y así mejorar las condiciones de salud. Este documento describe la implementación y prestación de telemedicina en ocho (8) Empresas Sociales de Estado (ESE) de diferentes municipios en Colombia durante el año 2019 a partir de una plataforma de telesalud que permitió la prestación de servicios como consulta médica especializada y exámenes como Electrocardiograma e imágenes diagnósticas de baja complejidad y la capacitación en el uso de tecnologías biomédicas del personal de salud de las instituciones, como estrategia para el aumento de cobertura, oportunidad y resolutividad en la atención en salud.
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