Background and Aim: Cardiac electrophysiology study (EPS) is the study of the electrical system of the heart. One of the most common methods of treating cardiac arrhythmias is ablation. The main problem with this method is determination of the position of the heart that must be be ablated. ELECTROCARDIOGRAM (ECG) signal is used as a non-invasive, safe and fast tool to understand the electrical activity of the heart. The aim of this study was to identify the focal atrial tachycardia ectopic foci based on ECG signal analysis using sparse decomposition algorithm. Materials and Methods: 12-lead ECG signals of 48 patients with focal atrial tachycardia were recorded and stored. After preprocessing the ECG signals, by using Pan-Tompkins algorithm, each pulse of each signal was separated. Sparse coefficients of test data were calculated based on the sparse decomposition algorithm and the test data were classified. 4 anatomical position in the right atrium, one in the septum and 4 anatomical position in the left atrium were considered as 9 classes and the position of the ectopic foci in each test data was determined. Results: At first, the location of the ectopic foci was identified in the right or left atrium, and then the exact anatomical position in each atrium was estimated. The average accuracy of identifying the position of ectopic foci in 5 runs of algorithm was 81. 27±2. 78. The mean accuracy of identification of ectopic foci was 61. 73% in 4 anatomical position of right atrium, 64. 05% in septum and 65. 16% in 4 anatomical position of left atrium. Conclusion: Based on the findings of the study, the location of the ectopic foci of focal atrial tachycardia can be identified with appropriate accuracy using ECG signal analysis before performing electrophysiological study.

Background: Alcohol consumption leads to a significant number of deaths, mostly in men, worldwide. Considering the effect of ethanol toxicity on the heart, we studied various Electrocardiographic (ECG) changes in patients with acute ethanol poisoning. Methods: A cross-sectional study was performed on patients admitted to Khorshid Hospital (affiliated to Isfahan University of Medical Sciences) due to ethanol poisoning. All 15-to 50-year-old patients with acute ethanol intoxication were included in the study (N=250). The patients’ information, including the demographic characteristics, clinical manifestations, and ECG changes were recorded and analyzed. Different variables were compared between the patients with or without ECG changes. Results: Most of the research patients (n=208) were men (83. 82%). The Mean± SD age of the study patients was 26. 8± 8. 87 years. About 54. 8% of the patients presented abnormal ECG. The changes in ECG were not significantly different based on the demographic characteristic and clinical manifestations. The time interval between ethanol consumption and admission was significantly higher in patients with abnormal ECG, compared to those with normal ECG (Mean± SD: 7. 09± 10. 67 vs. 4. 77± 4. 54 hours, respectively) (P=0. 03). Conclusion: ECG changes are common in patients with ethanol poisoning. The time interval between ethanol consumption to hospital admission may be an important factor in the occurrence of ECG changes.

The ELECTROCARDIOGRAM (EKG) is one of the major Para-clinic exams for evaluating patients suspected to cardiac or non-cardiac disease which could be very informative especially when assessed by experienced clinicians. To improve and accelerate the approach to EKG interpretation, simple and accurate criteria are useful and save the physician’s time especially in emergent situations. In this article, we introduce our criteria which determine whether the electrical axis of heart is normal or not and if abnormal, what kind of deviation it has. These criteria say that "if the mean QRS complex in leads I and II are positive, the axis will be accurately in the normal range (-30 to +90); unless, the axis is abnormal necessitating a more complex evaluation". These criteria could simplify the first step of the approach to EKG interpretation especially in emergent situations. They can also be proper substitute for current methods of heart axis determination in clinical practice and for educational goals.

Introduction: Since electrocardiography along with the other diagnostic procedures, is applied in seeking cardiac disease, so perceiving normal and abnormal electrocardiography patterns in newborns, accelerates the diagnosis of these diseases. On the other side some ECG parameters of term and premature newborns, which changes through life span, are different from each other Objective: There was no study done in our center to compare the ELECTROCARDIOGRAM of term and premature neonates; so we decided to compare their EKGs and its differences with other centers in the world.Materials and Methods: During 2002, from 30 term newborns (gestational age of > 38 weeks) and 30 premature (GS< 38 weeks) who were born in hospitals of Shiraz University of medical sciences and age 24-96 ours were chosen. And a complete EKG (12 leads) was conducted on lying position when newborn was calm and alert. All neonates were assessed fully for underlying diseases that could affect their EKG. All EKGS were assessed and compared as regard to heart rate, axis of heart, voltage, P wave duration and R wave in QRS complex. Comparative statistics was done using SPSS soft ware with fisher exact method.Results: QRS axis in full term neonate is shifted to the right and to the left in premature neonates (P<0.05). Duration of P and QRS waves in term is longer than those in premature babies (P<0.05). Voltage of P wave in premature neonates is higher than that in the term babies. We didn't find significant difference between R wave voltages in these two groups. Conclusion: The ELECTROCARDIOGRAM of premature infants is different from the term ones in axis, P voltage and QRS duration. 

In the world of digital communication, authentication is an important concern and the need for a safe and secure system increases the necessity of designing authentication systems. To perform authentication, biometric-based approaches are of great interest due to the property of being alive and resistant to forgery. In this study, an authentication system based on heart signal is designed. Due to the process of receiving heart signals, their data usually has a lot of noise. In order to prepare the data, in the proposed system, the heart signals are first cleaned and then transferred to the frequency domain for feature extraction. Also, they are converted into an image by applying the Wigner-Ville distribution, so that each image contains the signal information of each person’s heart and is unique. In the proposed authentication system, these images are used for training and evaluation in a deep convolutional neural network. The output of this system provides the possibility of people’s identification. The data of this study are taken from the NSRDB and MITDB databases, and significant results have been obtained compared to previous studies.

Background: An ELECTROCARDIOGRAM (ECG) can provide information on subclinical myocardial damage. The presence, and more importantly, the quantity of coronary artery calcification (CAC), relates well with the overall severity of the atherosclerotic process. A strong relation has been demonstrated between coronary calcium burden and the incidence of myocardial infarction, a relation independent of age. The aim of this study was to assess the relation of left ventricular hypertrophy (LVH) and ECG abnormalities with CAC. Methods: The study population comprised 566 postmenopausal women selected from a population-based cohort study. Information on LVH and repolarization abnormalities (T-axis and QRS-T angle) was obtained using electrocardiography. Modular ECG Analysis System (MEANS) was used to assess ECG abnormalities. The women underwent a multi detectorrow computed tomography (MDCT) scan (Philips Mx 8000 IDT 16) to assess CAC. The Agatston score was used to quantify CAC; scores greater than zero were considered as the presence of coronary calcium. Logistic regression was used to assess the relation of ECG abnormality with coronary calcification.Results: LVH was found in 2.7% (n = 15) of the women. The prevalence of T-axis abnormality was 6% (n = 34), whereas 8.5% (n = 48) had a QRS-T angle abnormality. CAC was found in 62% of the women. Compared to women with a normal T-axis, women with borderline or abnormal T-axes were 3.8 fold more likely to have CAC (95% CI: 1.4-10.2). Similarly, compared to women with a normal QRS-T angle, in women with borderline or abnormal QRS-T angle, CAC was 2.0 fold more likely to be present (95% CI: 1.0-4.1). Conclusion: Among women with ECG abnormalities reflecting subclinical ischemia, CAC is commonly found and may in part explain the increased coronary heart disease risk associated with these ECG abnormalities.

In present study, the effects of propofol as an intravenous anesthetic drug on the ELECTROCARDIOGRAM of dogs before and during anesthesia were studied. Five healthy adult dogs were induced with propofol (8 mg/kg IV) and maintained under anesthesia with continuous infusion of the same drug (04 mg/kg/min IV) for 60 minutes. An ELECTROCARDIOGRAM (lead II) was obtained before induction (time 0), and at 5, 10, 15, 30, 45 and 60 minutes after initiation of the anesthesia. Data was analyzed by using the analysis of repeated measures design. No significant changes were observed in heart rate during anesthesia (P>0.05). The P duration was increased during 0 to 15 minutes after anesthesia but it was decreased in 15 to 60 minutes after anesthesia significantly (P<0.05). The P amplitude increased during anesthesia significantly (P<0.05). The T-P interval was decreased during anesthesia significantly (P<0.05). Therefore, propofol may be considered as a safe anesthetic drug which has not any considerable effects on electrical cardiac activity.

Background: ELECTROCARDIOGRAM (ECG) plays a vital role in the analysis of heart activity. It can be used to analyze the different heart diseases and mental stress assessment also. Various noises, such as baseline wandering, muscle artifacts and power line interface disturbs the information within the ECG signal. To acquire correct information from ECG signal, these noises should be removed. Methods: In the proposed work, the improved variational mode decomposition (IVMD) method for the removal of noise in ECG signals is used. In the proposed method, the weighted signal amplitude integrated over the timeframe of the ECG signal varies the window size during decomposition. Raw ECG data are extracted from 10 subjects and ECG data are also taken from the MIT BIH database for the proposed method. Results: The performance comparison of traditional variational mode decomposition (VMD) and the proposed technique is also calculated using mean square error, percentage root mean square difference, signal to noise ratio and correlation coefficient. The extracted highest signal to noise ratio (SNR) value of acquired ECG signals using traditional VMD is 42db whereas highest value of signal to noise ratio (SNR) using improved VMD (IVMD) is 83db. Conclusion: The proposed IVMD technique represented better performance than traditional VMD for denoising of ECG signals.

Background: ELECTROCARDIOGRAM (ECG) is a diagnostic tool that is routinely used noninvasively to assess the electrical and muscular functions of the heart. All nurses should be able to recognize basic ECG rhythms. Objective: This study aimed to determine the ECG knowledge and practice among nurses in university hospitals in North Cyprus. Methods: This descriptive study was conducted on the registered nurses who worked in critical care units, including intensive care unit, coronary care unit, emergency department, recovery department, and cardiology department in two university hospitals (Near East University Hospital and Dr. Suat Gü nsel Hospital). Totally, 72 registered nurses worked in both hospitals 65 one of whom took part in the study voluntarily. The study data were collected using a researcher-made questionnaire. The questionnaire was prepared in Turkish and was used after being reviewed by three specialist nurses and one cardiologist. The questionnaire contained three sections and 15 questions. Results: The majority of the nurses had B. Sc. degrees (93. 8%) and recorded ECGs for patients (89. 2%). The majority of the participants had passed ECG training courses (60. 0%). Considering the nurses’ knowledge of ECG, the total frequency of correct answers was 69%. Considering their practice of ECG interpretations, the total frequency of correct answers was 67%. Cardiology department nurses had the highest percentage of correct answers (P = 0. 002). Indeed, the lowest and highest means of correct answers were observed among the nurses with less than one year and more than six years of work experience, respectively. Conclusion: The study results showed a high level of ECG knowledge and practice among the nurses. The hospital unit and passage of previous ECG training courses played an important role in the nurses’ experience of ECG interpretation. Hence, ECG training courses were effective in improving the nurses’ ECG knowledge.

In this paper, we have exploited the first-order sliding mode control method to track the ECG data of the human heart by three different nonlinear control laws. In order to lessen the intrinsic chattering of the classic sliding mode control system, smooth function approximations of the control input, by means of the hyperbolic tangent and the saturation function, were used. The fast Fourier transform was used to evaluate the average chattering frequency of the control inputs. The synthesized control schemes namely SMC-sign, SMC-tanh, and SMC-sat, were able to track the real-world ECG signal with an average root mean square error of 0. 0306 and a chattering frequency of 92. 7 Hz. The findings show that the sliding mode controllers can be implemented in electronic artificial pacemakers to provide the intended results successfully. Based on today's electronics, the involved frequency range (556. 4 Hz for the worst case) is quite acceptable and practical.