A computer model is presented for simulation of the spread of activation and repolarization in ventricular myocardium. The program calculating the activation sequence is based on an algorithm similar to Huygen's principle of constructing wavefronts. Physiological parameters of the heart, such as areas of early activation on the endocardium, conduction velocity, anisotropy of propagation, duration of action potentials and refractory periods are taken into account. The time-course of ECG and MCG is calculated using the equations of the bidomain model. Simulation of pathologic cases of activation is performed through variation of the physiological heart parameters. The simulations presented here show good agreement of ECG and MCG with measurements in the normal case, the case of bundle branch block and abnormal repolarization. A special feature of the model is the possibility of simulating reentry rhythms following a premature stimulus in ventricular myocardium. Two kinds of reentry are simulated: reentry around an anatomical obstacle and the leading-circle model. The widespread capability for investigating not only ECG but also MCG and various kinds of pathologic activation patterns including reentry rhythms indicates that the model may be useful in studying numerous problems in cardiologic research.
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Background: Foreign body (coins, magnets, button batteries, and metallic foreign bodies) ingestion is common and causes significant morbidity and mortality in children aged six months to three years. Endoscopic removal of swallowed foreign substances is widely accepted, but sedation and general anesthesia may be required to alleviate pain and anxiety during the procedure. Dexmedetomidine is used as a sedative, hypnotic, anxiolytic, and analgesic.
View Article and Find Full Text PDFBioengineering (Basel)
November 2024
Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China.
This review systematically analyzes the latest advancements in preprocessing techniques for Electrocardiography (ECG) and Magnetocardiography (MCG) signals over the past decade. ECG and MCG play crucial roles in cardiovascular disease (CVD) detection, but both are susceptible to noise interference. This paper categorizes and compares different ECG denoising methods based on noise types, such as baseline wander (BW), electromyographic noise (EMG), power line interference (PLI), and composite noise.
View Article and Find Full Text PDFSensors (Basel)
September 2024
Department of Electrical and Computer Engineering, Tennessee Technological University, Cookeville, TN 38505, USA.
Heart diseases remain one of the leading causes of morbidity and mortality worldwide, necessitating innovative diagnostic methods for early detection and intervention. An electrocardiogram (ECG) is a well-known technique for the preliminary diagnosis of heart conditions. However, it can not be used for continuous monitoring due to skin irritation.
View Article and Find Full Text PDFAm Heart J Plus
July 2024
Department for Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité, Campus Benjamin Franklin; Charité Universitätsmedizin Berlin, Germany.
Biomed Phys Eng Express
May 2024
Department of Cardiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Dhanvantri Nagar, Pondicherry-605 006, Puducherry, India.
Cardiac electrical changes associated with ischemic heart disease (IHD) are subtle and could be detected even in rest condition in magnetocardiography (MCG) which measures weak cardiac magnetic fields. Cardiac features that are derived from MCG recorded from multiple locations on the chest of subjects and some conventional time domain indices are widely used in Machine learning (ML) classifiers to objectively distinguish IHD and control subjects. Most of the earlier studies have employed features that are derived from signal-averaged cardiac beats and have ignored inter-beat information.
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