Jader Giraldo-Guzmán, S. H. Contreras-Ortiz, M. Kotas, F. Castells, Tomasz Moron
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引用次数: 0
Abstract
Cardiovascular diseases are the main cause of death in the world, according to the World Health Organization. Among them, ischemic heart disease is at the top, followed by a stroke. Several studies have revealed that atrial fibrillation (AF), which is the most common cardiac arrhythmia, increases up to five fold the overall risk of stroke. As AF can be asymptomatic, approximately 20% of the AF cases remain undiagnosed. AF can be detected by analyzing electrocardiography records. Many studies have been conducted to develop automatic methods for AF detection. This paper reviews some of the most relevant methods, classified into three groups: analysis of heart rate variability, analysis of the atrial activity, and hybrid methods. Their benefits and limitations are analyzed and compared, and our beliefs about where AF automatic detection research could be addressed are presented to improve its effectiveness and performance.
期刊介绍：
Biomedical engineering has been characterized as the application of concepts drawn from engineering, computing, communications, mathematics, and the physical sciences to scientific and applied problems in the field of medicine and biology. Concepts and methodologies in biomedical engineering extend throughout the medical and biological sciences. This journal attempts to critically review a wide range of research and applied activities in the field. More often than not, topics chosen for inclusion are concerned with research and practice issues of current interest. Experts writing each review bring together current knowledge and historical information that has led to the current state-of-the-art.
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