An Objective Measure of Carotid Disease Based on a Multiparameter Approach

Laura Verde, G. Pietro
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Abstract

Atherosclerosis is a multifactorial disease that affects a significant number of people during their lifetime. It is a pathology clinically silent for years that develops with a gradual thickening of the vessel walls and a consecutive formation of plaque. This is the cause of several dangerous conditions such as ischemic stroke, the most common cause of stroke in middle-aged people. To avoid and reduce these events a continuos and meticulous monitoring of patients with any carotid diseases is necessary. This paper presents an objective measure of the progression of a carotid patology. An index capable of distinguishing between the initial state of thickening of the carotid arterial walls and the successive presence of more serious plaque has been defined. The presence of thickening or plaque is estimated by evaluating Heart Rate Variability. This is a non-invasive approach, able to estimate characteristic parameters in an easy and efficient way, constituting an accurate and optimum instrument for a real-time continuous monitoring. Locally Weighted Learning has been used to automatically find a relationship between these parameters and the presence of a disorder, tested on an available dataset.
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基于多参数方法的颈动脉疾病客观测量
动脉粥样硬化是一种影响许多人一生的多因素疾病。它是一种多年的病理临床沉默,随着血管壁逐渐增厚和斑块的连续形成而发展。这是导致缺血性中风等几种危险情况的原因,缺血性中风是中年人中风的最常见原因。为了避免和减少这些事件,有必要对任何颈动脉疾病患者进行持续细致的监测。本文提出了一种客观的测量颈动脉病理进展的方法。已经定义了一个能够区分颈动脉壁增厚的初始状态和更严重斑块的连续存在的指标。通过评估心率变异性来估计增厚或斑块的存在。这是一种无创的方法,能够以简单有效的方式估计特征参数,构成实时连续监测的准确和最佳仪器。局部加权学习已被用于自动找到这些参数与无序存在之间的关系,并在可用的数据集上进行了测试。
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