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Classification of normal and dysphagia in patients with GERD using swallowing sound analysis

机译:吞咽声波分析对GERD患者正常和吞咽困难的分类

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摘要

In recent years, acoustical analysis of the swallowing mechanism has received considerable attention and because of many damages of invasive methods, it is preferred. This paper proposes acoustic-based method to separate dysphagia patients with reflux disorder from normal persons. In this work, we have used swallowing sound of 22 individuals (11 normal and 11 abnormal). Swallowing sound signals were recorded with sound recorder over the trachea and ambient noise was removed and spectral features were extracted from the sounds. Classification is done by non-linear support vector machines, using leave-one-out. According to the experimental results, the system can classify 66.1% of total swallow signals correctly (signal accuracy) and 95.7% of the total subject in a group of healthy and dysphagia patients (subject accuracy). The experimental results show that the proposed system can provide concrete features for clinicians to diagnose dysphagia in reflux patients.
机译:近年来,吞咽机制的声学分析已引起广泛关注,并且由于侵入性方法的许多损害,因此是首选。本文提出了一种基于声学的方法,将吞咽障碍的吞咽困难患者与正常人区分开。在这项工作中,我们使用了22个人的吞咽声(11个人正常和11个人异常)。用声音记录器在气管上记录吞咽的声音信号,并去除环境噪声,并从声音中提取频谱特征。使用留一法,通过非线性支持向量机进行分类。根据实验结果,该系统可以正确地将一组吞咽信号中的66.1%(信号准确性)正确分类,并将一组健康和吞咽困难的患者中95.7%的对象正确分类(受试者准确性)。实验结果表明,该系统可以为临床医生诊断返流性吞咽困难提供具体的功能。

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