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

Babak Basiri, M. Vali, S. Agah
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引用次数: 2

Abstract

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.
吞咽声分析对胃食管反流患者正常与吞咽困难的分类
近年来,吞咽机制的声学分析受到了相当大的关注,由于有创方法的诸多损伤,因此首选声学分析。本文提出了基于声学的吞咽困难反流患者与正常人的分离方法。在这项工作中,我们使用了22个人的吞咽声(11个正常和11个异常)。用气管上的录音机记录吞咽声信号,去除环境噪声,提取声音的频谱特征。分类是由非线性支持向量机完成的,使用“留一”。实验结果表明,在一组健康和吞咽困难患者中,该系统对吞咽信号的正确率为66.1%,对吞咽信号的正确率为95.7%。实验结果表明,该系统可为临床医生诊断反流患者的吞咽困难提供具体特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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