A review on intelligent aid diagnosis for dysphagia using swallowing sounds

Dan Li, Junhui Wu, Xiaoyan Jin, Yanyun Li, Beibei Tong, Wen Zeng, Peiyuan Liu, Weixuan Wang, Shaomei Shang
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Abstract

Abstract Dysphagia, a widespread clinical condition in the elderly, can lead to malnutrition, aspiration pneumonia, and even death. Swallowing sounds emanate from vibrations that occur during the contraction of muscles in the mouth, pharynx, and laryngeal; the opening or closure of the glottis and esophageal sphincter; or the movement of food particles through the throat during swallowing. The development of wearable sensors, data science, and machine learning has spurred growing attention to the clinical method of monitoring swallowing sounds for accurate dysphagia diagnosis. This review delves into the acoustic theory foundation and the application of swallowing sound signal analysis methods, elucidating their potential clinical value for dysphagia diagnosis and treatment.
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利用吞咽声进行吞咽困难智能辅助诊断综述
摘要 吞咽困难是老年人的一种常见临床症状,可导致营养不良、吸入性肺炎甚至死亡。吞咽声音来自口腔、咽部和喉部肌肉收缩时产生的振动;声门和食管括约肌的打开或关闭;或吞咽过程中食物颗粒在喉咙中的移动。随着可穿戴传感器、数据科学和机器学习的发展,人们越来越关注通过监测吞咽声来准确诊断吞咽困难的临床方法。本综述将深入探讨吞咽声信号分析方法的声学理论基础和应用,阐明其在吞咽困难诊断和治疗中的潜在临床价值。
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