Cervical auscultation is the recording of sounds and vibrations caused by the human body from the throat during swallowing. While traditionally done by a trained clinician with a stethoscope, much work has been put toward developing more sensitive and clinically useful methods to characterize the data obtained with this technique. The eventual goal of the field is to improve the effectiveness of screening algorithms designed to predict the risk that swallowing disorders pose to individual patients' health and safety. This paper provides an overview of these signal-processing techniques and summarizes recent advances made with digital transducers in hopes of organizing the highly varied research on cervical auscultation. It investigates where on the body these transducers are placed in order to record a signal as well as the collection of analog and digital filtering techniques used to further improve the signal quality. It also presents the wide array of methods and features used to characterize these signals, ranging from simply counting the number of swallows that occur over a period of time to calculating various descriptive features in the time, frequency, and phase space domains. Finally, this paper presents the algorithms that have been used to classify these data into “normal” and “abnormal” categories. Both linear as well as nonlinear techniques are presented in this regard.

中文翻译：

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吞咽困难筛查：颈部听诊信号和现代信号处理技术的贡献


颈部听诊是记录人体吞咽时从喉咙发出的声音和振动。虽然传统上是由训练有素的临床医生用听诊器完成的，但人们已经投入了大量的工作来开发更灵敏和临床有用的方法来表征通过该技术获得的数据。该领域的最终目标是提高筛查算法的有效性，该算法旨在预测吞咽障碍对个体患者健康和安全造成的风险。本文概述了这些信号处理技术，并总结了数字传感器的最新进展，希望能够组织有关颈部听诊的高度多样化的研究。它研究这些传感器放置在身体上的哪个位置以记录信号，以及收集用于进一步提高信号质量的模拟和数字滤波技术。它还介绍了用于表征这些信号的各种方法和特征，从简单地计算一段时间内发生的吞咽次数到计算时间、频率和相空间域中的各种描述性特征。最后，本文介绍了用于将这些数据分类为“正常”和“异常”类别的算法。在这方面，提出了线性和非线性技术。