论文标题
音频和接触麦克风进行咳嗽检测
Audio and Contact Microphones for Cough Detection
论文作者
论文摘要
在评估慢性咳嗽疾病的病理严重程度的框架中，医学文献强调了缺乏允许自动，客观和可靠检测咳嗽事件的工具。本文介绍了一个基于两个麦克风的系统，我们为此目的开发了一个系统。所提出的方法依赖于各种各样的音频描述符，这是一种基于其相互信息的特征选择算法和人工神经网络的使用。首先，研究了与音频信号的补充，可能使用接触麦克风（放置在患者的胸腔或气管上）。这项研究强调，与音频方式相比，该联系麦克风遇到了可靠性问题，几乎没有新的相关信息。其次，将所提出的仅一式音频方法与使用数据库中的四个传感器进行比较，该数据库中的四个传感器经常被咳嗽，并在各种条件下产生。与商业系统相比，提出的方法的平均灵敏度和特异性分别为94.7％和95％，其咳嗽检测性能更好。
In the framework of assessing the pathology severity in chronic cough diseases, medical literature underlines the lack of tools for allowing the automatic, objective and reliable detection of cough events. This paper describes a system based on two microphones which we developed for this purpose. The proposed approach relies on a large variety of audio descriptors, an efficient algorithm of feature selection based on their mutual information and the use of artificial neural networks. First, the possible use of a contact microphone (placed on the patient's thorax or trachea) in complement to the audio signal is investigated. This study underlines that this contact microphone suffers from reliability issues, and conveys little new relevant information compared to the audio modality. Secondly, the proposed audio-only approach is compared to a commercially available system using four sensors on a database with different sound categories often misdetected as coughs, and produced in various conditions. With average sensitivity and specificity of 94.7% and 95% respectively, the proposed method achieves better cough detection performance than the commercial system.
