Nemati Ebrahim, Rahman Md Mahbubur, Nathan Viswam, Vatanparvar Korosh, Kuang Jilong
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:208-212. doi: 10.1109/EMBC44109.2020.9175345.
Identifying the presence of sputum in the lung is essential in detection of diseases such as lung infection, pneumonia and cancer. Cough type classification (dry/wet) is an effective way of examining presence of lung sputum. This is traditionally done through physical exam in a clinical visit which is subjective and inaccurate. This work proposes an objective approach relying on the acoustic features of the cough sound. A total number of 5971 coughs (5242 dry and 729 wet) were collected from 131 subjects using Smartphone. The data was reviewed and annotated by a novel multi-layer labeling platform. The annotation kappa inter-rater agreement score is measured to be 0.81 and 0.37 for 1st and 2nd layer respectively. Sensitivity and specificity values of 88% and 86% are measured for classification between wet and dry coughs (highest across the literature).
识别肺部痰液的存在对于检测诸如肺部感染、肺炎和癌症等疾病至关重要。咳嗽类型分类（干咳/湿咳）是检查肺部痰液存在情况的有效方法。传统上这是在临床就诊时通过体格检查来完成的，这种方法主观且不准确。这项工作提出了一种基于咳嗽声音声学特征的客观方法。使用智能手机从131名受试者那里总共收集了5971次咳嗽（5242次干咳和729次湿咳）。数据由一个新型的多层标注平台进行审查和标注。第一层和第二层的标注kappa评分者间一致性分数分别为0.81和0.37。干咳和湿咳分类的灵敏度和特异性值分别为88%和86%（在文献中是最高的）。
