论文标题

事件持续时间对自动喘息分类的影响

Influence of Event Duration on Automatic Wheeze Classification

论文作者

Rocha, Bruno M., Pessoa, Diogo, Marques, Alda, Carvalho, Paulo, Paiva, Rui Pedro

论文摘要

患有呼吸系统疾病的患者通常会表现出不定的呼吸道声音,例如喘息。喘息事件的持续时间可变。在这项工作中,我们研究了事件持续时间对喘息分类的影响,也就是说,非鞭子类的创建如何影响分类器的性能。首先,我们在开放访问呼吸声数据库上评估了几个分类器,最佳的敏感性和特异性值分别为98%和95%。然后,通过更改非旋风类设计中的一个参数,即事件持续时间,最佳分类器仅达到敏感性和特异性值分别为55%和76%。这些结果证明了实验设计对评估喘息分类算法的性能的重要性。

Patients with respiratory conditions typically exhibit adventitious respiratory sounds, such as wheezes. Wheeze events have variable duration. In this work we studied the influence of event duration on wheeze classification, namely how the creation of the non-wheeze class affected the classifiers' performance. First, we evaluated several classifiers on an open access respiratory sound database, with the best one reaching sensitivity and specificity values of 98% and 95%, respectively. Then, by changing one parameter in the design of the non-wheeze class, i.e., event duration, the best classifier only reached sensitivity and specificity values of 55% and 76%, respectively. These results demonstrate the importance of experimental design on the assessment of wheeze classification algorithms' performance.

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