Name
Abstract | ||
|---|---|---|
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). |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/EMBC44109.2020.9175345 | 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) |
Keywords | DocType | Volume |
Cough,Humans,Pneumonia,Sensitivity and Specificity,Sound,Sputum | Conference | 2020 |
ISSN | ISBN | Citations |
2375-7477 | 978-1-7281-1991-5 | 1 |
PageRank | References | Authors |
0.36 | 4 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ebrahim Nemati | 1 | 84 | 15.30 |
| Md. Mahmudur Rahman | 2 | 17 | 16.00 |
| Viswam Nathan | 3 | 50 | 14.09 |
| Korosh Vatanparvar | 4 | 134 | 16.20 |
| Jilong Kuang | 5 | 38 | 17.00 |