Name
Title | ||
|---|---|---|
A Novel Method For Automatic Identification Of Respiratory Disease From Acoustic Recordings |
Abstract | ||
|---|---|---|
This paper evaluates the use of breath sound recordings to automatically determine the respiratory health status of a subject. A number of features were investigated and Wilcoxon Rank Sum statistical test was used to determine the significance of the extracted features. The significant features were then passed to a feature selection algorithm based on mutual information, to determine the combination of features that provided minimal redundancy and maximum relevance. The algorithm was tested on a publicly accessible respiratory sounds database. With the testing dataset, the trained classifier achieved accuracy of 87.1%, sensitivity of 86.8% and specificity of 93.6%. These are promising results showing the possibility of determining the presence or absence of respiratory disease using breath sounds recordings. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/EMBC.2019.8857154 | 2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) |
Field | DocType | Volume |
Computer vision,Mel-frequency cepstrum,Respiratory sounds,Pattern recognition,Feature selection,Computer science,Feature extraction,Wilcoxon signed-rank test,Artificial intelligence,Mutual information,Classifier (linguistics),Statistical hypothesis testing | Conference | 2019 |
ISSN | Citations | PageRank |
1557-170X | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuen Hoong Kok | 1 | 0 | 0.34 |
| Syed Anas Imtiaz | 2 | 22 | 6.03 |
| Esther O. Rodríguez-Villegas | 3 | 24 | 7.08 |