Quintas-2012a
From IEETA
Conference proceedings article
| Title | Multi-algorithm respiratory crackle detection |
|---|---|
| Author | João Quintas, Guilherme Campos, Alda Marques |
| Booktitle | 6th International Conference on Health Informatics (HEALTHINF 2013) |
| Address | Barcelona, Spain |
| Volume | |
| Pages | |
| Month | February |
| Year | 2013 |
| Group | |
| Group (before 2015) | Signal Processing Laboratory |
| Indexed by ISI | Yes |
| Scope | International |
Four crackle detection algorithms were implemented based on selected techniques proposed in the literature. The algorithms were tested on a set of lung sounds and their performance was assessed in terms of sensitivity (SE), accuracy (PPV) and their harmonic mean (F index). The reference annotation data for calculating these indices were obtained through agreement by majority between independent annotations made by three health professionals on the same set of lung sounds. A combination of the four algorithms based on agreement by majority afforded more than 7% performance improvement over the best individual algorithm.