Name
Title | ||
|---|---|---|
A Machine Hearing System for Robust Cough Detection Based on a High-Level Representation of Band-Specific Audio Features. |
Abstract | ||
|---|---|---|
our proposal is aligned with a more comfortable and less disruptive patient monitoring, with benefits for patients (allows self-monitoring of cough symptoms), practitioners (e.g., assessment of treatments or better clinical understanding of cough patterns) and national health systems (by reducing hospitalisations). |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TBME.2018.2888998 | IEEE transactions on bio-medical engineering |
Keywords | Field | DocType |
Noise measurement,Protocols,Auditory system,Feature extraction,Monitoring,Mel frequency cepstral coefficient,Time-frequency analysis | Mel-frequency cepstrum,Computer vision,External Data Representation,Noise measurement,Feature selection,Segmentation,Remote patient monitoring,Computer science,Support vector machine,Feature extraction,Speech recognition,Artificial intelligence | Journal |
Volume | Issue | ISSN |
66 | 8 | 1558-2531 |
Citations | PageRank | References |
1 | 0.37 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jesus Monge-Alvarez | 1 | 7 | 1.92 |
| Carlos Hoyos-Barcelo | 2 | 6 | 1.22 |
| Luis Miguel San-Jose-Revuelta | 3 | 1 | 0.37 |
| Pablo Casaseca | 4 | 77 | 15.83 |