Efficient computation of image moments for robust cough detection using smartphones
- Submitting institution
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University of the West of Scotland
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 13118306
- Type
- D - Journal article
- DOI
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10.1016/j.compbiomed.2018.07.003
- Title of journal
- Computers in Biology and Medicine
- Article number
- -
- First page
- 176
- Volume
- 100
- Issue
- -
- ISSN
- 0010-4825
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2018
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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4
- Research group(s)
-
-
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Efficient feature extraction engine for Smartphone-based cough detection is proposed, which enables real-time continuous cough detection whilst keeping battery consumption below 25%. The implementations are incorporated to the Smartcough App. (https://smartcough.wordpress.com/), which raised industrial interest for further commercialisation. The 1.5-billion-revenue Semiconductor company Cirrus Logic funded validation study to explore commercialisation of the app.(£30k). Collaboration with Regional Health System in Castilla León (Spain) has also resulted to deploy the app in a real clinical environment.
Contacts:
Corporate Business Development Manager, Cirrus Logic.
Admissions Manager, Castilla León Health System (SACYL).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -