An assessment of algorithms to estimate respiratory rate from the electrocardiogram and photoplethysmogram
- Submitting institution
-
University of Oxford
- Unit of assessment
- 12 - Engineering
- Output identifier
- 9445
- Type
- D - Journal article
- DOI
-
10.1088/0967-3334/37/4/610
- Title of journal
- Physiological Measurement
- Article number
- -
- First page
- 610
- Volume
- 37
- Issue
- 4
- ISSN
- 0967-3334
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
http://peterhcharlton.github.io/Rrest
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
5
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Winner of the Institute of Physics "Martin Black" prize for best biomedical publication in 2016. This work produced results that have been used in large EPSRC-funded programmes (ASPIRE, Healthcare Technologies Grand Challenge Award) that focus on machine learning for wearable sensors in medicine.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -