A 3D machine vision method for non-invasive assessment of respiratory function
- Submitting institution
-
University of the West of England, Bristol
- Unit of assessment
- 12 - Engineering
- Output identifier
- 912018
- Type
- D - Journal article
- DOI
-
10.1002/rcs.1669
- Title of journal
- International Journal of Medical Robotics and Computer Assisted Surgery
- Article number
- -
- First page
- 179
- Volume
- 12
- Issue
- 2
- ISSN
- 1478-5951
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- Year of publication
- 2015
- URL
-
http://dx.doi.org/10.1002/rcs.1669
- Supplementary information
-
-
- 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
-
3
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper represents the culmination of the NIHR funded project ‘Novel Non-invasive Assessment of Respiratory Function (NORM)’, led by the first author, involving collaboration with respiratory clinician Henderson at University Hospital Bristol NHS Trust (grant NIHRDH-II-FS-0908-10078). The techniques described on 3D vision for morphological analysis and appraisal of the body inform the author’s current £1M application to NIHR with clinical and industrial partners: ‘AssistAbility: To develop and evaluate the effectiveness of a remote automated frailty monitoring and physiotherapy intervention system, to reduce frailty, falls and injuries and improve quality-of-life in frail older-adults.’
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
