A personalized-model-based central aortic pressure estimation method
- Submitting institution
-
The University of Leeds
- Unit of assessment
- 12 - Engineering
- Output identifier
- ELEC-45
- Type
- D - Journal article
- DOI
-
10.1016/j.jbiomech.2016.11.007
- Title of journal
- Journal of Biomechanics
- Article number
- -
- First page
- 4098
- Volume
- 49
- Issue
- 16
- ISSN
- 0021-9290
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2016
- URL
-
https://doi.org/10.1016/j.jbiomech.2016.11.007
- Supplementary information
-
https://www.sciencedirect.com/science/article/pii/S0021929016311654#s0080
- 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
- The paper establishes the world first computational model to enable a central aortic pressure estimation method to be implemented in daily living environments. The patented technology (CN103892818A, ‘A non-invasive central aortic blood pressure measurement method and apparatus’) supported the investment of CNY30M (~ £3.4M) from the Nanjing local government to set up the Chinese Academy of Sciences ‘Institute of Healthcare Technologies’ (www.cas-healthcare.cn), which has subsequently incubated a number of start-up companies (including Ningxin Ltd, Ningzhen ltd, and Zitong Consulting Ltd) to develop technologies of benefit to cardiovascular patients.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
