Complexity Variability Assessment of Nonlinear Time-Varying Cardiovascular Control
- Submitting institution
-
The University of Essex
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1154
- Type
- D - Journal article
- DOI
-
10.1038/srep42779
- Title of journal
- Scientific Reports
- Article number
- 42779 (2017)
- First page
- 42779
- Volume
- 7
- Issue
- 1
- ISSN
- 2045-2322
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2017
- URL
-
-
- 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
- Yes
- Number of additional authors
-
5
- Research group(s)
-
B - Brain Computer Interfaces and Neural Engineering (BCI-NE)
- Citation count
- 23
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work presented a new approach to discern pathology-related changes in autonomic control by quantifying second-order moments of time-varying cardiovascular complexity. Rigour: The proposed methodology was statistically tested on four separate studies: Congestive Heart Failure (CHF), Major Depression Disorder (MDD), Parkinson's Disease (PD), and Post-Traumatic Stress Disorder (PTSD) patients with insomnia. Significance: Our results show applicability of the method to a range of heterogeneous disorders from cardiology, neurology and psychiatry, with important implications. The research findings of this paper were reported in the scientific section of "La Repubblica" (the second most-widespread Italian newspaper by circulation): https://www.repubblica.it/scienze/2017/03/28/news/indicatore_che_rivela_malattie_neurologiche_osservando_il_cuore-161637489
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -