An Automatic Health Monitoring System for Patients Suffering From Voice Complications in Smart Cities
- Submitting institution
-
The University of Essex
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1441
- Type
- D - Journal article
- DOI
-
10.1109/access.2017.2680467
- Title of journal
- IEEE Access
- Article number
- -
- First page
- 3900
- Volume
- 5
- Issue
- -
- ISSN
- 2169-3536
- 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
-
2
- Research group(s)
-
B - Brain Computer Interfaces and Neural Engineering (BCI-NE)
- Citation count
- 30
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Published in IEEE-Access, an award-winning multidisciplinary journal, this voice complications research demonstrated a more efficient assessment method via this first-foray into limited bands of low-frequencies to assess dysphonic patients whilst simultaneously enabling high-accuracy via running-speech. Previously only clinical assessment using monotonal vowels was possible but the more complex analysis of running-speech enables continuous remote patient monitoring in smart homes/cities. Subsequent to a period in industry the author has further developed the work and it also influenced others including BUT(Czech-Republic) and ULPGC(Spain) who implemented the suggested frequencies band for feature extraction in the development of a robust pathology detection system (DoI:10.1007/s00521-018-3464-7).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -