Feasibility study of intelligent autonomous determination of the bladder voiding need to treat bedwetting using ultrasound and smartphone ML techniques
- Submitting institution
-
University of Central Lancashire
- Unit of assessment
- 12 - Engineering
- Output identifier
- 25303
- Type
- D - Journal article
- DOI
-
10.1007/s11517-018-1942-9
- Title of journal
- Medical & Biological Engineering & Computing
- Article number
- -
- First page
- 1079
- Volume
- 57
- Issue
- 5
- ISSN
- 0140-0118
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2019
- 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
-
4
- Research group(s)
-
A - Aerospace and Sensing Group
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper resulted from a collaborative project involving Lancashire Teaching Hospital NHS Trust and UCLan funded by the NIHR (≈ £486,000). It introduced the use of machine learning techniques, in conjunction with ultrasound sensor data produced by a body worn device, to form a pre-void alarm to treat children with nocturnal enuresis. The research led to a collaboration between UCLan and Novasound Ltd. to produce a commercial prototype for a miniaturised ultrasound device based on a patent (WO2017017426) granted to protect the invention.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
