The development of a video retrieval system using a clinician-led approach
- Submitting institution
-
Manchester Metropolitan University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2367
- Type
- D - Journal article
- DOI
-
10.1016/j.eswa.2019.112992
- Title of journal
- Expert Systems with Applications
- Article number
- 112992
- First page
- -
- Volume
- 142
- Issue
- -
- ISSN
- 0957-4174
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2019
- URL
-
https://e-space.mmu.ac.uk/624134/
- 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)
-
B - Human Centred-Computing
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper helps physiotherapists to save time by enabling them to search quickly through large quantities of video in order to find specific head movements. Based on a collaboration with The Movement Centre, Oswestry (Sarah Bew; sarahbew@the-movement-centre.co.uk) it sidesteps difficulties in accurately defining/matching movement descriptions in other formats (e.g., natural language queries) by letting clinicians move their own body to generate ‘queries-by-movement’. The tool permits fast analysis of long recordings (e.g. home videos shared by patients) which can be important tools in recovery, while ensuring clinicians can make decisions about the specific movements they are interested in.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -