Beyond Activity Recognition: Skill Assessment from Accelerometer Data
- Submitting institution
-
University of Newcastle upon Tyne
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 216591-86533-1292
- Type
- E - Conference contribution
- DOI
-
10.1145/2750858.2807534
- Title of conference / published proceedings
- UbiComp '15: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing
- First page
- 1155
- Volume
- -
- Issue
- -
- ISSN
- -
- Open access status
- -
- Month of publication
- September
- Year of publication
- 2015
- URL
-
http://dx.doi.org/10.1145/2750858.2807534
- 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
-
6
- Research group(s)
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C - Open Lab
- Citation count
- 19
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presents a new model for automatic skill assessment using activity recognition techniques, based on wearables data, and includes a proof of concept, which is then thoroughly tested with a sample of medical students, providing training data around practised surgical activities. The work has significant potential to support new kinds of skills-based training and evaluation for people engaged in learning manual tasks (such as surgery). The paper was presented at a prestigious conference and has been well cited.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -