Towards Scalable Measures of Quality of Interaction: Motor Interference
- Submitting institution
-
University of Hertfordshire
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 20209471
- Type
- D - Journal article
- DOI
-
10.1145/3344277
- Title of journal
- ACM Transactions on Human-Robot Interaction
- Article number
- 8
- First page
- -
- Volume
- 9
- Issue
- 2
- ISSN
- 2573-9522
- Open access status
- Compliant
- Month of publication
- December
- 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
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The reported work constitutes a world first in detecting motor interference in a spatial and experimental setup with relaxed constraints as compared to the standard paradigm. It was presented at the online HRI2020 workshop on `Test Methods and Metrics for Effective HRI in Real World Human-Robot Teams’ which led to the first author's involvement in standardisation efforts in HRI (IEEE study group on human-robot interaction metrics led by Jeremy Marvel, NIST). It has been instrumental in securing a senior lectureship for the first author and led to a follow-up experiment.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -