Signal Processing of Multimodal Mobile Lifelogging Data towards Detecting Stress in Real-World Driving
- Submitting institution
-
Liverpool John Moores University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 988
- Type
- D - Journal article
- DOI
-
10.1109/TMC.2018.2840153
- Title of journal
- IEEE Transactions on Mobile Computing
- Article number
- -
- First page
- 632
- Volume
- 18
- Issue
- 3
- ISSN
- 1536-1233
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2018
- 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
-
1
- Research group(s)
-
-
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work represents the culmination of research developed under an EPSRC-funded project (EP/M029484/1, £99k, 2015-2016) and introduces novel algorithms designed to process multiple streams of lifelogging data for stress detection in the context of real-world driving. The work helps to support the self-regulation of stress for the benefit of mental health and driving safety.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
