Physiological Impact Assessment of Decision Support Systems on Control Room Operators: An ANCOVA Analysis
This study investigates the physiological effects of AI based Decision Support Systems (DSS) on control room operators through a comprehensive analysis of multiple physiological indicators.Using data from 41 participants divided into control and experimental groups, we analyzed heart rate, temperature, electrodermal activity (EDA), and pupil diameter across three scenarios of increasing complexity.Analysis of Covariance (ANCOVA) was employed to control for baseline differences, revealing significant reductions in pupil diameter (p = 0.0029) for the DSS group, indicating lower cognitive load.While other physiological measures showed consistent trends suggesting reduced stress with DSS use, these differences were not statistically significant.The findings provide empirical evidence for DSS's positive impact on operator cognitive load, particularly during complex scenarios, while highlighting the need for comprehensive physiological monitoring in assessing human-system interaction.
Authors
- Ammar N. Abbas (ORCID: https://orcid.org/0000-0002-2578-5137)
- Maria Chiara Leva (ORCID: https://orcid.org/0000-0002-6770-8332)
- Anders L. Madsen (ORCID: https://orcid.org/0000-0003-0633-9411)
- Joseph Mietkiewicz (ORCID: https://orcid.org/0009-0007-3109-5865)
- Chidera Winifred Amazu (ORCID: https://orcid.org/0000-0001-8788-3173)
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.3850/978-981-94-3281-3_esrel-sra-e2025-p9407-cd
- Primary Topic
- Healthcare Technology and Patient Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Canadian Institute of Steel Construction
- European Commission