ORCID
- Maria Chiara Leva: 0000-0002-6770-8332
Abstract
Attention is a safety-critical operator ability that needs to be sustained over the course of specific tasks. However, many internal factors (e.g.: cognitive underload or overload, fatigue, etc.) and external factors (e.g.: HMI quality, environmental stressors, noise, etc.), can cause attention to drift away from the task. Having real-time indicators of operator’s attention could increase the safety of any human-operated system. Recent industrial deployment of drivermonitoring systems demonstrated the possible use of certain physiological and behavioural metrics as indicators of attention. However, it is unclear how sensitive and accurate these metrics are in detecting attention-related changes. This paper aims to provide a brief review of the potential real-time proxy-indicators of attention and present an experiment design to assess their suitability and sensitivity using performance metrics as a benchmark. Several variables identified in the literature are presented, each is associated with a particular aspect of attention. They are grouped into electroencephalography-, eye-tracking-, and electrocardiography- based variables. The experiment devised to test these variables involves computer-based task, designed to incur varying degrees of task load and to evoke different attentional requirements. It allows the recording of different individual performance metrics. The relationship between performance and physiological indicators will be tested and compared across different attentional requirement and task load conditions. Real-time indices of attention have important safety implications such as providing immediate feedback to the operator or predicting attentional lapses.
Keywords
Attention, Electrocardiography (ECG); NASA Multi Attribute Task Battery (MATB), Electroencephalography (EEG), Eyetracking, Operator safety, Physiology, Real-time measurement
Publication Date
2022-01-01
Event
32nd European Safety and Reliability Conference, ESREL 2022
Publication Title
Proceedings of the 32nd European Safety and Reliability Conference, ESREL 2022 - Understanding and Managing Risk and Reliability for a Sustainable Future
Publisher
Research Publishing Services
ISBN
9789811851834
First Page
3309
Last Page
3316
Deposit Date
2026-07-29
Additional Links
Recommended Citation
Bjegojevic, Bojana; Leva, Maria Chiara; Cromie, Sam; and Balfe, Nora, "Physiological Indicators for Real-Time Detection of Operator’s Attention" (2022). Research Outputs: 2025-Present. 48.
https://arrow.tudublin.ie/schfsehro/48