TY - GEN
T1 - Physiological Indicators for Real-Time Detection of Operator’s Attention
AU - Bjegojevic, Bojana
AU - Leva, Maria Chiara
AU - Cromie, Sam
AU - Balfe, Nora
N1 - Publisher Copyright:
© 2022 ESREL2022 Organizers. Published by Research Publishing, Singapore.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - Attention
KW - Electrocardiography (ECG); NASA Multi Attribute Task Battery (MATB)
KW - Electroencephalography (EEG)
KW - Eyetracking
KW - Operator safety
KW - Physiology
KW - Real-time measurement
UR - https://www.scopus.com/pages/publications/85207660905
U2 - 10.3850/978-981-18-5183-4_J01-05-149-cd
DO - 10.3850/978-981-18-5183-4_J01-05-149-cd
M3 - Conference contribution
AN - SCOPUS:85207660905
SN - 9789811851834
T3 - Proceedings of the 32nd European Safety and Reliability Conference, ESREL 2022 - Understanding and Managing Risk and Reliability for a Sustainable Future
SP - 3309
EP - 3316
BT - Proceedings of the 32nd European Safety and Reliability Conference, ESREL 2022 - Understanding and Managing Risk and Reliability for a Sustainable Future
A2 - Leva, Maria Chiara
A2 - Patelli, Edoardo
A2 - Podofillini, Luca
A2 - Wilson, Simon
PB - Research Publishing Services
T2 - 32nd European Safety and Reliability Conference, ESREL 2022
Y2 - 28 August 2022 through 1 September 2022
ER -