dc.contributor.author | Cromie, Samuel | |
dc.contributor.author | Balfe, Nora | |
dc.contributor.author | Leva, Chiara | |
dc.contributor.editor | Maria Chiara Leva, Edoardo Patelli, Luca Podofillini, and Simon Wilson | en |
dc.date.accessioned | 2024-08-01T05:31:24Z | |
dc.date.available | 2024-08-01T05:31:24Z | |
dc.date.created | 2022 | en |
dc.date.issued | 2022 | |
dc.date.submitted | 2022 | en |
dc.identifier.citation | Bojana Bjegojevic, Maria Chiara Leva, Sam Cromie, Nora Balfe, Physiological Indicators for Real-Time Detection of Operator's Attention, 32nd European Safety and Reliability Conference (ESREL 2022), Dublin, 2022, Maria Chiara Leva, Edoardo Patelli, Luca Podofillini, and Simon Wilson, Research Publishing, Singapore., 2022, 3309 - 3316 | en |
dc.identifier.other | Y | |
dc.description.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 driver-
monitoring 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. | en |
dc.format.extent | 3309 | en |
dc.format.extent | 3316 | en |
dc.language.iso | en | en |
dc.publisher | Research Publishing, Singapore. | en |
dc.rights | Y | en |
dc.subject | Attention, Operator safety, Physiology, Real-time measurement, Electroencephalography (EEG), Eye- tracking, Electrocardiography (ECG); NASA Multi Attribute Task Battery (MATB) | en |
dc.title | Physiological Indicators for Real-Time Detection of Operator's Attention | en |
dc.title.alternative | 32nd European Safety and Reliability Conference (ESREL 2022) | en |
dc.type | Conference Paper | en |
dc.type.supercollection | scholarly_publications | en |
dc.type.supercollection | refereed_publications | en |
dc.identifier.peoplefinderurl | http://people.tcd.ie/sdcromie | |
dc.identifier.peoplefinderurl | http://people.tcd.ie/balfen | |
dc.identifier.peoplefinderurl | http://people.tcd.ie/levac | |
dc.identifier.rssinternalid | 268495 | |
dc.identifier.doi | https://doi.org/10.3850/978-981-18-5183-4_J01-05-149-cd | |
dc.rights.ecaccessrights | openAccess | |
dc.subject.TCDTag | Cognitive Neuroscience | en |
dc.subject.TCDTag | HUMAN FACTORS | en |
dc.subject.TCDTag | Neurophysiology | en |
dc.identifier.orcid_id | 0000-0001-5023-0435 | |
dc.status.accessible | N | en |
dc.contributor.sponsor | Science Foundation Ireland (SFI) | en |
dc.identifier.uri | https://hdl.handle.net/2262/108797 | |