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INTRODUCTION: Studies examining sustained attention abilities typically utilize metrics that quantify performance on vigilance tasks, such as response time and response time variability. However, approaches that assess the duration that an individual can maintain their attention over time are lacking. METHODS: Here we developed an objective attention span metric that quantified the maximum amount of time that a participant continuously maintained an optimal in the zone sustained attention state while performing a continuous performance task. RESULTS: In a population of 262 individuals aged 7-85, we showed that attention span was longer in young adults than in children and older adults. Furthermore, declines in attention span over time during task engagement were related to clinical symptoms of inattention in children. DISCUSSION: These results suggest that quantifying attention span is a unique and meaningful method of assessing sustained attention across the lifespan and in populations with inattention symptoms.

The capacity to sustain attention to virtual threat landscapes has led cyber security to emerge as a new and novel domain for vigilance research. However, unlike classic domains, such as driving and air traffic control and baggage security, very few vigilance tasks exist for the cyber security domain. Four essential challenges that must be overcome in the development of a modern, validated cyber vigilance task are extracted from this review of existent platforms that can be found in the literature. Firstly, it can be difficult for researchers to access confidential cyber security systems and personnel. Secondly, network defense is vastly more complex and difficult to emulate than classic vigilance domains such as driving. Thirdly, there exists no single, common software console in cyber security that a cyber vigilance task could be based on. Finally, the rapid pace of technological evolution in network defense correspondingly means that cyber vigilance tasks can become obsolete just as quickly. Understanding these challenges is imperative in advancing human factors research in cyber security.

Vigilance decrement refers to a psychophysiological decline in the capacity to sustain attention to monotonous tasks after prolonged periods. Vigilance decrement was explored in the cyber security domain across two studies. The Western Australian Cyber Defence Task (WACDT) was designed, developed and validated as a network defence sustained attention task in Study 1. The WACDT is the only cyber vigilance task presented to the literature outside of antiquated products developed by the United States Air Force. The WACDT was then used in Study 2 as an experimental platform by which to explore psychophysiological indicators of cyber vigilance decrement. A functional near infrared spectrometer was used to identify several cerebral haemodynamic features that indicate when a network defence analyst is experiencing cyber vigilance decrement. A novel theoretical account was proposed in Study 2 to explain cerebral haemodynamic features associated with vigilance decrement known as Optimal Resource Control Failure Theory (ORCFT). Studies 1 and 2 collectively illustrate the divide between hardware, software and cyber-cognitive vulnerabilities in the network defence space.

This paper proposes two novel methods to classify semantic vigilance levels by utilizing EEG directed connectivity patterns with their corresponding graphical network measures. We estimate the directed connectivity using relative wavelet transform entropy (RWTE) and partial directed coherence (PDC) and the graphical network measures by graph theory analysis (GTA) at four frequency bands. The RWTE and PDC quantify the strength and directionality of information flow between EEG nodes. On the other hand, the GTA of the complex network measures summarizes the topological structure of the network. We then evaluate the proposed methods using machine learning classifiers. We carried out an experiment on nine subjects performing semantic vigilance task (Stroop color word test (SCWT)) for approximately 45 minutes. Behaviorally, all subjects demonstrated vigilance decrement as reflected by the significant increase in response time and reduced accuracy. The strength and directionality of information flow in the connectivity network by RWTE/PDC and the GTA measures significantly decrease with vigilance decrement, p<0.05. The classification results show that the proposed methods outperform other related and competitive methods available in the literature and achieve 100% accuracy in subject-dependent and above 89% in subject-independent level in each of the four frequency bands. The overall results indicate that the proposed methods of directed connectivity patterns and GTA provide a complementary aspect of functional connectivity. Our study suggests directed functional connectivity with GTA as informative features and highlight Support Vector Machine as the suitable classifier for classifying semantic vigilance levels., American University of Sharjah

This paper presents the first comprehensive review on vigilance enhancement using both conventional and unconventional means, and further discusses the resulting contradictory findings. It highlights the key differences observed between the research findings and argues that variations of the experimental protocol could be a significant contributing factor towards such contradictory results. Furthermore, the paper reveals the effectiveness of unconventional means of enhancement in significant reduction of vigilance decrement compared to conventional means. Meanwhile, a discussion on the challenges of enhancement techniques is presented, with several suggested recommendations and alternative strategies to maintain an adequate level of vigilance for the task at hand. Additionally, this review provides evidence in support of the use of unconventional means of enhancement on vigilance studies, regardless of their practical challenges.

Objective: We investigated a driver monitoring system (DMS) designed to adaptively back up distracted drivers with automated driving. Background: Humans are likely inadequate for supervising today’s on-road driving automation. Conversely, backup concepts can use eye-tracker DMS to retain the human as the primary driver and use computerized control only if needed. A distraction DMS where perceived false alarms are minimized and the status of the backup is unannounced might reduce problems of distrust and overreliance, respectively. Experimental research is needed to assess the viability of such designs. Methods: In a driving simulator, 91 participants either supervised driving automation (auto-hand-on-wheel vs. auto-hands-off-wheel), drove with different forms of DMS-induced backup control (eyes-only-backup vs. eyes-plus-context-backup; visible-backup vs. invisible-backup), or drove without any automation. All participants performed a visual N-back task throughout. Results: Supervised driving automation increased visual distraction and hazard non-responses compared to backup and conventional driving. Auto-hand-on-wheel improved response generation compared to auto-hands-off-wheel. Across entire driving trials, the backup improved lateral performance compared to conventional driving. Without negatively impacting safety, the eyes-plus-context-backup DMS reduced unnecessary automated control compared to the eyes-only-backup DMS conditions. Eyes-only-backup produced low satisfaction ratings, whereas eyes-plus-context-backup satisfaction was on par with automated driving. There were no appreciable negative consequences attributable to the invisible-backup driving automation. Conclusions: We have demonstrated preliminary feasibility of DMS designs that incorporate driving context information for distraction assessment and suppress their status indication. Application: An appropriately designed DMS can enable benefits for automated driving as a backup., Intelligent Vehicles, Human-Robot Interaction

Objective: We investigated a driver monitoring system (DMS) designed to adaptively back up distracted drivers with automated driving. Background: Humans are likely inadequate for supervising today’s on-road driving automation. Conversely, backup concepts can use eye-tracker DMS to retain the human as the primary driver and use computerized control only if needed. A distraction DMS where perceived false alarms are minimized and the status of the backup is unannounced might reduce problems of distrust and overreliance, respectively. Experimental research is needed to assess the viability of such designs. Methods: In a driving simulator, 91 participants either supervised driving automation (auto-hand-on-wheel vs. auto-hands-off-wheel), drove with different forms of DMS-induced backup control (eyes-only-backup vs. eyes-plus-context-backup; visible-backup vs. invisible-backup), or drove without any automation. All participants performed a visual N-back task throughout. Results: Supervised driving automation increased visual distraction and hazard non-responses compared to backup and conventional driving. Auto-hand-on-wheel improved response generation compared to auto-hands-off-wheel. Across entire driving trials, the backup improved lateral performance compared to conventional driving. Without negatively impacting safety, the eyes-plus-context-backup DMS reduced unnecessary automated control compared to the eyes-only-backup DMS conditions. Eyes-only-backup produced low satisfaction ratings, whereas eyes-plus-context-backup satisfaction was on par with automated driving. There were no appreciable negative consequences attributable to the invisible-backup driving automation. Conclusions: We have demonstrated preliminary feasibility of DMS designs that incorporate driving context information for distraction assessment and suppress their status indication. Application: An appropriately designed DMS can enable benefits for automated driving as a backup., Intelligent Vehicles, Human-Robot Interaction

A Master of Science thesis in Electrical Engineering by Salma Khaled Mohamad Zeid entitled, "Measurement of Vigilance Using EEG Source Localization," submitted in November 2017. Thesis advisor is Dr. Hasan Al-Nashash and thesis co-advisor is Dr. Hasan Mir. Soft and hard copy available., Vigilance, or sustained attention, is crucial for jobs where attentiveness for prolonged times is required. These jobs include air traffic control, luggage inspection, and surveillance jobs. Vigilance decrement can cause catastrophic consequences. Therefore, vigilance level assessment is a widely-researched topic. Several methods have been used to assess vigilance levels such as eye tracking techniques which include monitoring saccadic eye movements and pupil size variation. Other methods used are heart rate variability, and physiological data such as electrocardiogram (ECG), electro-oculogram (EoG) and electroencephalogram (EEG). EEG data has been found to have strong correlations with human's vigilance level. This thesis report presents a novel method for the assessment of vigilance decrement using EEG data that embarks upon the brain's temporal behavior. An experiment based on a 20 to 30-minute Psychomotor Vigilance Task (PVT), that simulates real applications where vigilance decrement is observed, was carried out on 33 subjects and their EEG recordings and reaction times were collected. In the PVT task, subjects were required to respond to target events while refraining from non-target events. Vigilance reinforcement by challenge integration was tested where 22 out of the 33 subjects had an additional task where they had to respond to noisy target events. The spectral power density characteristics namely the delta, theta, alpha and beta waves of the EEG data are compared for low and high vigilance states. Furthermore, EEG source localization is utilized to monitor source dynamics of the brain in transition from vigilance states. Results from both methods are analyzed using Student's t-test with the significance threshold set at 0.1. Power spectral density analysis showed that power in AF8 electrode in delta, theta and alpha bands increased with vigilance decrement with p-values .023, .079 and .020 respectively. The source localization approach showed an increase, College of Engineering, Department of Electrical Engineering

This report summarizes activity from the first year of a three-year project on aiding decision making in human-system interface. This report includes description of a new adaptive automation design model, allowing system designers the ability to visually and systematically evaluate the placement of adaptive automation within a system network. This model aids the designer to isolate the tasks, which require human decision making, ideally permitting tasks to be automated which do not require human decisions. A tool for evaluating adaptive automation, referred to as Space Navigator has been developed. This game has been designed using the model, has allowed us (and future researchers) to simplify data gathering from human participants. The resulting automation system will allow for research into how similarity and difference of actions between a human-machine team affect the overall performance of the system. The final experimental data will provide several areas of further research including trust in automation, training improvement, workload reduction (actual and perceived), and task load switching., The original document contains color images.

For prolonged cognitive tasks the efficiency of an observer, as a function of test period, is often illustrated as a downward-sloping curve. This deterioration is called the vigilance decrement and is due to a shift in attention during a task. We have investigated the temporal features of attention by using an RSVP task. We focused on transient performance in a trial, in addition to prolonged performance throughout the experiment. Throughout the experiment a vigilance decrement occurred. During a trial however, the detection of a target at the beginning of a sequence was dramatically low and recovered as it appeared later. This result has been shown neither in the vigilance studies, which predict high performance after the task onset, nor in the RSVP studies, which predict high and fair detection of only target in the sequence. This result would reflect a gradual modulation of temporal attention to a rapid sequence., Summary of Awarded Presentation at the 23rd Annual Meeting

Donald, F., Donald, C., & Thatcher, A. (2015). Work exposure and vigilance decrements in closed circuit television surveillance. Applied ergonomics, 47, 220-228. Available here