Signal Complexity, Response Complexity, and Signal Specification in Vigilance

Childs, Jerry M.

doi:10.1177/001872087601800203

Cited by 7 publications

(3 citation statements)

References 32 publications

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“…Some researchers have simply ignored the end-spurt effect, dropping the final period from analyses (e.g., Scheffers et al, 1999). Others have changed methodology to allay the effects of the end-spurt, such as removing clocks and personal time devices (e.g., Childs, 1976;Halcomb & Blackwell, 1969) or suggesting the experiment will be longer than it actually is (e.g., McCann, 1969). Whereas others might have examined larger time-on-task periods (e.g., experiment halves) due to decreased confidence and statistical power as they traditionally focus on behavioral performance regarding targets (i.e., low number of stimuli in smaller time-on-task periods).…”

mentioning

confidence: 99%

Beyond the Vigilance End-Spurt with Event-Related Potentials

Morris

Haubert

Gunzelmann

2020

Proceedings of the Human Factors and Ergonomics Society Annual

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As task environments become more automated and operators become more passive monitors, it is important to understand the underlying mechanisms of the vigilance decrement to help inform task development and interventions. Some vigilance studies have reported an end-spurt effect, where performance increases at the end of the task. This is commonly purported to be the result of increased resources from motivation or arousal; however, self-regulation of attentional resources throughout the vigil has not been addressed. To provide insight into the mechanisms underlying the vigilance decrement, we utilize event-related potentials to examine the vigilance decrement beyond the end-spurt. Thirty-two individuals aged 18 – 36 ( M = 22.60; SD = 4.08) completed a vigilance task with an unknown end time while EEG data was collected. Results revealed non-monotonic trends in N1 and P3 components, suggesting that individuals might self-regulate resources during the vigil, adapting to the constraints of the task environment.

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mentioning

confidence: 99%

Beyond the Vigilance End-Spurt with Event-Related Potentials

Morris

Haubert

Gunzelmann

2020

Proceedings of the Human Factors and Ergonomics Society Annual

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“…Kennedy (1971), Childs (1976), and Galinsky et al (1993) are examples of Human Factors research into fatigue and stress while doing auditory monitoring.…”

Section: Hermann and Huntmentioning

confidence: 99%

Auralization of process and port status using program binaries to generate semantically meaningful non-fatiguing noise as canonical sound signals

Loui

Dozier

Barber

et al. 2015

2015 IEEE International Conference on Electro/Information Technology (EIT)

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We describe using auralization to monitor process stack and netstat status on a server or small group of servers. Using the auditory channel is especially useful for monitoring because it can be done without taking much attention. Our contribution is to suggest generating noise-like sounds that more naturally fade into the background, and are less fatiguing over long monitoring sessions. Although our noises are not musically or tonally interesting, they are nevertheless semantically identifiable and succeed in indicating changes of state.

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“…Childs found that subjects perform better when monitoring for only one target than monitoring for several targets, indicating that the attention resources are important in vigilance [3]. Parasuraman found that high event rates would decrease sensitivity and vigilance performance, any technique that will enhance a subject's memory of signal characteristics should improve vigilance [13].…”

Section: Introductionmentioning

confidence: 99%

The Design of a Fuzzy Logical Vigilance Performance Alarm System for Automation Supervisory Control Tasks

Liu

Hwang

2001

Journal of the Chinese Institute of Industrial Engineers

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Previous researches have shown that the vigilance determines the reliability of human performance, especially in low arousal level tasks such as the radar monitoring, so it is an important factor for automation system performance. The purpose of this research was to study how the fuzzy technique can combat the loss of vigilance in automation. Firstly, a quantitative performance measuring model with signal to noise ratio (η value) for dynamic characteristics of human decision-making was proposed. Secondly, using the terms of the performance evaluating value (η value) and the stochastic process in automation signal status, a fuzzy logical vigilance performance alarm system was constructed. The results of this study indicated that using the performance measuring model to measure system operating performance on human dynamic decision-making is easy and objective, and the fuzzy logical vigilance performance alarm combined with financial incentives according to the η value could improve the system operating performance significantly.

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Signal Complexity, Response Complexity, and Signal Specification in Vigilance

Cited by 7 publications

References 32 publications

Beyond the Vigilance End-Spurt with Event-Related Potentials

Beyond the Vigilance End-Spurt with Event-Related Potentials

Auralization of process and port status using program binaries to generate semantically meaningful non-fatiguing noise as canonical sound signals

The Design of a Fuzzy Logical Vigilance Performance Alarm System for Automation Supervisory Control Tasks

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