Quantitative modeling of user performance in multitasking environments

Liu, Shijing; Nam, Chang S.

doi:10.1016/j.chb.2018.02.035

Cited by 17 publications

(13 citation statements)

References 118 publications

(224 reference statements)

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“…Also, EEG research may use formulation by (7) on findings considering previous and later interventions on videogames on spectral ERP for fortress hits, rare tones (inside and outside the game), and mine appearances [ 43 ]. Limitation here is for a variety of complex and non/complex tasks maybe worked [ 44 ].…”

Section: Onclusion: Improvement Of Modelling Novel Responsmentioning

confidence: 99%

Prior context influences motor brain areas in an auditory oddball task and prefrontal cortex multitasking modelling

et al. 2021

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In this study, the relationship of orienting of attention, motor control and the Stimulus- (SDN) and Goal-Driven Networks (GDN) was explored through an innovative method for fMRI analysis considering all voxels in four experimental conditions: standard target (Goal; G), novel (N), neutral (Z) and noisy target (NG). First, average reaction times (RTs) for each condition were calculated. In the second-level analysis, ‘distracted’ participants, as indicated by slower RTs, evoked brain activations and differences in both hemispheres’ neural networks for selective attention, while the participants, as a whole, demonstrated mainly left cortical and subcortical activations. A context analysis was run in the behaviourally distracted participant group contrasting the trials immediately prior to the G trials, namely one of the Z, N or NG conditions, i.e. Z.G, N.G, NG.G. Results showed different prefrontal activations dependent on prior context in the auditory modality, recruiting between 1 to 10 prefrontal areas. The higher the motor response and influence of the previous novel stimulus, the more prefrontal areas were engaged, which extends the findings of hierarchical studies of prefrontal control of attention and better explains how auditory processing interferes with movement. Also, the current study addressed how subcortical loops and models of previous motor response affected the signal processing of the novel stimulus, when this was presented laterally or simultaneously with the target. This multitasking model could enhance our understanding on how an auditory stimulus is affecting motor responses in a way that is self-induced, by taking into account prior context, as demonstrated in the standard condition and as supported by Pulvinar activations complementing visual findings. Moreover, current BCI works address some multimodal stimulus-driven systems.

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Section: Onclusion: Improvement Of Modelling Novel Responsmentioning

confidence: 99%

Prior context influences motor brain areas in an auditory oddball task and prefrontal cortex multitasking modelling

et al. 2021

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“…Table 1 shows articles included in the analysis in chronological order and the overview of the MATB use in respective study. Generating three levels of task difficulty (all subtasks) as a basis to measure workload using a subjective method (NASA-TLX), whose data will be compared with CPN model values 30 [33] Examine cross-participant estimation of operator workload in a non-stimulus-locked, multitask environment by developing and evaluating seven neural network architectures Generating low and high workload condition (all subtasks) to obtain EEG dataset that will be used for neural network training [34] Validate a quantitative model for the study of user performance improvement in a multitasking environment Generating three levels of task difficulty (all subtask) based on baud rate and to be used as a basis for subjective workload rating and for performance measurement…”

Section: Resultsmentioning

confidence: 99%

The use of multi-attribute task battery in mental workload studies: A scoping review

Prasetyo

2024

SHS Web Conf.

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Multi-Attribute Task Battery (MATB) is a software that has been arguably utilized in many ergonomics/human factors studies, including in the topic of mental workload. However, the use of this well-known program in diverse investigations has not yet been systematically tracked. Furthermore, it may be argued that a critical appraisal of MATB is urgently needed so that future researchers and users can take several crucial factors into account when planning a study or experiment using MATB. The aim of this paper is to comprehensively identify and review the use of MATB software in published studies. This aim might be accomplished by achieving two goals: (1) systematic discovery of published papers in literature databases and (2) categorization of research according to pertinent topics. In this paper, thirty-one articles were included for analysis after carefully screening for their eligibility. Our scoping review finds that MATB is a beneficial program for creating multitasking environments in general, with aviation being the area where it has been used the most. The program was also extensively used for studies on mental workload, especially by producing various stimuli that ultimately result in varying degrees of task demand or difficulty. Moreover, to successfully use MATB, researchers must be aware of a few operational issues and criticisms.

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“…The four tasks files consisted of two blocks of two trials each, where the trials were either 'low' or 'high' TC. TC was determined by the baud rate (Liu & Nam, 2018). The blocks were randomized so that each participant executed the trials in a different order.…”

Section: Methodsmentioning

confidence: 99%

The Effect of Task Complexity on Eye Movement and Multitasking Performance in Students With and Without ADHD

Johnson

Kim

2020

Proceedings of the Human Factors and Ergonomics Society Annual

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Attention Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder that affects many individual’s ability to maintain and shift attention. Little is known about the connection between executive function and eye movement in individuals diagnosed with ADHD during multitasking. The objective of this research is to examine the relationship between patterns of eye movement and multitasking performance between students with and without ADHD. During the experiment, students with and without ADHD completed NASA’s Multi-Attribute Task Battery at both low and high task complexity. We found that students without ADHD showed higher error counts, higher workload ratings, and greater total number of fixations in the high task complexity than in the low task complexity. By understanding the relationship among eye movement, executive functioning, and mental workload, it is possible to gain insight in attention allocation in online learning environments and apply that knowledge to create tools for equal access to learning.

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Quantitative modeling of user performance in multitasking environments

Cited by 17 publications

References 118 publications

Prior context influences motor brain areas in an auditory oddball task and prefrontal cortex multitasking modelling

Prior context influences motor brain areas in an auditory oddball task and prefrontal cortex multitasking modelling

The use of multi-attribute task battery in mental workload studies: A scoping review

The Effect of Task Complexity on Eye Movement and Multitasking Performance in Students With and Without ADHD

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