scholarly journals Unravelling the Physiological Correlates of Mental Workload Variations in Tracking and Collision Prediction Tasks: Implications for Air Traffic Controllers

2021 ◽  
Author(s):  
Alka Rachel John ◽  
Avinash K Singh ◽  
Tien-Thong Nguyen Do ◽  
Ami Eidels ◽  
Eugene Nalivaiko ◽  
...  
Keyword(s):  
Adaptive Systems ◽  
Closed Loop ◽  
Mental Workload ◽  
Physiological Measures ◽  
Task Load ◽  
Air Traffic Controllers ◽  
Collision Prediction ◽  
Size Number ◽  
The Impact ◽  
Electroencephalogram Eeg

AbstractObjectiveWe have designed tracking and collision prediction tasks to elucidate the differences in the physiological response to the workload variations in basic ATC tasks to untangle the impact of workload variations experienced by operators working in a complex ATC environment.BackgroundEven though several factors influence the complexity of ATC tasks, keeping track of the aircraft and preventing collision are the most crucial.MethodsPhysiological measures, such as electroencephalogram (EEG), eye activity, and heart rate variability (HRV) data, were recorded from 24 participants performing tracking and collision prediction tasks with three levels of difficulty.ResultsThe neurometrics of workload variations in the tracking and collision prediction tasks were markedly distinct, indicating that neurometrics can provide insights on the type of mental workload. The pupil size, number of blinks and HRV metric, root mean square of successive difference (RMSSD), varied significantly with the mental workload in both these tasks in a similar manner.ConclusionOur findings indicate that variations in task load are sensitively reflected in physiological signals, such as EEG, eye activity and HRV, in these basic ATC-related tasks.ApplicationThese findings have applicability to the design of future mental workload adaptive systems that integrate neurometrics in deciding not just ‘when’ but also ‘what’ to adapt. Our study provides compelling evidence in the viability of developing intelligent closed-loop mental workload adaptive systems that ensure efficiency and safety in ATC and beyond.PrécisThis article identifies the physiological correlates of mental workload variation in basic ATC tasks. The findings assert that neurometrics can provide more information on the task that contributes to the workload, which can aid in the design of intelligent mental workload adaptive system.

scholarly journals The Impact of Automation on Air Traffic Controller’s Behaviors

Aerospace ◽  
2021 ◽  
Vol 8 (9) ◽  
pp. 260
Author(s):  
Yanjun Wang ◽  
Rongjin Hu ◽  
Siyuan Lin ◽  
Michael Schultz ◽  
Daniel Delahaye
Keyword(s):  
Eye Movements ◽  
Situation Awareness ◽  
Traffic Management ◽  
Mental Workload ◽  
Air Traffic ◽  
Task Load ◽  
The Gaze ◽  
Air Traffic Controllers ◽  
Automation Tools ◽  
The Impact

Air traffic controllers have to make quick decisions to keep air traffic safe. Their behaviors have a significant impact on the operation of the air traffic management (ATM) system. Automation tools have enhanced the ATM system’s capability by reducing the controller’s task-load. Much attention has been devoted to developing advanced automation in the last decade. However, less is known about the impact of automation on the behaviors of air traffic controllers. Here, we empirically tested the effects of three levels of automation—including manual, attention-guided, and automated—as well as varying traffic levels on eye movements, situation awareness and mental workload. The results showed that there are significant differences in the gaze and saccade behaviors between the attention-guided group and automated group. Traffic affected eye movements under the manual mode or under the attention-guided mode, but had no effect on eye movements under the automated mode. The results also supported the use of automation for enhancing situation awareness while reducing mental workload. Our work has potential implications for the design of automation and operation procedures.

scholarly journals Work Performance Measurement of Data Entry Employees in E-Commerce Industry Based on Mental Workload Value

2019 ◽  
Vol 10 (2) ◽  
Author(s):  
Iwan Aang Soenandi
Keyword(s):  
Work Performance ◽  
Mental Workload ◽  
Data Entry ◽  
Time Measurement ◽  
Task Load ◽  
Factors Influencing ◽  
Before And After ◽  
Reaction Time Measurement ◽  
Nasa Tlx ◽  
Electroencephalogram Eeg

This reseach aimed to measure the mental workload of data entry processing tasks in the e-commerce industry based on mental workload value. It was to determine the factors influencing mental workload mainly induced by the data entry process. The experiments without work instruction and with two types of work instruction were conducted to diagnose the mental workload. The measurement of the initial mental workload condition of data entry employees was conducted in the laboratory. Then, the Electroencephalogram (EEG) measurement using sensors from Emotiv was performed every 30 minutes, and the data of EEG measurements (focus, engagement, and stress) were collected using the laptop. Meanwhile, pulse measurement (heart rate) was measured before and after the work. Raw National Aeronautics and Space Administration Task Load Index (NASA-TLX) and reaction time measurement were conducted after the work. Through these experiments, the researchers identify that mental effort and fatigue are the significant determinants of mental workload value in the data entry process of the e-commerce industry. In respect of the results of work performance analysis, it is recommended that the placement of work instruction should be near the employee. Then, the task demand (minimum completion target) should be adjusted according to each employee’s capacity.

scholarly journals A Systematic Review of Physiological Measures of Mental Workload

2019 ◽  
Vol 16 (15) ◽  
pp. 2716 ◽  
Author(s):  
Da Tao ◽  
Haibo Tan ◽  
Hailiang Wang ◽  
Xu Zhang ◽  
Xingda Qu ◽  
...  
Keyword(s):  
Eye Movement ◽  
Human Performance ◽  
Mental Workload ◽  
Empirical Studies ◽  
Physiological Measures ◽  
Comprehensive Understanding ◽  
Machine Systems ◽  
Electroencephalogram Eeg ◽  
Research Domains ◽  
Selection Of

Mental workload (MWL) can affect human performance and is considered critical in the design and evaluation of complex human-machine systems. While numerous physiological measures are used to assess MWL, there appears no consensus on their validity as effective agents of MWL. This study was conducted to provide a comprehensive understanding of the use of physiological measures of MWL and to synthesize empirical evidence on the validity of the measures to discriminate changes in MWL. A systematical literature search was conducted with four electronic databases for empirical studies measuring MWL with physiological measures. Ninety-one studies were included for analysis. We identified 78 physiological measures, which were distributed in cardiovascular, eye movement, electroencephalogram (EEG), respiration, electromyogram (EMG) and skin categories. Cardiovascular, eye movement and EEG measures were the most widely used across varied research domains, with 76%, 66%, and 71% of times reported a significant association with MWL, respectively. While most physiological measures were found to be able to discriminate changes in MWL, they were not universally valid in all task scenarios. The use of physiological measures and their validity for MWL assessment also varied across different research domains. Our study offers insights into the understanding and selection of appropriate physiological measures for MWL assessment in varied human-machine systems.

scholarly journals MENTAL WORKLOAD OF AIR TRAFFIC CONTROL (ATC) PERSONNEL AT ADISUTJIPTO INTERNATIONAL AIRPORT

Vortex ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 57
Author(s):  
Via Choirul Seftiyana
Keyword(s):  
Traffic Control ◽  
Negative Impact ◽  
Mental Workload ◽  
Air Traffic ◽  
High Concentration ◽  
Task Load ◽  
Mental Demand ◽  
Air Traffic Controllers ◽  
The Right ◽  
A Company

Air traffic controllers are under excessive stress because of their job. This has been linked to aspects of ATC work such as high job demands, time or responsibility pressure, or inadequate equipment. Types of work that require more vigilance, such as air traffic controllers at airports, are closely related to mental jobs that require high concentration. Because there is a negative impact on a company if it gives mental workload too high or too low for its employees, it is necessary to measure it to find out the right mental workload for its employees. This study aims to calculate the mental workload felt by ATC personnel in the APP unit. Measurement of mental workload in this study using the NASA-TLX (National Aeronautics and Space Administration Task Load Index). This method measures 6 (six) dimensions of workload size, namely Mental Demand, Physical Demand, Temporal Demand, Performance, Effort and Frustation Level

Context Effects in Subjective Mental Workload Ratings

1998 ◽  
Vol 40 (4) ◽  
pp. 591-600 ◽  
Author(s):  
Herbert A. Colle ◽  
Gary B. Reid
Keyword(s):  
Task Difficulty ◽  
Context Effect ◽  
Context Effects ◽  
Mental Workload ◽  
Task Load ◽  
Potential Applications ◽  
Performance Context ◽  
Nasa Task Load Index ◽  
The Impact ◽  
High Range

The impact of performance context on subjective mental workload ratings was assessed with the Subjective Workload Assessment Technique (SWAT) and the NASA Task Load Index (TLX). In Experiment 1, a strong context effect was demonstrated. A low range of task difficulty produced considerably higher ratings on a common set of difficulty levels than did a high range of task difficulty. In Experiment 2, increasing the participants′ range of experiences during practice eliminated the context effect. We recommend that methods for standardizing context, such as providing experience with the complete difficulty range, be developed for subjective mental workload evaluations. Actual or potential applications of this research include providing methodologies for controlling context effects in practical assessments of mental workload to increase the validity of subjective measures.

scholarly journals Mental Workload Estimation Based on Physiological Features for Pilot-UAV Teaming Applications

2021 ◽  
Vol 15 ◽  
Author(s):  
Gaganpreet Singh ◽  
Caroline P. C. Chanel ◽  
Raphaëlle N. Roy
Keyword(s):  
Classification Accuracy ◽  
Mental Workload ◽  
Subject Classification ◽  
Support Vector ◽  
Physiological Measures ◽  
Significant Drop ◽  
Linear Discriminant ◽  
Physiological Signal ◽  
Cooperative Team ◽  
The Impact

Manned-Unmanned Teaming (MUM-T) can be defined as the teaming of aerial robots (artificial agents) along with a human pilot (natural agent), in which the human agent is not an authoritative controller but rather a cooperative team player. To our knowledge, no study has yet evaluated the impact of MUM-T scenarios on operators' mental workload (MW) using a neuroergonomic approach (i.e., using physiological measures), nor provided a MW estimation through classification applied on those measures. Moreover, the impact of the non-stationarity of the physiological signal is seldom taken into account in classification pipelines, particularly regarding the validation design. Therefore this study was designed with two goals: (i) to characterize and estimate MW in a MUM-T setting based on physiological signals; (ii) to assess the impact of the validation procedure on classification accuracy. In this context, a search and rescue (S&R) scenario was developed in which 14 participants played the role of a pilot cooperating with three UAVs (Unmanned Aerial Vehicles). Missions were designed to induce high and low MW levels, which were evaluated using self-reported, behavioral and physiological measures (i.e., cerebral, cardiac, and oculomotor features). Supervised classification pipelines based on various combinations of these physiological features were benchmarked, and two validation procedures were compared (i.e., a traditional one that does not take time into account vs. an ecological one that does). The main results are: (i) a significant impact of MW on all measures, (ii) a higher intra-subject classification accuracy (75%) reached using ECG features alone or in combination with EEG and ET ones with the Adaboost, Linear Discriminant Analysis or the Support Vector Machine classifiers. However this was only true with the traditional validation. There was a significant drop in classification accuracy using the ecological one. Interestingly, inter-subject classification with ecological validation (59.8%) surpassed both intra-subject with ecological and inter-subject with traditional validation. These results highlight the need for further developments to perform MW monitoring in such operational contexts.

The Impact of Visual Feedback Type on the Mastery of Visuo-Motor Transformations

2012 ◽  
Vol 220 (1) ◽  
pp. 3-9 ◽  
Author(s):  
Sandra Sülzenbrück
Keyword(s):  
Empirical Research ◽  
Visual Feedback ◽  
Closed Loop ◽  
Motor Planning ◽  
Visual Input ◽  
Closed Loop Control ◽  
Loop Control ◽  
Feedback Type ◽  
Effective Use ◽  
The Impact

For the effective use of modern tools, the inherent visuo-motor transformation needs to be mastered. The successful adjustment to and learning of these transformations crucially depends on practice conditions, particularly on the type of visual feedback during practice. Here, a review about empirical research exploring the influence of continuous and terminal visual feedback during practice on the mastery of visuo-motor transformations is provided. Two studies investigating the impact of the type of visual feedback on either direction-dependent visuo-motor gains or the complex visuo-motor transformation of a virtual two-sided lever are presented in more detail. The findings of these studies indicate that the continuous availability of visual feedback supports performance when closed-loop control is possible, but impairs performance when visual input is no longer available. Different approaches to explain these performance differences due to the type of visual feedback during practice are considered. For example, these differences could reflect a process of re-optimization of motor planning in a novel environment or represent effects of the specificity of practice. Furthermore, differences in the allocation of attention during movements with terminal and continuous visual feedback could account for the observed differences.

scholarly journals Impacts of COVID-19 on Animals in Zoos: A Longitudinal Multi-Species Analysis

2021 ◽  
Vol 2 (2) ◽  
pp. 130-145
Author(s):  
Ellen Williams ◽  
Anne Carter ◽  
Jessica Rendle ◽  
Samantha J. Ward
Keyword(s):  
Holistic Approach ◽  
Physiological Measures ◽  
Environmental Interactions ◽  
Species Analysis ◽  
Zoo Animals ◽  
Animal Interaction ◽  
Chinese Goral ◽  
Grevy’S Zebra ◽  
The Impact ◽  
Swamp Wallaby

Prolonged and repetitive COVID-19 facility closures have led to an abrupt cessation of visitors within UK and Irish zoos for variable periods since March 2020. This study sought to increase understanding of the impact of closures and reopenings on animal behaviour, thereby broadening understanding of whether zoo animals habituate to visitors. Data were collected from June to August 2020 at two UK facilities on eight species (n = 1 Chinese goral, n = 2 Grevy’s zebra, n = 11 swamp wallaby, n = 2 Rothschild’s giraffe, n = 2 nyala, n = 4 Chapman’s zebra, n = 2 snow leopard and n = 3 Amur leopard). Behaviour change and enclosure use was variable across species but most changes were non-significant. Grevy’s zebra engaged in more comfort behaviour during closure periods than post-closure (p < 0.05). Chinese goral engaged in more environmental interactions during closure periods (p < 0.05). Grevy’s zebra spent longer than would be expected by chance closest to public viewing areas during closure periods (p < 0.008). These results suggest variable impacts of covid-19 closures and reopenings, mirroring human-animal interaction literature. We highlight the potential for some species to take longer to re-habituate to the presence of zoo visitors. As facility closures/reopenings are ongoing, we advocate a longitudinal monitoring approach. Furthermore, we recommend incorporation of physical and physiological measures of welfare where possible, alongside behavioural responses, to enable a holistic approach to answering fundamental questions on whether zoo animals habituate to visitors.

scholarly journals Research on Closed-Loop Supply Chain Decision-Making in Different Cooperation Modes with Government’s Reward-Penalty Mechanism

2021 ◽  
Vol 13 (11) ◽  
pp. 6425
Author(s):  
Quanxi Li ◽  
Haowei Zhang ◽  
Kailing Liu
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Stackelberg Game ◽  
Recycling Rate ◽  
Transfer Payment ◽  
Closed Loop Supply Chain ◽  
Asymmetry Of Information ◽  
Optimal Decisions ◽  
The Government ◽  
The Impact

In closed-loop supply chains (CLSC), manufacturers, retailers, and recyclers perform their duties. Due to the asymmetry of information among enterprises, it is difficult for them to maximize efficiency and profits. To maximize the efficiency and profit of the CLSC, this study establishes five cooperation models of CLSC under the government‘s reward–penalty mechanism. We make decisions on wholesale prices, retail prices, transfer payment prices, and recovery rates relying on the Stackelberg game method and compare the optimal decisions. This paper analyzes the impact of the government reward-penalty mechanism on optimal decisions and how members in CLSC choose partners. We find that the government’s reward-penalty mechanism can effectively increase the recycling rate of used products and the total profit of the closed-loop supply chain. According to the calculation results of the models, under the government’s reward-penalty mechanism, the cooperation can improve the CLSC’s used products recycling capacity and profitability. In a supply chain, the more members participate in the cooperation, the higher profit the CLSC obtain. However, the cooperation mode of all members may lead to monopoly, which is not approved by government and customers.

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