Model-based development of a mental workload-sensitivity index for subject clustering

Fürstenau, Norbert; Radüntz, Thea; Mühlhausen, Thorsten

doi:10.1080/1463922x.2020.1711990

Cited by 5 publications

(23 citation statements)

References 19 publications

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“…Subject's normalized workload-sensitivity index s a was based on a linear model for the dependence of subjectively experienced workload as assessed by the ISA questionnaire and traffic load. In Fürstenau et al (2020), we showed that the linear model was able to predict the ISA value with a high confidence for means across the subjects and provided reasonable linear correlation coefficients for the individuals. Independence from the arbitrary ISA values was achieved via normalization by scales' means, i.e., (traffic load max + traffic load min ) / 2 for the traffic volume and (ISA max + ISA min ) / 2 for the subjective workload, resulting in anticorrelated (normalized) sensitivity and intercept s b = 1 − s a .…”

Section: Subjective Ratingsmentioning

confidence: 80%

Indexing Mental Workload During Simulated Air Traffic Control Tasks by Means of Dual Frequency Head Maps

et al. 2020

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In our digitized society, advanced information and communication technology and highly interactive work environments impose high demands on cognitive capacity. Optimal workload conditions are important for assuring employee's health and safety of other persons. This is particularly relevant in safety-critical occupations, such as air traffic control. For measuring mental workload using the EEG, we have developed the method of Dual Frequency Head Maps (DFHM). The method was tested and validated already under laboratory conditions. However, validation of the method regarding reliability and reproducibility of results under realistic settings and real world scenarios was still required. In our study, we examined 21 air traffic controllers during arrival management tasks. Mental workload variations were achieved by simulation scenarios with different number of aircraft and the occurrence of a priority-flight request as an exceptional event. The workload was assessed using the EEG-based DFHM-workload index and instantaneous self-assessment questionnaire. The DFHM-workload index gave stable results with highly significant correlations between scenarios with similar traffic-load conditions (r between 0.671 and 0.809, p ≤ 0.001). For subjects reporting that they experienced workload variation between the different scenarios, the DFHM-workload index yielded significant differences between traffic-load levels and priority-flight request conditions. For subjects who did not report to experience workload variations between the scenarios, the DFHM-workload index did not yield any significant differences for any of the factors. We currently conclude that the DFHM-workload index reveals potential for applications outside the laboratory and yields stable results without retraining of the classifiers neither regarding new subjects nor new tasks.

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Section: Subjective Ratingsmentioning

confidence: 80%

Indexing Mental Workload During Simulated Air Traffic Control Tasks by Means of Dual Frequency Head Maps

et al. 2020

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“…4.1, we assume an equidistant ISA scale so that any deviation from linearity is included in the nonlinearities of the model equations. In a recent publication, we provided evidence for the logistic dependence of ISA-WL on the environmental traffic load variable n and derived a linearized ISA-WL-sensitivity index for subject clustering (Fürstenau et al 2020). The subjective index was successfully applied for the validation of the neurophysiological DFHM WL index (Sect.…”

Section: Subjective Quasi Real-time Measuresmentioning

confidence: 99%

“…For testing the DFHM-WL index sensitivity, the participants in this analysis were separated into two groups (low and high WL sensitivity) according to their individual linearized WLsensitivity parameters that were formally derived from the logistic ISA characteristic of the subjective self-report measures. Fürstenau et al (2020). In Sects.…”

Section: Neurophysiological (Eeg-based) Measuresmentioning

confidence: 99%

“…For the theoretical modeling and data analysis, we used as dependent variables the scenario means < ISA > (n j ) and < RC > (n j ) calculated over the whole time series as WLrating and TL-value estimate, respectively, for each participant in the eight scenarios. Tables with pre-processed raw data and results for individual participants are provided in our previous publication (Fürstenau et al 2020) and in Appendix 1 for completeness. In what follows, we restrict the theoretical predictions, regression analysis and discussion to the means across the 21 subjects.…”

Section: Experimental Design and Workload Assessmentmentioning

confidence: 99%

“…For this purpose, we validate the theoretically derived power law relationship between the quasi real-time onedimensional subjective Instantaneous Self Assessment workload measure (ISA-WL) (Kirwan et al 1997;Jordan 1992;Brennan 1992;Tattersall and Foord 1996) and the objective communication task load variable (frequency of ATCO's radio calls, RC-TL) as mediator between WL and environmental traffic load, by means of a human-in-theloop (HitL) ATC-simulation experiment (Mühlhausen et al 2018). Thereby, we formally combine the logistic RC-TL model with the recently published logistic WL model that was used for the analysis of the subjective ratings of operators (Fürstenau et al 2020). In that previous work, we recorded during execution of the simulated ATC task, the periodic reporting of the subjectively experienced WL level as dependent on environmental load variable traffic flow n (aircraft per hour, AC/h), by means of the online five-level ISA questionnaire.…”

Section: Introductionmentioning

confidence: 99%

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Power law model for subjective mental workload and validation through air traffic control human-in-the-loop simulation

Fürstenau

Radüntz

2021

Cogn Tech Work

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We provide evidence for a power law relationship between the subjective one-dimensional Instantaneous Self Assessment workload measure (five-level ISA-WL scale) and the radio communication of air traffic controllers (ATCOs) as an objective task load variable. It corresponds to Stevens’ classical psychophysics relationship between physical stimulus and subjective response, with characteristic power law exponent γ of the order of 1. The theoretical model was validated in a human-in-the loop air traffic control simulation experiment with traffic flow as environmental stimulus that correlates positively with ATCOs frequency and duration of radio calls (task load, RC-TL) and their reported ISA-WL. The theoretical predictions together with nonlinear regression-based model parameter estimates expand previously published results that quantified the formal logistic relationship between the subjective ISA measure and simulated air traffic flow (Fürstenau et al. in Theor Issues Ergon Sci 21(6): 684–708, 2020). The present analysis refers to a psychophysics approach to mental workload suggested by (Gopher and Braune in Hum Factors 26(5): 519–532, 1984) that was recently used by (Bachelder and Godfroy-Cooper in Pilot workload esimation: synthesis of spectral requirements analysis and Weber's law, SCL Tech, San Diego, 2019) for pilot workload estimation, with a corresponding power law exponent in the typical range of Stevens’ exponents. Based on the hypothesis of cognitive resource limitation, we derived the power law by combination of the two logistic models for ISA-WL and communication TL characteristics, respectively. Despite large inter-individual variance, the theoretically predicted logistic and power law parameter values exhibit surprisingly close agreement with the regression-based estimates (for averages across participants). Significant differences between logistic ISA-WL and RC-TL scaling parameters and the corresponding Stevens exponents as ratio of these parameters quantify the TL/WL dissociation with regard to traffic flow. The sensitivity with regard to work conditions of the logistic WL-scaling parameter as well as the power law exponent was revealed by traffic scenarios with a non-nominal event: WL sensitivity increased significantly for traffic flow larger than a critical value. Initial analysis of a simultaneously measured new neurophysiological (EEG) load index (dual frequency head maps, DFHM, (Radüntz in Front Physiol 8: 1–15, 2017)) provided evidence for the power law to be applicable to the DFHM load measure as well.

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Model Based Analysis of Subjective Mental Workload During Multiple Remote Tower Human-In-The-Loop Simulations

Fürstenau

Papenfuß

2022

Virtual and Remote Control Tower

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Model-based development of a mental workload-sensitivity index for subject clustering

Cited by 5 publications

References 19 publications

Indexing Mental Workload During Simulated Air Traffic Control Tasks by Means of Dual Frequency Head Maps

Indexing Mental Workload During Simulated Air Traffic Control Tasks by Means of Dual Frequency Head Maps

Power law model for subjective mental workload and validation through air traffic control human-in-the-loop simulation

Model Based Analysis of Subjective Mental Workload During Multiple Remote Tower Human-In-The-Loop Simulations

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