Evaluation of mental workload with a combined measure based on physiological indices during a dual task of tracking and mental arithmetic

Kilseop Ryu, Rohae Myung

Research output: Contribution to journalArticle

199 Citations (Scopus)

Abstract

In this study, a combined measure was developed based on various physiological indices in order to evaluate the mental workload during a dual task. To determine the mental effort required for each task, three physiological signals were recorded while ten subjects performed different versions of a dual task composed of tracking and mental arithmetic. These signals were the electroencephalogram (EEG), electrooculogram (EOG), and electrocardiogram (ECG), which were transformed into the suppression of alpha rhythm, eye blink interval, and heart rate variability (HRV), respectively. The alpha suppression provided proper information to infer the efforts for the arithmetic task, but not for the tracking task. Conversely, the blink interval and HRV permitted detailed inferences over the workload of the tracking task, but not for the arithmetic task. These results can be explained in terms of the multiple resources model of workload. The processing indexed by the alpha suppression is inferred to be different from that indexed by the blink interval or HRV. Finally, the physiological measures were combined into a single measure using different weight coefficients. The newly developed measure systematically increased with the difficulty of each task and significantly distinguished between the different versions of each task. Relevance to industry A combined measure of mental workload that has the ability to evaluate operators' mental effort in a multitask condition would be valuable in a natural working environment, because most such work is composed of multiple tasks. In this paper, an approach is described that developed a combined measure of mental workload based on three physiological indices.

Original languageEnglish
Pages (from-to)991-1009
Number of pages19
JournalInternational Journal of Industrial Ergonomics
Volume35
Issue number11
DOIs
Publication statusPublished - 2005 Nov 1

Fingerprint

Workload
workload
suppression
evaluation
Heart Rate
Bioelectric potentials
Electroencephalography
Electrocardiography
Alpha Rhythm
Electrooculography
Processing
Industry
Weights and Measures
industry
ability
resources

Keywords

  • ECG
  • EEG
  • EOG
  • Factor analysis
  • Mental workload
  • Multiple regression analysis

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality
  • Human Factors and Ergonomics

Cite this

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abstract = "In this study, a combined measure was developed based on various physiological indices in order to evaluate the mental workload during a dual task. To determine the mental effort required for each task, three physiological signals were recorded while ten subjects performed different versions of a dual task composed of tracking and mental arithmetic. These signals were the electroencephalogram (EEG), electrooculogram (EOG), and electrocardiogram (ECG), which were transformed into the suppression of alpha rhythm, eye blink interval, and heart rate variability (HRV), respectively. The alpha suppression provided proper information to infer the efforts for the arithmetic task, but not for the tracking task. Conversely, the blink interval and HRV permitted detailed inferences over the workload of the tracking task, but not for the arithmetic task. These results can be explained in terms of the multiple resources model of workload. The processing indexed by the alpha suppression is inferred to be different from that indexed by the blink interval or HRV. Finally, the physiological measures were combined into a single measure using different weight coefficients. The newly developed measure systematically increased with the difficulty of each task and significantly distinguished between the different versions of each task. Relevance to industry A combined measure of mental workload that has the ability to evaluate operators' mental effort in a multitask condition would be valuable in a natural working environment, because most such work is composed of multiple tasks. In this paper, an approach is described that developed a combined measure of mental workload based on three physiological indices.",
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