EEG Features to Quantify the NASA-TLX Factors of Cognitive Workload

Measuring cognitive workload (CWL) is crucial for dynamic task reallocation (i.e., adaptation) between a human and a machine in a human-machine system (HMS). A conventional measurement of the CWL is based on subjectively reported scores about the six factors of the NASA Task Load Index (NASA-TLX) questionnaire. The questionnaire cannot however capture real-time fluctuations of the factors for an objective quantification. Additionally, each of the factors is associated with distinct activities and can be influenced by individual characteristics and/or task contexts. Such HMS adaptation should thus consider the objective quantification of each factor. So far, the quantification remains largely unexplored, while existing studies reveal a potential use of an electroencephalography (EEG) in measuring the CWL levels (e.g., high, medium, and low). Herein, we presented a pioneering study to propose EEG features for quantifying the factors. The pertinence of the features was demonstrated by their strong correlations with the scores of the factors across three distinct cases of visuomotor tasks. The pertinence is the stepping stone toward factor-based interventions in enabling HMS adaptation.