Key result
Physiological mental workload measures help predict human performance but lack formal reliability assessments.
Why the study?
Mental workload assessment aims to predict and understand human performance variations under changing system demands, but formal reliability assessments of physiological measures have been lacking.
This review outlines the utility of physiological metrics like MEG and EEG in evaluating mental workload, emphasizing the need for more rigorous reliability testing.
Answers are grounded in this paper and cite their sources.
Physiological mental workload metrics warrant caution before clinical use due to absent reliability data; leaves open formal validation studies for cardiovascular performance monitoring.
The ultimate goal of mental workload assessment is the prediction and understanding of variations in human performance in response to changes in system demands. This chapter describes some of the advantages of physiological measures of mental workload. Two general classes of physiological measures are examined in review of measures of mental workload: central nervous system measures (CNS) and peripheral nervous system measures. The boundaries between the CNS and the peripheral nervous system are based on anatomical distinctions. The Magnetoencephlographic activity technique provides information that complements Electroencephalographic Activity and event-related brain potentials and offers the potential for enhancing our understanding of the relationship between neurophysiological concepts of capacity and the psychological concept of mental workload. As with many physiological measures, there has been a lack of formal assessment of reliability, especially as it pertains to evaluations of mental workload.
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Arthur F. Kramer (2020) conducted a review in Mental workload. Physiological measures of mental workload was evaluated. Physiological measures of mental workload, including central and peripheral nervous system metrics, offer advantages for predicting human performance but lack formal reliability assessment.
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