Dr. Michael E. Smith Profile

Dr. Michael E. Smith

Principal Neuroscientist at SAM Technology Inc

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Proceedings Article | 23 May 2005 Paper

Assessing fitness-for-duty and predicting performance with cognitive neurophysiological measures

Michael Smith, Alan Gevins

Proceedings Volume 5797, (2005) https://doi.org/10.1117/12.602185

KEYWORDS: Electroencephalography, Brain, Statistical analysis, Neodymium, Brain activation, Neural networks, Electrophysiological tests, Psychoactive substances, Traumatic brain injury, Reliability

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Progress is described in developing a novel test of neurocognitive status for fitness-for-duty testing. The Sustained Attention & Memory (SAM) test combines neurophysiologic (EEG) measures of brain activation with performance measures during a psychometric test of sustained attention and working memory, and then gauges changes in neurocognitive status relative to an individual’s normative baseline. In studies of the effects of common psychoactive substances that can affect job performance, including sedating antihistamines, caffeine, alcohol, marijuana, and prescription medications, test sensitivity was greater for the combined neurophysiological and performance measures than for task performance measures by themselves. The neurocognitive effects of overnight sleep deprivation were quite evident, and such effects predicted subsequent performance impairment on a flight simulator task. Sensitivity to diurnal circadian variations was also demonstrated. With further refinement and independent validation, the SAM Test may prove useful for assessing readiness-to-perform in high-asset personnel working in demanding, high risk situations.

Proceedings Article | 23 May 2005 Paper

Neurophysiologic monitoring of mental workload and fatigue during operation of a flight simulator

Michael Smith, Alan Gevins

Proceedings Volume 5797, (2005) https://doi.org/10.1117/12.602181

KEYWORDS: Cortical activation, Electroencephalography, Brain, Visualization, Sensors, Process control, Neuroimaging, Brain activation, Signal detection, Modulation

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In one experiment, EEG recordings were made during a daytime session while 16 well-rested participants performed versions of a PC flight simulator task that were either low, moderate, or high in difficulty. In another experiment, the same subjects repeatedly performed high difficulty versions of the same task during an all night session with total sleep deprivation. Multivariate EEG metrics of cortical activation were derived for frontal brain regions essential for working memory and executive control processes that are presumably important for maintaining situational awareness, central brain regions essential for sensorimotor control, and posterior parietal and occipital regions essential for visuoperceptual processing. During the daytime session each of these regional measures displayed greater activation during the high difficulty task than during the low difficulty task, and degree of cortical activation was positively correlated with subjective workload ratings in these well-rested subjects. During the overnight session, cortical activation declined with time-on-task, and the degree of this decline over frontal regions was negatively correlated with subjective workload ratings. Since participants were already highly skilled in the task, such changes likely reflect fatigue-related diminishment of frontal executive capability rather than practice effects. These findings suggest that the success of efforts to gauge mental workload via proxy cortical activation measures in the context of adaptive automation systems will likely depend on use of user models that take both task demands and the operator’s state of alertness into account. Further methodological development of the measurement approach outlined here would be required to achieve a practical, effective objective means for monitoring transient changes in cognitive brain function during performance of complex real-world tasks.

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