Deployment of new technology at workplace has led to increased mental workload (MWL) for operators, adversely affecting performance and safety due to the disparity between an operator’s available cognitive resources and the demands imposed by a task. Extensive research employing subjective assessments, performance measures, physiological indicators, and task analyses has been conducted to evaluate MWL. The progression of neuroergonomics—a field that integrates neuroscience with ergonomics—has substantially expanded our understanding of cognitive strain. Neuroimaging techniques, particularly electroencephalography (EEG), have been instrumental in monitoring MWL in real-world situations. EEG provides direct, real-time measurements of brain activity with high temporal resolution, allowing for the detection of changes in mental states across different conditions. Specific brainwave patterns associated with MWL can be measured using EEG and are categorized by frequency bands. Beta waves (13–32 Hz) are linked to focused attention on cognitive tasks, problem-solving, and active thinking; elevated beta and decreasing alpha (8–13 Hz) activity often indicates increased mental workload. Understanding these neural correlates of mental workload enhances our ability to design technologies and tasks that optimize performance and promote safety.