Exploring Physiological Measures for Prediction and Identification of the Redline of Cognitive Workload
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Research suggests that physiological measures such as breath rate (BR), heart rate (HR), heart rate variability (HRV), skin conductance response (SCR), and electroencephalography (EEG) tend to be real-time indicators of mental workload, which are related with increases in the sympathetic nervous system. With increased cognitive workload, these physiological measures tend to change, until a plateau is reached. At this point, performance will decrease, as the workload imposed on the user exceeds their mental capacity to perform the task. This occurs when the user reaches their cognitive redline of workload. Performance will start to decline or decline more steeply at this point, as task demand imposed by the tasks is greater than the mental capacity. This thesis seeks to understand the underlying patterns reflected in the physiological data that can potentially be used as real-time indicators of the cognitive redline of workload. The study involved use of the Multi-Attribute Task Battery II (MATB-II) to manipulate workload. Subjective measures and performance were taken at the end of every scenario, while physiological measures (BR, HR, HRV, SCR, and EEG), and performance were analyzed to determine the cognitive redline. Results found subjective measures to be responsive to workload change, while heart rate variability seems to be the best physiological measure to respond to mental workload. EEG and SCR proved to also be reliable predictors.
Rodriguez Paras, Carolina (2015). Exploring Physiological Measures for Prediction and Identification of the Redline of Cognitive Workload. Master's thesis, Texas A & M University. Available electronically from