Operations Research, Systems Engineering and Industrial Engineering Commons^™

Applying Functional Data Analysis To Estimate The Mental Workload Of The Human Driver, David Olorunfemi Eniyandunmo

Electronic Theses and Dissertations

Recent studies have focused on accurately estimating mental workload using machine learning algorithms and extracting features from psycho-physiological measures. However, feature extraction leads to the loss of valuable information and often results in binary classifications that lack specificity in the identification of optimum mental workload levels. This study investigates the feasibility of using raw psycho-physiological data (EEG, facial EMG, ECG, EDA, pupillometry) combined with Functional Data Analysis (FDA) to estimate mental workload of human drivers. A driving scenario with five tasks was employed, and subjective ratings were collected using the modified Bedford workload scale. Results demonstrate that the FDA applied …