Chaeyoung Lee, MinJu Shin, David Eniyandunmo, Alvee Anwar, Eunsik Kim, Kyongwon Kim, Jae Keun Yoo, Chris Lee
This study investigates the impact of advanced driver-assistance systems on drivers' mental workload. Using a combination of physiological signals including ECG, EMG, EDA, EEG (af4 and fc6 channels from the theta band), and eye diameter data, this study aims to predict and categorize drivers' mental workload into low, adequate, and high levels. Data were collected from five different driving situations with varying cognitive demands. A functional linear regression model was employed for prediction, and the accuracy rate was calculated...
March 22, 2024: Applied Ergonomics