8 citations · 10 across the 4 of their papers we have counts for
4 papers
Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis
Mehshan Ahmed Khan, Houshyar Asadi, Mohammad Reza Chalak Qazani +6
Functional near-infrared spectroscopy (fNIRS) is employed as a non-invasive method to monitor functional brain activation by capturing changes in the concentrations of oxygenated h…
Predicting cognitive load in immersive driving scenarios with a hybrid CNN-RNN model
Mehshan Ahmed Khan, Houshyar Asadi, Mohammad Reza Chalak Qazani +3
One debatable issue in traffic safety research is that cognitive load from sec-ondary tasks reduces primary task performance, such as driving. Although physiological signals have b…
Functional near-infrared spectroscopy (fNIRS) and Eye tracking for Cognitive Load classification in a Driving Simulator Using Deep Learning
Mehshan Ahmed Khan, Houshyar Asadi, Mohammad Reza Chalak Qazani +2
Motion simulators allow researchers to safely investigate the interaction of drivers with a vehicle. However, many studies that use driving simulator data to predict cognitive load…
A comparative and critical study of EEGNet for fNIRS-driven cognitive load classification
Mehshan Ahmed Khan, Houshyar Asadi, Li Zhang +8
Accurately classifying cognitive load from functional near-infrared spectroscopy (fNIRS) signals remains a significant challenge due to temporal variability, inter-subject differen…