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20242026
most citedEnhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis

8 citations · 10 across the 3 of their papers we have counts for

collaborators

7 papers

cs.LG20268 cited

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…

cs.HC20261 cited

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…

cs.HC20261 cited

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…

cs.RO2025

Learning-Based Approximate Nonlinear Model Predictive Control Motion Cueing

Camilo Gonzalez Arango, Houshyar Asadi, Mohammad Reza Chalak Qazani +1

Motion Cueing Algorithms (MCAs) encode the movement of simulated vehicles into movement that can be reproduced with a motion simulator to provide a realistic driving experience wit…

eess.SY2025

A nonlinear real time capable motion cueing algorithm based on deep reinforcement learning

Hendrik Scheidel, Camilo Gonzalez, Houshyar Asadi +4

In motion simulation, motion cueing algorithms are used for the trajectory planning of the motion simulator platform, where workspace limitations prevent direct reproduction of ref…

cs.RO2025

A Deep Reinforcement Learning Based Motion Cueing Algorithm for Vehicle Driving Simulation

Hendrik Scheidel, Houshyar Asadi, Tobias Bellmann +3

Motion cueing algorithms (MCA) are used to control the movement of motion simulation platforms (MSP) to reproduce the motion perception of a real vehicle driver as accurately as po…