Arash

Arash

M.Sc in Mechatronics Engineering at K.N. Toosi University of Technology

Posts by Collection

portfolio

publications

Towards Cognitive Load Assessment Using Electrooculography Measures

Published in arXiv, 2023

Cognitive load assessment is crucial for understanding human performance in various domains. This study investigates the impact of different task conditions and time constraints on cognitive load using multiple measures, including subjective evaluations, performance metrics, and physiological eye-tracking data. Fifteen participants completed a series of primary and secondary tasks with different time limits. The NASA-TLX questionnaire, reaction time, inverse efficiency score, and eye-related features (blink, saccade, and fixation frequency) were utilized to assess cognitive load. The study results show significant differences in the level of cognitive load required for different tasks and when under time constraints. The study also found that there was a positive correlation (r = 0.331, p = 0.014) between how often participants blinked their eyes and the level of cognitive load required but a negative correlation (r = -0.290, p = 0.032) between how often participants made quick eye movements (saccades) and the level of cognitive load required. Additionally, the analysis revealed a significant negative correlation (r = -0.347, p = 0.009) and (r = -0.370, p = 0.005) between fixation and saccade frequencies under time constraints.

Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf

Towards Cognitive Load Assessment Using Electrooculography Measures

Published in arXiv, 2023

Cognitive load assessment is crucial for understanding human performance in various domains. This study investigates the impact of different task conditions and time constraints on cognitive load using multiple measures, including subjective evaluations, performance metrics, and physiological eye-tracking data. Fifteen participants completed a series of primary and secondary tasks with different time limits. The NASA-TLX questionnaire, reaction time, inverse efficiency score, and eye-related features (blink, saccade, and fixation frequency) were utilized to assess cognitive load. The study results show significant differences in the level of cognitive load required for different tasks and when under time constraints. The study also found that there was a positive correlation (r = 0.331, p = 0.014) between how often participants blinked their eyes and the level of cognitive load required but a negative correlation (r = -0.290, p = 0.032) between how often participants made quick eye movements (saccades) and the level of cognitive load required. Additionally, the analysis revealed a significant negative correlation (r = -0.347, p = 0.009) and (r = -0.370, p = 0.005) between fixation and saccade frequencies under time constraints.

Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf

Towards Cognitive Load Assessment Using Electrooculography Measures

Published in arXiv, 2023

Cognitive load assessment is crucial for understanding human performance in various domains. This study investigates the impact of different task conditions and time constraints on cognitive load using multiple measures, including subjective evaluations, performance metrics, and physiological eye-tracking data. Fifteen participants completed a series of primary and secondary tasks with different time limits. The NASA-TLX questionnaire, reaction time, inverse efficiency score, and eye-related features (blink, saccade, and fixation frequency) were utilized to assess cognitive load. The study results show significant differences in the level of cognitive load required for different tasks and when under time constraints. The study also found that there was a positive correlation (r = 0.331, p = 0.014) between how often participants blinked their eyes and the level of cognitive load required but a negative correlation (r = -0.290, p = 0.032) between how often participants made quick eye movements (saccades) and the level of cognitive load required. Additionally, the analysis revealed a significant negative correlation (r = -0.347, p = 0.009) and (r = -0.370, p = 0.005) between fixation and saccade frequencies under time constraints.

Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf

Towards Cognitive Load Assessment Using Electrooculography Measures

Published in arXiv, 2023

Cognitive load assessment is crucial for understanding human performance in various domains. This study investigates the impact of different task conditions and time constraints on cognitive load using multiple measures, including subjective evaluations, performance metrics, and physiological eye-tracking data. Fifteen participants completed a series of primary and secondary tasks with different time limits. The NASA-TLX questionnaire, reaction time, inverse efficiency score, and eye-related features (blink, saccade, and fixation frequency) were utilized to assess cognitive load. The study results show significant differences in the level of cognitive load required for different tasks and when under time constraints. The study also found that there was a positive correlation (r = 0.331, p = 0.014) between how often participants blinked their eyes and the level of cognitive load required but a negative correlation (r = -0.290, p = 0.032) between how often participants made quick eye movements (saccades) and the level of cognitive load required. Additionally, the analysis revealed a significant negative correlation (r = -0.347, p = 0.009) and (r = -0.370, p = 0.005) between fixation and saccade frequencies under time constraints.

Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf

Preliminary Guidelines for Electrode Positioning in Noninvasive Deep Brain Stimulation via Temporally Interfering Electric Fields

Published in IEEE, 2023

Advancements in neurosurgical robotics have improved medical procedures, particularly deep brain stimulation, where robots combine human and machine intelligence to precisely implant electrodes in the brain. While effective, this procedure carries risks and side effects. Noninvasive deep brain stimulation (NIDBS) offers promise by making brain stimulation safer, more affordable, and accessible. However, NIDBS lacks guidelines for electrode placement. This study explores adapting robotic principles to enhance the accuracy of NIDBS targeting and provides preliminary guidelines for transcranial electrode placement. Safety is also emphasized, ensuring a balance between therapeutic effectiveness and patient safety by maintaining electric fields within safe limits.

Recommended citation: Mobina Zibandepour, Akram Shojaei, Arash Abbasi Larki, and Mehdi Delrobaei. ”Preliminary Guidelines for Electrode Positioning in Noninvasive Deep Brain Stimulation via Temporally Interfering Electric Fields” 2023 11th RSI International Conference on Robotics and Mechatronics (ICRoM), Tehran, Iran, Islamic Republic of, 2023, pp. 739-744. https://ieeexplore.ieee.org/abstract/document/10412364

IMU-Based Motion Capture Data for Various Walking Tasks

Published in Figshare, 2024

This dataset contains motion capture data collected from 11 healthy subjects performing various walking tasks using IMU-based sensors. Each subject performed 8 different tasks.

Recommended citation: Akram Shojaei, Arash Abbasi Larki, Mehdi Delrobaei, Hanieh Moradi, and Yas Vaseghi. "IMU-Based Motion Capture Data for Various Walking Tasks" figshare, 24-Jun-2024. https://figshare.com/articles/dataset/IMU-Based_Motion_Capture_Data_for_Various_Walking_Tasks/26090200

talks

teaching

Neuromuscular Control Systems

Graduate course, Electrical Engineering Department, K.N. Toosi University of Technology, 2023

  • Data collecting using a motion capture device for the course project and assisting students with their projects
  • Grading assignments

Biomechatronics Systems

Graduate course, Electrical Engineering Department, K.N. Toosi University of Technology, 2023

  • Assisting students with course projects to use COMSOL to simulate the Electrical brain stimulation
  • Organizing lecture notes, grading assignments, and conducting meetings with students