Ph.D. Mechanical Engineering, University of Utah (2021)
M.S. Mechatronics Engineering, University of Tehran (2014)
B.S. Mechanical Engineering In Fluid Dynamic and Heat Transfer- Shahrood University of Technology (2011)
Lab: MEB 2210
Current Research: Investigating the Effect of Awareness System on the Smart Helmet Project
Directional Auditory Signal on head impact: Smart Helmet project is a NSF funded project and consist of 7 different groups. The aim of this project is to reduce the risk of concussion for American football players during the game and practice. As it has been mentioned in the literature, the risk of concussion is related to the amount of head acceleration after the impact. In this end of the project, we want to see the effect of neck muscle contraction following by a directional auditory signal on the reduction of head acceleration after impact. To investigate the effect of the directional auditory signal, we develop a testbed that simulate a controlled mild impact to the head of person and we are measuring the acceleration of the head and muscle activation using EMG system. Another aim of this project is to investigate what is the best latency between the sound and the impact.
Directional Auditory Signal on body impact: As an extension to the Directional Auditory Signal on head impact, this project has been designed. The aim of this project is to determine the effect of directional auditory signal for the players to react to hip perturbation during running. In this testbed, multiple perturbations are going to be applied to the subject in different position of the stride with and without audio signal before the perturbation to see whether it helps the person to maintain his/her balance on the treadmill or not.
Collision Detection in Football Field Using Deep Learning: The idea of the smart helmet project is based on collision detection estimation during the match. If we can increase the accuracy of the collision detection system and decrease the number of false alarms, the system will have the best performance. There are some parameters, like position of the ball, team formation and the player position, which can be defined as attributes for the system to increase the performance and accuracy of the estimation. The goal of this project is to modify a deep learning method for this application.
Research Interests: His research interests include Robotics, Biomechanics and Mechatronics
Personal Interests: He likes playing volleyball, soccer and hiking