Ehsan Rashedi Headshot

Ehsan Rashedi

Assistant Professor

Department of Industrial and Systems Engineering
Kate Gleason College of Engineering
Ergonomics/Human Factors
exreie@rit.edu
585-475-7260
Office Location
GLE-1598

Ehsan Rashedi

Assistant Professor

Department of Industrial and Systems Engineering
Kate Gleason College of Engineering
Ergonomics/Human Factors

Education

BS, MS, Sharif University of Technology (Iran); MS, Ph.D., Virginia Polytechnic Institute and State University

Bio

Dr. Ehsan Rashedi is director of Occupational Ergonomics and Biomechanics Laboratory in Industrial and Systems Engineering Department. His research interests include both theoretical and application-oriented research topics, covering several aspects within the fields of ergonomics, biomechanics, work physiology, safety, and rehabilitation.

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exreie@rit.edu
585-475-7260
Personal Links
ORCID
Google Scholar
Areas of Expertise
Physical Ergonomics
Biomechanics
Product Design and Evaluation
Wearable Technology
Human Factors
Fatigue Monitoring
Fall Risk Assessment
Gesture Recognition
Data Analytics

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Published Conference Proceedings
Karvekar, Swapnali, Masoud Abdollahi, and Ehsan Rashedi. "A Data-Driven Model to Identify Fatigue Level Based on the Motion Data from a Smartphone." Proceedings of the 2019 IEEE Western New York Image and Signal Processing. Ed. IEEE. Rochester, NY: n.p., Web.
Rashedi, Ehsan, et al. "Classification of LBP Patients Using an IMU Signal and Machine Learning Approaches." Proceedings of the American Society of Biomechanics Annual Meeting. Ed. ASB. Calgary, Canada: n.p., Web.
Katawala, Kavish, et al. "Effects of Slip and Trip on Low Back and the Resulting Lumbar Muscle Activity, Low Back Loads." Proceedings of the Institute of Industrial Engineering Annual Conference and Expo. Ed. IISE. Orlando, FL: n.p., Web.
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Peer Reviewed/Juried Poster Presentation or Conference Paper
Karvekar, Swapnali, Masoud Abdollahi, and Ehsan Rashedi. "Smartphone-based Human Fatigue Detection for Daily Activities Using Gait Analysis." Proceedings of the Applied Human Factors and Ergonomics. Ed. AHFE. Washington, DC: n.p..
Journal Paper
Esfahani, Mohammad Iman Mokhlespour, et al. "Sharif-Human movement instrumentation system (SHARIF-HMIS): Development and validation." Medical Engineering & Physics 61. (2018): 87-94. Print.
Kim, Sunwook, et al. "Assessing the influence of a passive, upper extremity exoskeletal vest for tasks requiring arm elevation: Part I – “Expected” effects on discomfort, shoulder muscle activity, and work task performance." Applied Ergonomics 70. (2018): 315-322. Print.
Kim, Sunwook, et al. "Assessing the influence of a passive, upper extremity exoskeletal vest for tasks requiring arm elevation: Part II – “Unexpected” effects on shoulder motion, balance, and spine loading." Applied Ergonomics 70. (2018): 323-330. Print.
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Currently Teaching

ISEE-330
Ergonomics and Human Factors
4 Credits
This course covers the physical and cognitive aspects of human performance to enable students to design work places, procedures, products and processes that are consistent with human capabilities and limitations. Principles of physical work and human anthropometry are studied to enable the student to systematically design work places, processes, and systems that are consistent with human capabilities and limitations. In addition, the human information processing capabilities are studied, which includes the human sensory, memory, attention and cognitive processes; display and control design principles; as well as human computer interface design.
ISEE-730
Data-Driven Human Biomechanics
3 Credits
Topics include musculoskeletal anatomy and mechanics, theory and application of electromyography, motion and force measuring equipment and techniques, human locomotion, balance and falls, inverse dynamics modeling of the human body, and current topics in musculoskeletal biomechanics research. Students collect data in the lab and conduct the data analysis using MATLAB software or Python software.
ISEE-760
Design of Experiments
3 Credits
This course presents an in-depth study of the primary concepts of experimental design. Its applied approach uses theoretical tools acquired in other mathematics and statistics courses. Emphasis is placed on the role of replication and randomization in experimentation. Numerous designs and design strategies are reviewed and implications on data analysis are discussed. Topics include: consideration of type 1 and type 2 errors in experimentation, sample size determination, completely randomized designs, randomized complete block designs, blocking and confounding in experiments, Latin square and Graeco Latin square designs, general factorial designs, the 2k factorial design system, the 3k factorial design system, fractional factorial designs, Taguchi experimentation.

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