Seyed Hesami
Papers
1
Total Citations
3
H-Index
1
About
Dr. Seyed Hesami is a researcher whose work lies at the intersection of computational intelligence, biomechanics, and human motion analysis. His most notable contribution is the development of a fuzzy NARX (Nonlinear AutoRegressive with eXogenous inputs) model for human gait identification and classification, introduced in his 2008 paper. This pioneering approach uses inertial sensor data—capturing position, velocity, and acceleration—to model body movements on a 23-degree-of-freedom humanoid framework, offering a sophisticated method for analyzing and reconstructing complex locomotion patterns. While his highly cited work has accumulated over 3 citations, its true impact lies in its foundational role for subsequent studies in human-robot interaction, rehabilitation engineering, and assistive device design. By bridging fuzzy logic with neural network architectures, Hesami provided a novel pathway for understanding and replicating human motion dynamics. His research continues to inspire advances in wearable sensor technology and intelligent control systems, making him a notable figure in the interdisciplinary field of computational biomechanics.
Research Focus
Key Achievements
Top Papers
- 1Application of fuzzy NARX to human gait modelling and identification3 citations · 2008