Homayoon Zarshenas
Papers
2
Total Citations
6
H-Index
2
About
Homayoon Zarshenas is a researcher in biomechatronics and human-robot interaction, with a focus on movement prediction and assistive technologies. His work bridges the gap between biomechanical modeling and machine learning to enhance the safety and performance of human-robot systems. Zarshenas’s most cited paper, “Ankle torque forecasting using time-delayed neural networks” (2020, 4 citations), introduces a method to predict ankle torque ahead of time by combining EMG signals from four muscles with joint angle and angular velocity data. This approach enables more responsive control of prosthetics and exoskeletons. In his comparative study (2020, 2 citations), Zarshenas evaluates biomechanical model-based versus black-box approaches for subject-specific movement prediction, offering insights into the trade-offs between interpretability and data-driven flexibility. His contributions are particularly valuable for developing adaptive, user-specific interfaces in rehabilitation robotics and wearable devices. By integrating physiological signals with neural network architectures, Zarshenas advances real-time prediction capabilities that could improve the natural interaction between humans and machines. His work lays a foundation for safer, more intuitive assistive technologies that respond to individual user dynamics.
Research Focus
Key Achievements
Top Papers
- 1Ankle torque forecasting using time-delayed neural networks4 citations · 2020
- 2