Sina Ghanaat

K.N.Toosi University of Technology, Robotics Research (United States)

Papers

Total Citations

H-Index

About

Sina Ghanaat is a researcher focused on the intersection of robotics, rehabilitation engineering, and human-robot interaction, with a particular emphasis on lower limb assistive devices. His major contributions center on the development and optimization of **RoboWalk**, a wearable exoskeleton designed for rehabilitation and load-carrying tasks. Ghanaat’s work addresses critical challenges in this field, including generating natural walking patterns and mitigating harmful forces on users. Notably, his 2021 paper on "RoboWalk Trajectory Planning Based on the Human Gait Prediction Using LSTM" (6 citations) pioneers the use of deep learning—specifically Long Short-Term Memory networks—to predict human gait, enabling smoother and more adaptive exoskeleton control. His 2022 study on test-stand development and performance analysis (4 citations) provides essential experimental validation of the device’s functionality. Earlier, his 2019 conceptual and optimal design paper (3 citations) laid the groundwork by addressing the horizontal force component that can cause user discomfort. Through this cohesive body of work, Ghanaat has advanced the practical viability of rehabilitation exoskeletons, demonstrating how intelligent control and careful mechanical design can improve both safety and efficacy in assistive robotics.