Papers
15
Total Citations
281
H-Index
8
About
Juri Taborri is a leading researcher in biomechatronics and rehabilitation robotics, whose work bridges the gap between human motor control and assistive technologies. His primary research areas include muscle synergy analysis, gait phase detection, and the development of sensor-based systems for clinical and robotic applications. Taborri’s major contributions are highlighted by his systematic review on the feasibility of muscle synergies in clinics, robotics, and sports (96 citations), which has become a foundational reference for understanding modular motor control. He has also pioneered the use of Hidden Markov Models for gait phase detection in children with cerebral palsy (74 citations), demonstrating how inter-subject training can streamline data processing for robotic rehabilitation devices. His work on the WAKE-up ankle module (31 citations) shows the practical impact of robotic assistance on gait variability and asymmetry in pediatric populations. Beyond rehabilitation, Taborri has explored sensor-based systems for monitoring work-related diseases in firefighters (19 citations) and developed the BEAT platform for standardizing balance assessment in exoskeleton users. His recent innovations include smart fabric sensors for human intention recognition and EEG-based locomotion identification for prosthetic control, reflecting his commitment to advancing real-world applications of robotic assistive technologies.
Research Focus
Key Achievements
Top Papers
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- 8RANK - Robotic Ankle: Design and testing on irregular terrains8 citations · 2022
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