Nicola Giulietti
Papers
2
Total Citations
12
H-Index
2
About
Nicola Giulietti is a leading researcher at the intersection of biomechanics, computer vision, and human-robot interaction. His work focuses on developing real-time, marker-less systems to measure and model human pose and body dynamics, with direct applications in Human-In-The-Loop (HITL) simulators for sports training and rehabilitation. Giulietti’s most cited work, "A Real-Time Human Pose Measurement System for Human-In-The-Loop Dynamic Simulators" (2025, 10 citations), introduces a vision-based framework that enables robotic platforms to respond instantly to a user’s pose and inertial properties. This breakthrough allows for more immersive, adaptive simulations that can correct movement in real time. In a subsequent study, "Measuring Human Body Inertia in Real-Time Using Stereo Cameras and Deep Learning: A Model Dependency Analysis" (2024, 2 citations), he advances the field by analyzing how different computational models affect the accuracy of inertia estimation, a critical factor for realistic haptic feedback in virtual reality and robotic training systems. Giulietti’s contributions are foundational for the next generation of intelligent, responsive rehabilitation and sports technologies.
Research Focus
Key Achievements
Top Papers
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- 2