Caue Conterno Barreira
Papers
1
Total Citations
15
H-Index
1
About
Caue Conterno Barreira is a researcher whose work sits at the intersection of biomechanics, signal processing, and human-robot interaction. His primary research focus is on using surface electromyography (sEMG) to decode human motor intent, a critical challenge for developing intuitive prosthetic and exoskeleton control systems. His most cited work, "Elbow Joint Angle Estimation with Surface Electromyography Using Autoregressive Models" (2018, 15 citations), introduces a sophisticated method for estimating continuous joint angles from muscle activity. By applying autoregressive models to sEMG signals from the biceps, triceps, and brachioradialis, Barreira demonstrated a more accurate and dynamic approach to mapping neuromuscular signals to limb movement. This contribution is foundational for designing responsive human-robot interfaces and for advancing computational models of the musculoskeletal system. His work bridges the gap between raw biological signals and practical robotic control, offering a pathway toward more natural and fluid interaction between humans and machines. Barreira’s research is particularly valuable for students and engineers working in rehabilitation robotics, assistive technology, and neural interfacing.
Research Focus
Key Achievements
Top Papers
- 1