Kassio J. S. Eugenio

Universidade Federal do Rio Grande do Norte

Papers

2

Total Citations

14

H-Index

2

About

Kassio J. S. Eugenio is a researcher at the forefront of assistive robotics and wearable sensor technology, with a focus on enhancing mobility for individuals with lower-limb impairments. His work centers on two critical challenges: safe, autonomous path planning for active orthoses and precise motion estimation using low-cost sensors. In his highly cited 2018 paper, "Safe Path Planning Based on Probabilistic Foam for a Lower Limb Active Orthosis to Overcoming an Obstacle," Eugenio introduced the Probabilistic Foam Method—a novel approach that simplifies navigation for robotic orthoses by propagating a structure of "bubbles" through free space, ensuring collision-free paths from start to goal. This work has garnered 9 citations, reflecting its impact on rehabilitation robotics. Complementing this, his 2018 study "Characterization of Resistive Flex Sensor Applied to Joint Angular Displacement Estimation" (5 citations) systematically evaluates the limitations of resistive flex sensors for joint angle estimation, providing essential calibration data for wearable systems used in movement analysis. Eugenio’s contributions bridge the gap between theoretical robotics and practical rehabilitation, offering scalable solutions for active orthosis control and sensor-based motion tracking. His research is a valuable resource for students and engineers developing next-generation assistive devices.

Research Focus

Key Achievements

2
H-Index
2
Papers
14
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Safe Path Planning Based on Probabilistic Foam for a Lower Limb Active Orthosis to Overcoming an Obstacle
9 citations · 2018
📈 Most Prolific Year: 2018 (2 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Universidade Federal do Rio Grande do Norte

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago