Manuel Segura
Papers
1
Total Citations
5
H-Index
1
About
Manuel Segura is a researcher in human–machine interaction, with a focus on sensorimotor integration and rehabilitation technologies. His work centers on developing quantitative assessment tools for eye-hand coordination by integrating haptic feedback, eye-tracking, and motion capture systems. In his most cited paper, Segura introduced a multi-platform haptic system that maps robotic device movements to a virtual environment, correlating eye-gaze and upper arm kinematics to derive objective coordination metrics. This contribution provides a foundation for more precise evaluation of motor function in clinical and training contexts, bridging the gap between robotic interfaces and natural human movement. Although early in his citation impact, with his key paper accumulating 5 citations, Segura’s approach represents a novel step toward personalized, data-driven rehabilitation and skill assessment. His work is particularly relevant for researchers in neurorehabilitation, virtual reality, and assistive robotics, offering a framework that could be extended to stroke recovery, sports training, or surgical skill evaluation. By combining multiple sensing modalities, Segura advances the goal of creating ecologically valid, real-time feedback systems for human performance analysis.
Research Focus
Key Achievements
Top Papers
- 1