Matteo Cioeta
Papers
1
Total Citations
6
H-Index
1
About
Matteo Cioeta’s research sits at the intersection of neurorehabilitation and robotics, with a focus on using quantitative kinematic metrics to enhance stroke recovery. His most-cited work, a 2022 study on subacute stroke patients, demonstrates how robot-measured movement parameters can predict discharge rehabilitation outcomes—a critical step toward personalized therapy. By correlating pre-treatment kinematics with motor recovery, Cioeta addresses a gap in the literature, moving beyond subjective clinical scales to objective, data-driven predictions. This work has already garnered 6 citations, signaling its growing influence in the field. His contributions are particularly notable for bridging engineering and clinical practice, offering tools that could streamline rehabilitation planning and improve patient outcomes. Cioeta’s research underscores a shift toward precision medicine in neurorehabilitation, where robotic devices not only assist therapy but also serve as diagnostic instruments. For students and researchers, his work exemplifies how interdisciplinary approaches can solve real-world clinical challenges, making him a rising voice in the effort to optimize recovery after neurological injury.
Research Focus
Key Achievements
Top Papers
- 1