Cristina Gramigna
Papers
1
Total Citations
17
H-Index
1
About
Cristina Gramigna’s research lies at the intersection of neurorehabilitation, brain–computer interfaces, and motor recovery after stroke. Her most-cited work, “Predicting Functional Recovery in Chronic Stroke Rehabilitation Using Event-Related Desynchronization-Synchronization during Robot-Assisted Movement” (2016, 17 citations), addresses a critical gap in personalized medicine: identifying which chronic stroke patients will benefit most from robot-assisted therapy. By analyzing electroencephalographic markers of motor intention—specifically event-related desynchronization and synchronization—Gramigna demonstrated that neural oscillatory patterns can predict functional gains before treatment begins. This pioneering approach moves beyond one-size-fits-all rehabilitation, offering a neurophysiological basis for patient stratification. Her contributions are particularly notable for bridging real-time brain dynamics with robotic exoskeleton training, a methodology that holds promise for closed-loop neurorehabilitation systems. While her citation count reflects a focused, emerging body of work, the translational impact is significant: her findings empower clinicians to allocate intensive robotic therapy to those most likely to respond, reducing unnecessary costs and patient frustration. Gramigna’s research continues to shape how we think about recovery biomarkers, making her a key voice in the future of precision rehabilitation.
Research Focus
Key Achievements
Top Papers
- 1