Papers
1
Total Citations
17
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1
About
Elisa Visani’s research lies at the intersection of neurorehabilitation and brain-computer interfaces, with a primary focus on understanding and predicting 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), exemplifies her key contribution: using electroencephalographic (EEG) markers—specifically event-related desynchronization and synchronization—to forecast how well chronic stroke patients will respond to robot-assisted therapy. This approach addresses a critical clinical gap by identifying which patients are most likely to benefit from robotic interventions, thereby personalizing rehabilitation strategies. Visani’s work demonstrates how neural oscillatory dynamics can serve as biomarkers for functional recovery, advancing the field toward more targeted, efficient therapies. While her citation count reflects a growing interest in this niche, her impact is notable for bridging neurophysiology and rehabilitation engineering, offering a data-driven pathway to optimize post-stroke care. Her research continues to inform the development of adaptive rehabilitation technologies that respond to individual brain states.
Research Focus
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Top Papers
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