Sara Pizzamiglio

University of East London

Papers

3

Total Citations

62

H-Index

3

About

Sara Pizzamiglio is a researcher whose work lies at the intersection of motor control, neurorehabilitation, and human-robot interaction. Her primary research areas focus on how the human brain and muscles adapt to novel force fields, particularly in the context of robot-mediated motor learning. Pizzamiglio’s most cited paper (2018, 36 citations) demonstrates that resting-state functional connectivity in the brain can predict an individual’s ability to adapt arm reaching movements in a robot-mediated force field—a finding with significant implications for personalized rehabilitation. Her 2017 study on high-frequency intermuscular coherence (23 citations) revealed how the nervous system orchestrates coordinated muscle activation during adaptation, showing that coherent coupling between arm muscles is a key mechanism for learning. In related work, she explored muscle co-contraction patterns during force field learning, suggesting that specific muscle group training could be guided by these patterns—particularly relevant for neuropathological populations. Pizzamiglio’s research bridges neuroscience and robotics, offering insights that could enhance motor recovery after stroke or injury. Her work underscores the potential of combining brain imaging, electromyography, and robotic systems to decode and improve human motor adaptation.

Research Focus

Key Achievements

3
H-Index
3
Papers
62
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
Resting-state functional connectivity predicts the ability to adapt arm reaching in a robot-mediated force field
36 citations · 2018
📈 Most Prolific Year: 2017 (2 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: University of East London

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago