Emilia Biffi

IRCCS Eugenio Medea, Politecnico di Milano

Papers

18

Total Citations

398

H-Index

10

About

Emilia Biffi is a prominent researcher specializing in pediatric neurorehabilitation, robotic-assisted therapy, and clinical outcome measurement, with a particular focus on children with cerebral palsy and acquired brain injuries. Her work has significantly advanced the field by establishing standardized clinical benchmarks, most notably through her highly cited 2020 study (90 citations) defining the Minimum Clinically Important Difference for key gait assessment tools, providing clinicians with essential thresholds for evaluating meaningful patient progress. Biffi has been instrumental in validating and optimizing robot-assisted gait training, demonstrating through multiple studies how dosage, duration, and technology design influence motor recovery in pediatric populations. Her 2017 work on immersive virtual reality platforms (71 citations) broke new ground by addressing patient engagement as a critical rehabilitation variable, particularly for young patients. Extending her expertise to upper limb rehabilitation, she has explored robotic exoskeletons and voice-controlled assistive devices, broadening accessibility for severely impaired individuals. More recently, her 2024 research applying artificial intelligence to predict patient engagement reflects her forward-thinking integration of emerging technologies into clinical practice. Collectively, her contributions bridge engineering innovation and clinical application, making her a leading voice in technology-driven pediatric rehabilitation.

Research Focus

Key Achievements

10
H-Index
18
Papers
398
Total Citations
22
Avg Citations/Paper
🏆 Most Cited Paper
Minimum Clinically Important Difference of Gross Motor Function and Gait Endurance in Children with Motor Impairment: A Comparison of Distribution‐Based Approaches
90 citations · 2020
📈 Most Prolific Year: 2018 (5 Papers)
🤝 Key Collaborators: 86
🏛 Institutions: IRCCS Eugenio Medea, Politecnico di Milano

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago