Alessandro Di Matteo
Papers
2
Total Citations
20
H-Index
2
About
Alessandro Di Matteo is a rising researcher at the intersection of rehabilitation engineering and brain-computer interfaces (BCIs). His work centers on two critical frontiers: restoring motor function through telerehabilitation and decoding neural intent for prosthetic control. In his highly cited 2023 paper, Di Matteo introduced the "Virtual Glove System," a novel framework for patient-therapist cooperative hand telerehabilitation. This work, which has already garnered 15 citations, addresses the critical need for reproducible, assistive-technology-driven therapy for post-stroke and post-surgery patients, integrating robotics and virtual reality to track patient progress remotely. More recently, in 2024, Di Matteo has advanced the field of active BCIs by analyzing deep learning architectures for EEG-based classification during motor execution. This research, with 5 citations, aims to decode human neurophysiological signals to control external devices like robotic arms, bridging the gap between neural intention and action. By combining rigorous deep learning analysis with practical rehabilitation frameworks, Di Matteo is making significant strides toward more intuitive and accessible assistive technologies, promising to enhance the quality of life for individuals with motor impairments.
Research Focus
Key Achievements
Top Papers
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- 2