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About

Matteo Polsinelli is a researcher at the intersection of assistive technology, rehabilitation engineering, and brain-computer interfaces (BCIs). His work centers on developing innovative, technology-driven solutions for hand rehabilitation, particularly for patients recovering from stroke or surgery. Polsinelli’s major contribution is the creation of the "Virtual Glove System," a LEAP motion-based tracking device that replaces traditional, costly therapist-led rehabilitation with objective, reproducible, and remote therapy. His 2018 paper on this system has garnered 35 citations, establishing a foundation for accessible hand therapy. He further advanced this concept with a 2023 study on a patient-therapist cooperative telerehabilitation framework (15 citations), enabling real-time remote monitoring and progression tracking. Expanding into neuroprosthetics, Polsinelli has explored deep learning architectures for EEG-based BCI classification of motor execution (2024, 5 citations) and integrated BCIs with hand tracking and robotic arms to improve decoding of hand and finger movements (2021). His work bridges virtual reality, robotics, and neural decoding, aiming to restore motor function and independence. Polsinelli’s research is pivotal for students and researchers interested in low-cost, scalable rehabilitation technologies and the future of human-machine interaction in clinical settings.