G. Cappiello

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About

G. Cappiello is a researcher working at the intersection of rehabilitation engineering, robotics, and machine learning, with a particular focus on improving outcomes for stroke survivors. Their most notable contribution centers on the application of intelligent decision-support systems to personalize upper extremity robot-assisted rehabilitation, a domain that represents one of the most promising frontiers in modern neurorehabilitation. In their 2022 pilot study, Cappiello introduced a Random Tree Forest-based framework capable of tailoring robotic therapy delivered through serious games to the individual needs of stroke patients — addressing a critical gap in the field where technological sophistication has often outpaced clinical personalization. This work, which has already garnered 14 citations since publication, demonstrates a meaningful commitment to bridging computational intelligence with real-world therapeutic practice. By embedding adaptive algorithms into rehabilitation workflows, Cappiello's research helps clinicians move beyond one-size-fits-all protocols toward genuinely patient-centered care. For students and researchers exploring the convergence of artificial intelligence, human-robot interaction, and clinical rehabilitation science, Cappiello's work offers an important and timely example of how data-driven methods can meaningfully enhance patient recovery trajectories.