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About

Marco Paleari is a researcher at the intersection of rehabilitation robotics and human-robot interaction, with key contributions spanning assistive exoskeletons, affective computing, and autonomous perception. His most cited work, "Design and testing of an under-actuated surface EMG-driven hand exoskeleton" (2017, 26 citations), addresses the growing need for cost-effective rehabilitation for stroke and neurological pathologies by developing a robotic hand exoskeleton controlled via surface electromyography—a promising step toward accessible, home-based therapy. In affective computing, Paleari’s "Adapting psychologically grounded facial emotional expressions to different anthropomorphic embodiment platforms" (2007, 18 citations) pioneered the translation of psychological models of emotion into expressive artificial agents, enhancing human-ambient intelligence communication. His "Bimodal Emotion Recognition" (2010, 13 citations) further advanced multimodal sensing for emotional AI. Additionally, his work on "Object tracking with adaptive HOG detector and adaptive Rao-Blackwellised particle filter" (2012, 3 citations) contributed to real-time visual tracking for human-robot teams in space missions. Through these diverse contributions, Paleari has demonstrated a sustained commitment to making robots more perceptive, expressive, and clinically useful, bridging engineering and psychology to improve human life.