Papers
44
Total Citations
900
H-Index
15
About
Marco Germanotta is a distinguished Italian rehabilitation researcher whose work sits at the intersection of robotic technology, neurological recovery, and clinical outcomes. His research focuses primarily on upper limb robotic rehabilitation following stroke, sensor-based motor assessment, and the application of artificial intelligence in rehabilitation settings. Germanotta has made significant contributions to the field by rigorously evaluating how robotic devices can objectively quantify motor performance and enhance functional recovery in patients with neurological conditions including stroke and Friedreich's Ataxia. His landmark 2019 multicenter randomized clinical trial on upper limb robotic rehabilitation after stroke, cited 134 times, helped establish a stronger evidence base for robot-mediated therapy at scale. Complementing this, his psychometric studies validating robotic assessment indices — for both planar devices and finger training systems — have been instrumental in building clinician confidence in technology-derived outcome measures. His 2018 review on robotic and sensor technology, garnering 97 citations, further cemented his role as a leading synthesizer of the field. More recently, he has expanded into exploring how robotic rehabilitation can address post-stroke cognitive impairment and how AI and machine learning can optimize rehabilitation protocols. Across ten highly cited publications, Germanotta's work reflects a career dedicated to transforming rehabilitation practice through rigorous, technology-driven science.
Research Focus
Key Achievements
Top Papers
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- 2Robotic and Sensor Technology for Upper Limb Rehabilitation97 citations · 2018
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