Michele Canepa
Papers
5
Total Citations
29
H-Index
3
About
Michele Canepa is a leading researcher in noninvasive human-machine interfaces and robotic neurorehabilitation, with a focus on advancing upper-limb prosthetics and motor assessment. His work centers on integrating high-density surface electromyography (sEMG) and machine learning to enable intuitive, long-term myocontrol of prosthetic devices—overcoming classical limitations of few degrees of freedom. His 2024 paper on incremental learning for prosthesis control has already garnered 11 citations, reflecting its impact on the field. Canepa has also made significant contributions to multimodal data collection, exemplified by the Reach&Grasp dataset (9 citations), which combines kinematic, electrophysiological, and tactile data to characterize complex upper-limb movements. He co-developed NeBULA, a standardized protocol for benchmarking robotic neurorehabilitation technologies, addressing a critical gap in objective therapy assessment. Additionally, his clinical evaluation of the Hannes polyarticulated prosthetic hand (2022) and his EEG-EMG dataset for biomarker research (2025) underscore his commitment to translating engineering innovations into practical, patient-centered solutions. Canepa’s work is pivotal for students and researchers seeking to understand the future of assistive robotics and neurorehabilitation.
Research Focus
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Top Papers
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