Felipe Campelo
Papers
2
Total Citations
6
H-Index
2
About
Felipe Campelo is a researcher whose work sits at the intersection of biomedical signal processing, machine learning, and assistive robotics, with a particular focus on advancing the control of robotic prosthetic limbs. His research investigates the classification and fusion of bioelectric signals — specifically electromyographic (EMG) and electroencephalographic (EEG) data — to improve how prosthetic devices interpret human intent. A central contribution of his work is demonstrating that combining muscular and brain activity signals through multimodal fusion strategies yields meaningfully better classification performance than either signal alone, even when using accessible, low-cost devices. His 2021 paper on dynamic data fusion has garnered 4 citations, while his more recent 2025 investigation into methodological rigour in upper-limb gesture identification continues to push the field toward more robust experimental standards. By critically examining prevailing methodological limitations in EMG-EEG classification research, Campelo's work not only proposes practical improvements but also raises the bar for scientific practice in the field. His contributions are particularly relevant for researchers and engineers working toward more intuitive, responsive, and accessible prosthetic technologies for upper-limb amputees.
Research Focus
Key Achievements
Top Papers
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