Papers
3
Total Citations
48
H-Index
3
About
Andrea Gigli’s research lies at the intersection of intelligent prosthetics, human-machine interaction, and biosignal processing, with a particular focus on restoring natural, intuitive control for individuals with hand amputations. Her major contributions center on advancing myoelectric control systems—using pattern recognition of muscle signals to enable users to operate robotic limbs as naturally as their own. Gigli’s most cited work, “Gaze, visual, myoelectric, and inertial data of grasps for intelligent prosthetics” (2020, 36 citations), provides a rich, multimodal dataset that captures the complexity of real-world grasping tasks, integrating gaze, visual, and inertial data alongside muscle signals. This resource is pivotal for developing more robust, context-aware prosthetics. In her 2019 study on natural myocontrol, she compared static versus dynamic data acquisition, demonstrating that signals collected during realistic, dynamic movements significantly improve control reliability—a key insight for translating lab-based systems to everyday use. Gigli’s work is notable for its emphasis on ecological validity, pushing the field toward prosthetics that truly respond to the variability of daily life. Her contributions are shaping the next generation of intelligent, user-responsive assistive technologies.
Research Focus
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