Francesca Giordaniello

HES-SO University of Applied Sciences and Arts Western Switzerland, Sapienza University of Rome

Papers

Total Citations

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About

Francesca Giordaniello is a researcher at the forefront of assistive and rehabilitation technologies, with a primary focus on human-machine interfaces, multimodal sensing, and prosthetic control. Her most impactful work centers on improving the robustness and usability of robotic hand prostheses by integrating multiple data streams. In her landmark paper, "Megane Pro: Myo-electricity, visual and gaze tracking data acquisitions to improve hand prosthetics" (2017, 14 citations), she pioneered the first multimodal dataset combining surface electromyography (sEMG), visual scene data, and gaze tracking. This work directly addresses a critical bottleneck in commercial prosthetics—limited control robustness—by demonstrating how eye-tracking and visual context can complement traditional myoelectric signals. Giordaniello also advanced object recognition systems for assistive devices, as shown in her paper "Semi-automatic Training of an Object Recognition System in Scene Camera Data Using Gaze Tracking and Accelerometers" (2017, 10 citations), where she developed a semi-autonomous training method that leverages natural gaze behavior to reduce user burden. Her contributions are foundational for next-generation prosthetics that are more intuitive, adaptive, and responsive to user intent, bridging the gap between laboratory research and real-world clinical applications.