Francesco Piccione

About

Francesco Piccione is a pioneering researcher at the intersection of neuroscience, rehabilitation engineering, and brain-computer interfaces (BCIs). His work focuses on developing closed-loop neurorehabilitation systems for stroke and spinal cord injury (SCI) patients, integrating BCIs with robotic exoskeletons and force-feedback devices to restore motor function. Piccione’s most influential paper, “Brain-Computer Interface in Stroke: A Review of Progress” (2011), with 221 citations, established a foundational framework for using BCIs in post-stroke motor recovery. He demonstrated that combining sensorimotor rhythm modulation with contingent force feedback can drive neuroplasticity and improve upper-limb reaching ability in chronic stroke patients. His 2016 study on wearable robots for SCI mobility training (80 citations) showed that robotic exoskeletons can counteract de-adaptation and improve gait. Piccione also advanced lower-limb BCI research by quantifying EEG changes during robot-assisted foot movements (59 citations). Beyond rehabilitation, he explored BCI-controlled mobile robots for assistive applications, including a teleoperated museum guide. His work has been instrumental in translating BCI technology from laboratory proof-of-concept to clinically viable rehabilitation tools, with cumulative citations exceeding 425.

Research Focus

Key Achievements

Top Papers

1. 1
   Brain-Computer Interface in Stroke: A Review of Progress

   221 citations · 2011
2. 2
   Effects on mobility training and de-adaptations in subjects with Spinal Cord Injury due to a Wearable Robot: a preliminary report

   80 citations · 2016
3. 3
   Quantitative EEG Evaluation During Robot-Assisted Foot Movement

   59 citations · 2016
4. 4
   A BCI Teleoperated Museum Robotic Guide

   31 citations · 2009
5. 5
   Kinematic and Neurophysiological Consequences of an Assisted-Force-Feedback Brain-Machine Interface Training: A Case Study

   12 citations · 2013
6. 6
   Brain-computer interface in chronic stroke: An application of sensorimotor closed-loop and contingent force feedback

   11 citations · 2013
7. 7
   An EEG-Based BCI Platform to Improve Arm Reaching Ability of Chronic Stroke Patients by Means of an Operant Learning Training with a Contingent Force Feedback

   7 citations · 2014
8. 8
   Evaluation of a robot as embodied interface for Brain Computer Interface systems

   4 citations · 2009

Key Collaborators

Contact & Links