Max Robotics — Global Service Robot Directory + US Certification

About

Michele Cotti Cottini is a leading researcher in neural engineering and assistive robotics, with a focus on restoring hand function through intelligent, human-machine interfaces. His work centers on the development of EMG-controlled robotic hand rehabilitation devices, where he has pioneered methods to decode user intent from muscle signals before movement execution. His most influential paper, "Artificial neural network EMG classifier for functional hand grasp movements prediction" (2016, 73 citations), introduced a novel classifier that predicts multiple degrees-of-freedom hand grasps—such as pinching and grasping—enabling more natural and responsive control of assistive devices. Cottini further advanced the field by integrating EEG-based biofeedback into robotic rehabilitation, as demonstrated in his work on an integrated system that maximizes patient active participation during therapy. His contributions bridge the gap between neural signal processing and practical, home-based rehabilitation tools, offering scalable solutions for stroke and spinal cord injury patients. By combining real-time EMG classification with robotic actuation, Cottini’s research has laid critical groundwork for affordable, intelligent prosthetics and rehabilitation robots that empower users to regain independence in daily living.