EEG represents a cheap, high time-resolution and portable tool for neuro-motor rehabilitation. Signal processing is a very important element to achieve the most from an EEG-based rehabilitative system. In this talk, two examples of EEG-based clinical application will be presented: an EEG-based brain computer interface platform for upper limb recovery after stroke, on one side, and the identification of EEG abnormal oscillations in focal hand dystonia patients, on the other side. "SHORT BIO: "Giulia Cisotto was born in 1985. She received the Master degree in Telecommunication Engineering in 2010 and Ph.D. in Science and Technology of Information in 2014 at the University of Padua. Since 2010, she worked on the EEG signals processing for several clinical applications such as the diagnosis of Amyotrophic Lateral Sclerosis, the detection of awareness changes in Persistent Vegetative State and Minimal Consciousness patients, and Brain-Computer Interface (BCI) for motor rehabilitation of upper limbs after Stroke. She worked in Japan for one year in 2014-2015 as a research associate at Keio University (Yokohama, Japan) and research student at National Centre of Neurology and Psychiatry of Tokyo. Since 2014 she started to study EEG applications for focal hand dystonia and her current interest is focused on EEG and EMG signals processing for rehabilitation purposes, especially for motor rehabilitation of focal hand dystonia, including BCI.