The Neural Interfacing Lab (NIL) focuses on research in the field of Brain-Machine Interface (BMI), specifically on the entire technology chain, from data acquisition through data processing up to control of robotic assistive devices with electrophysiological signals. More in detail, the research involves the choice of invasive and non-invasive sensors (e.g. EEG, HD EMG, neural implants), the in vitro testing of neural sensors, the sensors’ location, the processing and modeling for BMI, and neural stimulation. Our lab is currently under rapid development and is equipped with invasive and non-invasive neural data acquisition, stimulation hardware, and various electrophysiological sensors for non-invasive usage.
Publications
● Xygonakis, Ioannis; Zavaglia, Melissa; Haddadin, Sami: Robust Independent Component Analysis based EMG decomposition - a comparison study, 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2023; https://ieeexplore.ieee.org/document/10341096
● Viktorija Dimova-Edeleva; Oscar Soto Rivera; Riddhiman Laha; Luis F C Figueredo; Melissa Zavaglia; Sami Haddadin: Error-related Potentials in a Virtual Pick-and-Place Experiment: Toward Real-world Shared-control, Annu Int Conf IEEE Eng Med Biol Soc, 2023; https://pubmed.ncbi.nlm.nih.gov/38083754/
Team
Dr. Melissa Zavaglia; Dr. Alexander Craik; M.Sc. Viktorija Dimova-Edeleva; Dipl. -Ing. Ioannis Xygonakis