Wissenschaftliche Mitarbeiter

Dipl. -Ing. Ioannis Xygonakis

Picture of Ioannis Xygonakis

Technical University of Munich

Munich Institute of Robotics and Machine Intelligence (MIRMI)

Postal address

Georg-Brauchle-Ring 60_62
80992 München

About me

since 11/2020          Research Assistant,
                                Munich School of Robotics and Machine Intelligence, Technical University of Munich

12/2018-10/2020     Research Assistant,
                                Informatics and Telematics Institute [ITI] - CERTH, Thessaloniki, Greece

2017                        Dipl.-Ing. Electrical & Computer Engineering,
                                Aristotle University of Thessaloniki, Greece

  • I. Xygonakis, A. Athanasiou, N. Pandria, D. Kugiumtzis, and P. D. Bamidis, “Decoding motor imagery through Common Spatial Pattern filters at the EEG source space,” Computational Intelligence and Neuroscience, vol. 2018, 2018.
  • A. Athanasiou, I. Xygonakis, N. Pandria, P. Kartsidis, et al., “Towards rehabilitation robotics: Off-the-shelf BCI control of anthropomorphic robotic arms,” BioMed Research International, vol. 2017, 2017.
  • I. Kalamaras, I. Xygonakis, K. Glykos, S. Akselsen, et al., “Visual analytics for exploring air quality data in an AI-enhanced IoT environment,” in Proceedings of the 11th International Conference on Management of Digital EcoSystems, 2019, pp. 103–110.
  • A. Athanasiou, N. Terzopoulos, N. Pandria, I. Xygonakis, et al., “Functional brain connectivity during multiple motor imagery tasks in spinal cord injury,” Neural Plasticity, 2018.
  • A. Athanasiou, G. Arfaras, N. Pandria, I. Xygonakis, et al., “Wireless Brain-Robot Interface: User perception and performance assessment of spinal cord injury patients,” Wireless Communications and Mobile Computing, vol. 2017, 2017.
  • A. Athanasiou, G. Arfaras, I. Xygonakis, P. Kartsidis, et al., “Commercial BCI control and functional brain networks in spinal cord injury: A proof-of-concept,” in Computer-Based Medical Systems (CBMS), 2017 IEEE 30th International Symposium on, IEEE, 2017, pp. 262–267.


  • Neural signal processing and decoding
  • Brain-Computer Interfaces
  • EMG signal decomposition and decoding
  • Biomedical Signal processing
  • Intelligent prostheses