Towards Non-Invasive EEG-based Neuroprosthesis Control in Spinal Cord Injury (IS Colloquium)
- Gernot Müller-Putz (Head of the Institute for Knowledge Discovery)
- Graz University of Technology
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More than half of the persons with spinal cord injuries (SCI) are suffering from impairments of both hands, which results in a tremendous decrease of quality of life and represents a major barrier for inclusion in society. Functional restoration is possible with neuroprostheses (NPs) based on functional electrical stimulation (FES). A Brain-Computer Interface provides a means of control for such neuroprosthetics since users have limited abilities to use traditional assistive devices. This talk presents our early research on BCI-based NP control based on motor imagery, discusses hybrid BCI solutions and shows our work and effort on movement trajectory decoding. An outlook to future BCI applications will conclude this talk.
Biography: Gernot Müller-Putz is Head of the Institute for Knowledge Discovery, Graz University of Technology, Austria. He is also Head of the Laboratory for Brain-Computer Interfaces (BCI Lab) at Graz University of Technology. Currently he is Dean of Studies for "Information & Computer Engineering" at TUG, deputy speaker of the Field of Expertise "Human & Bio Technology", Speaker of BioTechMed "Neuroscience". In 2004 he received his PhD in electrical engineering ('New Concepts in Brain-Computer Communication Use of Steady-State Somatosensory Evoked Potentials, User Training by Telesupport and Control of Functional Electrical Stimulation') from Graz University of Technology, where, beginning in 2000, he worked on non-invasive electroencephalogram-based (EEG) brain-computer interfacing (BCI) for the control of neuroprosthetic devices. In 2008 he recieved his "venia docendi" for medical informatics ('Towards EEG-based Control of Neuroprosthetic Devices') at the faculty of computer sciende at Graz University of Technology. Since October 2014 he is full professor for semantic data analysis at TUG. His research interest include EEG-based neuroprosthesis control, hybrid BCI systems, communication for persons with disorders of consciousness, the human somatosensory system and assistive technology.