Beschreibung
AbstractStroke is one of the primary causes of adult disabilities. Despite significant progress in novel stroke therapies, including rehabilitation robotics, brain-robot interfaces, and non-invasive brain stimulation, these advances have not yet found their way into widespread clinical practice. In this talk, I argue that the slow translation of these therapies into clinical practice is due to the heterogeneity of stroke pathophysiology. I then sketch how machine learning can be used to combine rehabilitation robots with real-time brain decoding and non-invasive brain stimulation to person alize motor rehabilitation. I present initial results on the efficacy of personalized, i.e., brain-state dependent, brain stimulation, and outline future steps for creating intelligent brain-robotinterfaces for stroke rehabilitation.
| Zeitraum | 22 Juni 2019 |
|---|---|
| Ereignistitel | RSS 2019 Workshop |
| Veranstaltungstyp | Seminar/Workshop |
| Ort | Freiburg, DeutschlandAuf Karte anzeigen |
| Bekanntheitsgrad | International |