Personalized Neurorehabilitative Precision Medicine - From Data to Therapies

Stroke is the most common neurological disease leaving one third dead and one third with permanent impairment despite best medical treatment. The aim of the present study is to investigate why patients differ in how they benefit from neurorehabilitation by collecting clinical, electrophysiological, imaging and laboratory data in the acute phase of stroke as well as later on during rehabilitation and after 90 days. Following a closed-loop approach the data is analyzed by a machine learning algorithm to create a personalized neurorehabilitation strategy.