STUPS

IDENTIFICATION OF DATA-DRIVEN NEURAL MARKERS FOR ADAPTIVE DBS IN PARKINSON’S DISEASE


Relevant for Research Area

C - Applications


Summary

STUPS is a collaborative project, that addresses clinically relevant research questions related to the use of deep brain stimulation (DBS) in patients with Parkinson’s disease using technical approaches from the field of BCI and machine learning. Specifically, STUPS investigates methods that allow to extract brain signal features from local field potentials and EEG signals, which are informative about the motor state of a patient. Machine learning approaches are utilized in STUPS, as these informative features are expected to be subject-dependent and need to be extracted in a data-driven approach. The project furthermore explores the temporal dynamics revealed in the individual brain signals upon DBS. Thus STUPS will contribute important building blocks towards future fully adaptive DBS systems.


Project Publications

Castaño-Candamil. et. al., "Dynamics of STN low-frequency components upon DBS." In XXII Congress of the Europ. Soc. for Sterotactic and Functional Neurosurgery, 2016.

Castaño-Candamil. et. al. "DBS-induced alpha desynchronization in the subthalamic nucleus of PD patients.” Clinical Neurophysiology, 127(9):e202–e203, 2016.

Ferleger et al. “Optimization of treatment in essential tremor using electrocorticography data.”,Proc. of the 7th Graz BCI Conf., pp. 78-79, 2018.

Castaño-Candamil. et. al., “Closed-Loop Deep Brain Stimulation System for an Animal Model of Parkinson's Disease: A Pilot Study”, Proc. of the 7th Graz BCI Conf., pp. 58-63, 2017