Filtering out deep brain stimulation artifacts using a nonlinear oscillatory model
Tatyana I Aksenova1, Dimitri V Nowicki, Alim-Louis Benabid
1Unit 318, INSERM, 38043 Grenoble, Cedex 09, France, and Institute of Applied System Analysis, Ukrainian Academy of Sciences, Kiev 03056, Ukraine. tatyana.aksyonova@ujf-grenoble.fr
Neural Computation
|March 28, 2009
Abstract:
This letter is devoted to the suppression of spurious signals (artifacts) in records of neural activity during deep brain stimulation. An approach based on nonlinear adaptive model with self-oscillations is proposed. We developed an algorithm of adaptive filtering based on this approach. The proposed algorithm was tested using recordings collected from patients during the stimulation. This was then compared to existing methods and showed the best performance.
