Monthly
288 pp. per issue
6 x 9, illustrated
ISSN
0899-7667
E-ISSN
1530-888X
2014 Impact factor:
2.21

Neural Computation

September 2009, Vol. 21, No. 9, Pages 2648-2666
(doi: 10.1162/neco.2009.01-07-441)
© 2009 Massachusetts Institute of Technology
Filtering Out Deep Brain Stimulation Artifacts Using a Nonlinear Oscillatory Model
Article PDF (656.29 KB)
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.