Authors:
Bartosz Binias
and
Michal Niezabitowski
Affiliation:
Silesian University of Technology, Poland
Keyword(s):
EEG, Electroencephalography, Adaptive Filtering, Artifact Filtering, Artifact Correction, Signal Reconstruction, Nonlinear Projective Filtering, Nonlinear State Space Projection, Biomedical Signals.
Related
Ontology
Subjects/Areas/Topics:
Adaptive Signal Processing and Control
;
Engineering Applications
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Nonlinear Signals and Systems
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
Signal Reconstruction
Abstract:
In this work a novel approach to filtering of eyeblink related artifacts from EEG signals is presented. Proposed
solution, the Adaptive Nonlinear Projective Filtering (ANPF) algorithm, combines the classic approach
to adaptive filtering with algorithms from nonlinear state space projection family. Performance of described
method is compared with adaptive filter based on Normalized Least Mean Squares algorithm in terms of median
Normalized Mean Squared Error. Data used in conducted research was simulated according to described
procedure. Such approach allowed for a reliable comparison and evaluation of algorithm’s signal correction
properties. Additionally, a real time modification of ANPF algorithm is proposed and tested. The analysis
of sensitivity to changes of parameter values was also performed. Achieved results were tested for statistical
significance. According to obtained scores ANPF significantly outperforms referential method during offline
processing.