Title :
H∞ adaptive filters for eye blink artifact minimization from electroencephalogram
Author :
Puthusserypady, S. ; Ratnarajah, T.
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
Abstract :
Two adaptive algorithms (time varying and exponentially weighted) based on the H∞ principles are proposed for the minimization of electrooculogram (EOG) artifacts from corrupted electroencephalographic signals. Performance of the proposed algorithms are compared with the least-mean-square (LMS) algorithm. Improvements in the output signal-to-noise ratio along with time plots are used for the comparison. It is found that the H∞-based algorithms effectively minimize the EOG artifacts and always outperform the LMS algorithm.
Keywords :
H∞ optimisation; adaptive filters; biomedical equipment; electro-oculography; electroencephalography; medical signal processing; minimisation; neurophysiology; EEG; EOG; H∞ adaptive filter; electroencephalogram; electrooculogram; eye blink artifact; minimization; Adaptive algorithm; Adaptive filters; Brain modeling; Electroencephalography; Electrooculography; Filtering algorithms; Independent component analysis; Least squares approximation; Minimization methods; Uncertainty; Blink artifacts; electroencephalogram (EEG);
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2005.859526
