Separation of a Nonstationary Component from the EEG by a Nonlinear Digital Filter

A new nonlinear digital filter which separates nonstationary waves such as spikes from stationary background waves of the EEG is proposed. This filter is composed of a prediction filter and a simple nonlinear function. Some examples showing the separation of spikes from EEG data of epileptic patients are given.

[1]  J. Gotman,et al.  Automatic recognition and quantification of interictal epileptic activity in the human scalp EEG. , 1976, Electroencephalography and Clinical Neurophysiology.

[2]  Hiroshi Harashima,et al.  ϵ‐separating nonlinear digital filter and its applications , 1982 .

[3]  B. Widrow,et al.  Stationary and nonstationary learning characteristics of the LMS adaptive filter , 1976, Proceedings of the IEEE.

[4]  F H Lopes da Silva,et al.  Automatic detection and localization of epileptic foci. , 1977, Electroencephalography and clinical neurophysiology.

[5]  B Saltzberg,et al.  Detection of focal depth spiking in the scalp EEG of monkeys. , 1971, Electroencephalography and clinical neurophysiology.

[6]  Hiroshi Harashima,et al.  Statistical analysis of ϵ-separating nonlinear digital filters , 1983 .

[7]  J R Carrie,et al.  A hybrid computer technique for detecting sharp EEG transients. , 1972, Electroencephalography and clinical neurophysiology.