Adaptive estimation of single response evoked potentials.
A new adaptive filtering algorithm and structure is developed to estimate response-to-response variations in evoked responses. The evoked responses are modeled as the sum of three uncorrelated signal components: ensemble average, noise, and stochastic signal variation. A two stage time sequenced filter structure exhibiting improved convergence characteristics is developed along with a modified P-vector algorithm (mPa) which eliminates the need for a separate desired signal electrode. The mPa adaptive filter is tested with simulated and human EP data. The mPa filter is able to estimate signal variations from one response to the next.
Westerkamp
J J
JJ
Department of Electrical Engineering, University of Dayton, Ohio 45469-0226, USA.
Williams
R
R
D000465:Algorithms; D016477:Artifacts; D001931:Brain Mapping / Q000295:instrumentation; D002540:Cerebral Cortex / Q000502:physiology*; D004569:Electroencephalography / Q000295:instrumentation*; D005074:Evoked Potentials, Visual / Q000502:physiology; D005583:Fourier Analysis; D006801:Humans; D010364:Pattern Recognition, Visual / Q000502:physiology; D011930:Reaction Time / Q000502:physiology; D012815:Signal Processing, Computer-Assisted