title: Robust moving averages, with Hopfield neural network implementation, for monitoring evoked potential signals.
abstract: This technical note describes a robust version of moving averages, that enables reliable monitoring of the evoked potential (EP) signals. A cluster analysis (CA) procedure is introduced to robustify the signal averaging (SA). It is implemented via a Hopfield neural network (HNN), which performs selection of the trials forming a cluster around the current state of the EP signal. The core of this cluster serves as an estimate of the instantaneous EP. The effectiveness of the method, indicated by application to real data, and its computation efficiency, due to the use of simple matrix operations, makes it very promising for clinical observations.
authors.affiliation: Department of Medical Physics, School of Medicine, University of Patras, Greece.
authors.forename: N
authors.initials: N
authors.lastname: Laskaris
authors.forename: S
authors.initials: S
authors.lastname: Fotopoulos
authors.forename: P
authors.initials: P
authors.lastname: Papathanasopoulos
authors.forename: A
authors.initials: A
authors.lastname: Bezerianos
mesh_terms: D004569:Electroencephalography / Q000379:methods*; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D008991:Monitoring, Physiologic; D016571:Neural Networks, Computer