title: Spike detection: a review and comparison of algorithms.
abstract: For algorithm developers, this review details recent approaches to the problem, compares the accuracy of various algorithms, identifies common testing issues and proposes some solutions. For the algorithm user, e.g. electroencephalograph (EEG) technician or neurologist, this review provides an estimate of algorithm accuracy and comparison to that of human experts. Manuscripts dated from 1975 are reviewed. Progress since Frost's 1985 review of the state of the art is discussed. Twenty-five manuscripts are reviewed. Many novel methods have been proposed including neural networks and high-resolution frequency methods. Algorithm accuracy is less than that of experts, but the accuracy of experts is probably less than what is commonly believed. Larger record sets will be required for expert-level detection algorithms.
authors.affiliation: Persyst Development Corporation, Prescott, AZ 86305, USA. scottw@eeg-persyst.com
authors.forename: Scott B
authors.initials: SB
authors.lastname: Wilson
authors.forename: Ronald
authors.initials: R
authors.lastname: Emerson
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D006801:Humans