Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6891571 | Computer Methods and Programs in Biomedicine | 2013 | 7 Pages |
Abstract
In this work, a new algorithm for automatic detection of high frequency oscillations is presented. This algorithm uses approximate entropy and artificial neural networks to extract features in order to detect and classify high frequency components in electrophysiological signals. In contrast to the existing algorithms, the one proposed here is fast and accurate, and can be implemented on-line, thus reducing the time employed to analyze the experimental electrophysiological signals.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Armando López-Cuevas, Bernardino Castillo-Toledo, Laura Medina-Ceja, Consuelo Ventura-MejÃa, Kenia Pardo-Peña,