Detecting and characterizing high-frequency oscillations in epilepsy: a case study of big data analysis

We develop a framework to uncover and analyse dynamical anomalies from massive, nonlinear and non-stationary time series data. The framework consists of three steps: preprocessing of massive datasets to eliminate erroneous data segments, application of the empirical mode decomposition and Hilbert tr...

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Detalles Bibliográficos
Autores principales: Huang, Liang, Ni, Xuan, Ditto, William L., Spano, Mark, Carney, Paul R., Lai, Ying-Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society Publishing 2017
Materias:
Engineering
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5319343/
https://www.ncbi.nlm.nih.gov/pubmed/28280577
http://dx.doi.org/10.1098/rsos.160741

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5319343/
https://www.ncbi.nlm.nih.gov/pubmed/28280577
http://dx.doi.org/10.1098/rsos.160741

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