Sleep spindles detection from human sleep EEG signals using autoregressive (AR) model: a surrogate data approach

ISSN Print: 1937-6871
ISSN Online: 1937-688X
www.scirp.net/journal/jbise
E-mail: [email protected]

Citations

"Sleep spindles detection from human sleep EEG signals using autoregressive (AR) model: a surrogate data approach"
written by Venkatakrishnan Perumalsamy, Sangeetha Sankaranarayanan, Sukanesh Rajamony,
published by Journal of Biomedical Science and Engineering, Vol.2 No.5, 2009

has been cited by the following article(s):

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[4]	Visual Analytics for Development and Evaluation of
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[5]	Visual Analytics for Development and Evaluation of Order Selection Criteria for Autoregressive Processes.
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[6]	Using a Quadrature Parameter Sinusoidal Model to Characterize the Structure of EEG Sleep Spindles
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[7]	Visual Analytics for Development and Evaluation of Order Selection Criteria for Autoregressive Processes
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[5]	A study on decomposing EEGs during sleep into frequency components and revealing spindles using Kalman filter Chaos, Solitons & Fractals, 2021 DOI:10.1016/j.chaos.2021.110712

[6]	Identifying sleep spindles with multichannel EEG and classification optimization Computers in Biology and Medicine, 2017 DOI:10.1016/j.compbiomed.2017.08.030

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[8]	Using a quadratic parameter sinusoid model to characterize the structure of EEG sleep spindles Frontiers in Human Neuroscience, 2015 DOI:10.3389/fnhum.2015.00206

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