Characteristics of human EEG sleep spindles assessed by Gabor transform (original) (raw)

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Bódizs R, Körmendi J, Rigó P, Lázár AS : The individual adjustment method of sleep spindle analysis: Methodological improvements and roots in the fingerprint paradigm. J. Neurosci. Methods 178(1) 205-213. (2009)

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

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Development and comparison of four sleep spindle detection methods

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Spectral and temporal characterization of sleep spindles—methodological implications

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Poster: Quantification of correlations between sleep spindles in EEG for patients with sleep apnea

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2013 IEEE 3rd International Conference on Computational Advances in Bio and medical Sciences (ICCABS), 2013

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Automatic detection of spindles and K-complexes in sleep EEG using switching multiple models

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Spindle frequencies in sleep EEG show U-shape within first four NREM sleep episodes

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Statistical Analysis of Sleep Spindle Occurrences

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Topographical Analysis of Sleep Spindle Activity

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Sleep spindle detection using artificial neural networks trained with filtered time-domain EEG: A feasibility study

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Automated Sleep-Spindle Detection in Healthy Children Polysomnograms

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Assessing EEG sleep spindle propagation. Part 1: Theory and proposed methodology

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Sleep spindles and spike–wave discharges in EEG: Their generic features, similarities and distinctions disclosed with Fourier transform and continuous wavelet analysis

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Dual approach for automated sleep spindles detection within EEG background activity in infant polysomnograms

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