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Evaluating and Improving Automatic Sleep Spindle Detection by Using Multi-Objective Evolutionary Algorithms
Frontiers in Human Neuroscience 11 (2017)
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References found in this work
Automatic sleep spindle detection: benchmarking with fine temporal resolution using open science tools.Christian O'Reilly & Tore Nielsen - 2015 - Frontiers in Human Neuroscience 9.
Stage-independent, single lead EEG sleep spindle detection using the continuous wavelet transform and local weighted smoothing.Athanasios Tsanas & Gari D. Clifford - 2015 - Frontiers in Human Neuroscience 9.
Automatic Sleep Spindle Detection and Genetic Influence Estimation Using Continuous Wavelet Transform.Marek Adamczyk, Lisa Genzel, Martin Dresler, Axel Steiger & Elisabeth Friess - 2015 - Frontiers in Human Neuroscience 9.
Sleep spindle and K-complex detection using tunable Q-factor wavelet transform and morphological component analysis.Tarek Lajnef, Sahbi Chaibi, Jean-Baptiste Eichenlaub, Perrine M. Ruby, Pierre-Emmanuel Aguera, Mounir Samet, Abdennaceur Kachouri & Karim Jerbi - 2015 - Frontiers in Human Neuroscience 9.
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