Sleep Spindle Detection Using RUSBoost and Synchrosqueezed Wavelet Transform
نویسندگان
چکیده
منابع مشابه
Sleep spindle and K-complex detection using tunable Q-factor wavelet transform and morphological component analysis
A novel framework for joint detection of sleep spindles and K-complex events, two hallmarks of sleep stage S2, is proposed. Sleep electroencephalography (EEG) signals are split into oscillatory (spindles) and transient (K-complex) components. This decomposition is conveniently achieved by applying morphological component analysis (MCA) to a sparse representation of EEG segments obtained by the ...
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Mounting evidence for the role of sleep spindles in neuroplasticity has led to an increased interest in these non-rapid eye movement (NREM) sleep oscillations. It has been hypothesized that fast and slow spindles might play a different role in memory processing. Here, we present a new sleep spindle detection algorithm utilizing a continuous wavelet transform (CWT) and individual adjustment of s...
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1 Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK 4 2 Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, UK 5 3 Sleep and Circadian Neuroscience Institute, Nuffield Department of Medicine, University of Oxford, UK 6 4 Department of Biomedical Informatics, Emory University, Atlanta, Georgia, USA ...
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ژورنال
عنوان ژورنال: IEEE Transactions on Neural Systems and Rehabilitation Engineering
سال: 2020
ISSN: 1534-4320,1558-0210
DOI: 10.1109/tnsre.2020.2964597