ArticleFrontiers in human neuroscience2015
Spindles in Svarog: framework and software for parametrization of EEG transients.
Article in Frontiers in human neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- CB-1 receptor agonist drastically changes oscillatory activity, defining active sleep.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Two-Stage Atomic Decomposition of Multichannel EEG and the Previously Undetectable Sleep Spindles.Sensors (Basel, Switzerland) · 2024Article
- EEG Transients in the Sigma Range During non-REM Sleep Predict Learning in Dogs.Scientific reports · 2017Article
- Meet Spinky: An Open-Source Spindle and K-Complex Detection Toolbox Validated on the Open-Access Montreal Archive of Sleep Studies (MASS).Frontiers in neuroinformatics · 2017Article
- Sleep Spindles as an Electrographic Element: Description and Automatic Detection Methods.Neural plasticity · 2016Review
- Automatic sleep spindle detection: benchmarking with fine temporal resolution using open science tools.Frontiers in human neuroscience · 2015Article
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6 authors.
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Abstract
We present a complete framework for time-frequency parametrization of EEG transients, based upon matching pursuit (MP) decomposition, applied to the detection of sleep spindles. Ranges of spindles duration (>0.5 s) and frequency (11-16 Hz) are taken directly from their standard definitions. Minimal amplitude is computed from the distribution of the root mean square (RMS) amplitude of the signal within the frequency band of sleep spindles. Detection algorithm depends on the choice of just one free parameter, which is a percentile of this distribution. Performance of detection is assessed on the first cohort/second subset of the Montreal Archive of Sleep Studies (MASS-C1/SS2). Cross-validation performed on the 19 available overnight recordings returned the optimal percentile of the RMS distribution close to 97 in most cases, and the following overall performance measures: sensitivity 0.63 ± 0.06, positive predictive value 0.47 ± 0.08, and Matthews coefficient of correlation 0.51 ± 0.04. These concordances are similar to the results achieved on this database by other automatic methods. Proposed detailed parametrization of sleep spindles within a universal framework, encompassing also other EEG transients, opens new possibilities of high resolution investigation of their relations and detailed characteristics. MP decomposition, selection of relevant structures, and simple creation of EEG profiles used previously for assessment of brain activity of patients in disorders of consciousness are implemented in a freely available software package Svarog (Signal Viewer, Analyzer and Recorder On GPL) with user-friendly, mouse-driven interface for review and analysis of EEG. Svarog can be downloaded from http://braintech.pl/svarog.
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