ArticleBiomedical engineering online2013
Electroencephalographic profiles for differentiation of disorders of consciousness.
Article in Biomedical engineering online, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.
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Who cites it
20 citing papers in PubMed, 3 syntheses or guidelines pooled it, 53 citations in OpenAlex.
- Research hotspots and trends in the application of electroencephalography for assessment of disorders of consciousness: a bibliometric analysis.Frontiers in neurology · 2024Pooled it
- Managing disorders of consciousness: the role of electroencephalography.Journal of neurology · 2021Pooled it
- Persistent vegetative state and minimally conscious state: a systematic review and meta-analysis of diagnostic procedures.Deutsches Arzteblatt international · 2015Pooled it
- Detecting EEG index of arousal in sleeping patients with unresponsive wakefulness syndrome.iScience · 2026Article
- Prognostic value of quantitative and visual electroencephalography in disorders of consciousness: a retrospective study.Frontiers in neuroscience · 2025Article
- A Systematic Review of Sleep in Patients with Disorders of Consciousness: From Diagnosis to Prognosis.Brain sciences · 2021Review
- Narrative Review: Quantitative EEG in Disorders of Consciousness.Brain sciences · 2021Review
- 24-h polysomnographic recordings and electrophysiological spectral analyses from a cohort of patients with chronic disorders of consciousness.Journal of neurology · 2020Article
- Toward Improving Diagnostic Strategies in Chronic Disorders of Consciousness: An Overview on the (Re-)Emergent Role of Neurophysiology.Brain sciences · 2020Article
- Multifactor consciousness level assessment of participants with acquired brain injuries employing human-computer interfaces.Biomedical engineering online · 2020Article
- Bottom-up gamma maintenance in various disorders.Neurobiology of disease · 2019Review
- Sleep in patients with disorders of consciousness characterized by means of machine learning.PloS one · 2018Article
- Night and day variations of sleep in patients with disorders of consciousness.Scientific reports · 2017Article
- A Review of Resting-State Electroencephalography Analysis in Disorders of Consciousness.Frontiers in neurology · 2017Review
- Sleep/Wake Modulation of Polysomnographic Patterns has Prognostic Value in Pediatric Unresponsive Wakefulness Syndrome.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2016Article
- High-density electroencephalographic recordings during sleep in children with disorders of consciousness.NeuroImage. Clinical · 2016Article
- Electroencephalography (EEG) Measures of Neural Connectivity in the Assessment of Brain Responses to Salient Auditory Stimuli in Patients with Disorders of Consciousness.Frontiers in psychology · 2016Article
- Intrathecal baclofen: effects on spasticity, pain, and consciousness in disorders of consciousness and locked-in syndrome.Current pain and headache reports · 2015Review
- Spindles in Svarog: framework and software for parametrization of EEG transients.Frontiers in human neuroscience · 2015Article
- Preservation of electroencephalographic organization in patients with impaired consciousness and imaging-based evidence of command-following.Annals of neurology · 2014Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundElectroencephalography (EEG) is best suited for long-term monitoring of brain functions in patients with disorders of consciousness (DOC). Mathematical tools are needed to facilitate efficient interpretation of long-duration sleep-wake EEG recordings.
methodsStarting with matching pursuit (MP) decomposition, we automatically detect and parametrize sleep spindles, slow wave activity, K-complexes and alpha, beta and theta waves present in EEG recordings, and automatically construct profiles of their time evolution, relevant to the assessment of residual brain function in patients with DOC.
resultsAbove proposed EEG profiles were computed for 32 patients diagnosed as minimally conscious state (MCS, 20 patients), vegetative state/unresponsive wakefulness syndrome (VS/UWS, 11 patients) and Locked-in Syndrome (LiS, 1 patient). Their interpretation revealed significant correlations between patients' behavioral diagnosis and: (a) occurrence of sleep EEG patterns including sleep spindles, slow wave activity and light/deep sleep cycles, (b) appearance and variability across time of alpha, beta, and theta rhythms. Discrimination between MCS and VS/UWS based upon prominent features of these profiles classified correctly 87% of cases.
conclusionsProposed EEG profiles offer user-independent, repeatable, comprehensive and continuous representation of relevant EEG characteristics, intended as an aid in differentiation between VS/UWS and MCS states and diagnostic prognosis. To enable further development of this methodology into clinically usable tests, we share user-friendly software for MP decomposition of EEG (http://braintech.pl/svarog) and scripts used for creation of the presented profiles (attached to this article).
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