ArticleCognitive neurodynamics2008
An empirical EEG analysis in brain death diagnosis for adults.
Article in Cognitive neurodynamics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Article
- A Hybrid System for Distinguishing between Brain Death and Coma Using Diverse EEG Features.Sensors (Basel, Switzerland) · 2019Article
- Parameters of stochastic models for electroencephalogram data as biomarkers for child's neurodevelopment after cerebral malaria.Journal of statistical distributions and applications · 2018Article
- Evaluation of local field potential signals in decoding of visual attention.Cognitive neurodynamics · 2015Article
- Power spectral density and coherence analysis of Alzheimer's EEG.Cognitive neurodynamics · 2015Article
- Classifying human operator functional state based on electrophysiological and performance measures and fuzzy clustering method.Cognitive neurodynamics · 2013Article
- Predictive modeling of human operator cognitive state via sparse and robust support vector machines.Cognitive neurodynamics · 2013Article
- Analyzing EEG of quasi-brain-death based on dynamic sample entropy measures.Computational and mathematical methods in medicine · 2013Article
- Investigation of changes in EEG complexity during memory retrieval: the effect of midazolam.Cognitive neurodynamics · 2012Article
- Answering six questions in extracting children's mismatch negativity through combining wavelet decomposition and independent component analysis.Cognitive neurodynamics · 2011Article
- Selecting EEG components using time series analysis in brain death diagnosis.Cognitive neurodynamics · 2011Article
- New mechanics of traumatic brain injury.Cognitive neurodynamics · 2009Article
- On the synchrony of steady state visual evoked potentials and oscillatory burst events.Cognitive neurodynamics · 2009Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Electroencephalogram (EEG) is often used in the confirmatory test for brain death diagnosis in clinical practice. Because EEG recording and monitoring is relatively safe for the patients in deep coma, it is believed to be valuable for either reducing the risk of brain death diagnosis (while comparing other tests such as the apnea) or preventing mistaken diagnosis. The objective of this paper is to study several statistical methods for quantitative EEG analysis in order to help bedside or ambulatory monitoring or diagnosis. We apply signal processing and quantitative statistical analysis for the EEG recordings of 32 adult patients. For EEG signal processing, independent component analysis (ICA) was applied to separate the independent source components, followed by Fourier and time-frequency analysis. For quantitative EEG analysis, we apply several statistical complexity measures to the EEG signals and evaluate the differences between two groups of patients: the subjects in deep coma, and the subjects who were categorized as brain death. We report statistically significant differences of quantitative statistics with real-life EEG recordings in such a clinical study, and we also present interpretation and discussions on the preliminary experimental results.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.