Application of nonlinear dynamics analysis in assessing unconsciousness: A preliminary study

Wu, Dongyu; Cai, Gui; Yuan, Ying; Lin, Liangxu; Li, Guangqing; Song, Weiqun; Wang, Maobin

doi:10.1016/j.clinph.2010.05.036

Cited by 68 publications

(61 citation statements)

References 53 publications

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“…It has been found to be reliable with short data sets [5]. This method has been widely applied to medical studies including investigations into AD [5], Parkinson's disease [9] and coma [10] along with many others. In order to apply LZC the signal must first be parsed.…”

Section: Lempel-ziv Complexitymentioning

confidence: 99%

Investigation of Alzheimer’s Disease EEG Frequency Components with Lempel-Ziv Complexity

2015

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Abstract-This pilot study applied Lempel-Ziv Complexity (LZC) to 22 resting EEG signals, collected using the 10-20 international system, from 11 patients with Alzheimer's disease (AD) and 11 age-matched controls. This allowed for frequency band analysis as the EEG signals were first prefiltered with a third order Hamming window in the ranges F to F+WHz with both F and W equal to 1-30Hz respectively. Control subjects were found to have a greater signal complexity than AD patients with statistically significant bands seen at various ranges in all 16 electrodes. The maximum statistical significance (Student's t test, p<0.01) was increased over the findings with traditional signal filtering techniques allowing the whole range, with a maximum significance of p=3.50e -6 at electrode T4 between 7-18Hz. Electrode F4 also showed significantly high statistically significant differences. The maximum accuracy, both controls and AD patients correctly identified, found with Receiver Operating Characteristic Curves was 95.45% (21 of 22 subjects correctly classified) at T4 (7-18Hz and 7-20Hz), Fp2 (8-32Hz) and F4 (6-21Hz), which is significantly more accurate than the most accurate methods previously applied to this dataset. The beta band (13-30Hz) was found to be most influential in separating the two test groups in this study with the best range suggested to be 5-26Hz, combining traditional theta, alpha and beta bands. These findings suggest pre-filtering has a significant effect on method outcomes and can be successfully tailored to improve the statistical effectiveness of LZC at distinguishing between these two EEG groups. However, more testing is required to investigate the effectiveness at distinguishing other signal dynamics.

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Section: Lempel-ziv Complexitymentioning

confidence: 99%

Investigation of Alzheimer’s Disease EEG Frequency Components with Lempel-Ziv Complexity

2015

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“…Among possible nonlinear dynamics measures, the approximate entropy (ApEn) is particularly useful for short, noisy time series because it is capable of providing a robust, model-independent, information-theoretic estimation of dynamical complexity [19]. Prior studies have demonstrated that EEG-based ApEn can be a sensitive discriminator of various neurophysiological conditions such as sleep, Alzheimer's disease, attention-deficit/hyperactivity disorder and unconsciousness assessment [20][21][22][23]. Therefore, EEG nonlinear analysis may be utilized to provide information about cortical excitability.…”

mentioning

confidence: 99%

Effects of transcranial direct current stimulation on language improvement and cortical activation in nonfluent variant primary progressive aphasia

Wang

Chen³

et al. 2013

Neuroscience Letters

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“…Prolonged impaired consciousness (MCS and VS) have not been studied in such detail. Wu et al studied 21 subjects in PVS and 16 in MCS and founded that SSEPs failed to distinguished subjects in PVS from those in MCS, which indicated that this measure might be limited in predicting outcome in this population (Wu et al , 2011a).…”

Section: Somatosensory Evoked Potentials (Seps) and Unconsciousnessmentioning

confidence: 99%

“…The author considered that with EEG nonlinear analysis, the degree of suppression for PVS and MCS could be quantified and the changes of brain function for unconscious subjects could be captured by NDA. The possible mechanism might be that recovery of unconsciousness and the degree of suppression of unconsciousness are mediated through the brain cortex; NDA can reflect different levels of consciousness by measuring the complexity of the neuron networks in the brain cortex (Wu, Cai, 2011a). Further study with C-ApEn was carried out to investigate the cortical response to painful and auditory stimuli for subjects in PVS and MCS, and measure the interconnection of the residual cortical functional islands.…”

Section: Application Of Nda In Assessing Unconsciousnessmentioning

confidence: 99%

Electroencephalography (EEG) and Unconsciousness

Wu¹,

Yuan²

2012

Advances in Clinical Neurophysiology

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Application of nonlinear dynamics analysis in assessing unconsciousness: A preliminary study

Cited by 68 publications

References 53 publications

Investigation of Alzheimer’s Disease EEG Frequency Components with Lempel-Ziv Complexity

Investigation of Alzheimer’s Disease EEG Frequency Components with Lempel-Ziv Complexity

Effects of transcranial direct current stimulation on language improvement and cortical activation in nonfluent variant primary progressive aphasia

Electroencephalography (EEG) and Unconsciousness

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