Application of nonlinear dynamics analysis in assessing unconsciousness: a preliminary study.

ABSTRACT

OBJECTIVES: To quantify the degree of unconsciousness with EEG nonlinear analysis and investigate the change of EEG nonlinear properties under different conditions. METHODS: Twenty-one subjects in persistent vegetative state (PVS), 16 in minimally conscious state (MCS) and 30 normal conscious subjects (control group) with brain trauma or stroke were involved in the study. EEG was recorded under three conditions eyes closed, auditory stimuli and painful stimuli. EEG nonlinear indices such as Lempel-Ziv complexity (LZC), approximate entropy (ApEn) and cross-approximate entropy (cross-ApEn) were calculated for all the subjects. RESULTS: The PVS subjects had the lowest nonlinear indices followed by the MCS subjects and the control group had the highest. The PVS and MCS group had poorer response to auditory and painful stimuli than the control group. Under painful stimuli, nonlinear indices of subjects who recovered (REC) increased more significantly than non-REC subjects. CONCLUSIONS: With EEG nonlinear analysis, the degree of suppression for PVS and MCS could be quantified. The changes of brain function for unconscious subjects could be captured by EEG nonlinear analysis. SIGNIFICANCE: EEG nonlinear analysis could characterise the changes of brain function for unconscious state and might have some value in predicting prognosis of unconscious subjects.