Quantitative Electroencephalography Analysis for Improved Assessment of Consciousness in Cerebral Hemorrhage and Ischemic Stroke Patients

Consciousness is frequently assessed in acutely brain-injured patients. However, a direct measure of consciousness based on neurological examinations and behavioral observations is time-consuming and costly in medical labors. This paper aims to explore effective quantitative electroencephalography (EEG) measures to facilitate the objective assessment of consciousness. We do two studies in this paper. In the first study, the EEG signals recorded from 27 cerebral hemorrhage patients are analyzed to explore whether the phase synchrony index is effective in distinguishing the states of consciousness in cerebral hemorrhage patients. In the second study, 14 EEG recordings from four ischemic stroke patients, who have experienced more than two types of conscious disturbance, are studied to complement the analysis of the longitudinal value of the phase synchrony index. In both studies, a weighted sum of the six quantitative EEG features is analyzed on its correlation with the level of consciousness, and a linear regression model is built for the correlation analysis. In the first study, the phase synchrony index of the left and the right hemispheres (PSI-LR) in the beta band has shown a significant correlation with the level of consciousness in cerebral hemorrhage patients (Pearson correlation coefficients <inline-formula> <tex-math notation="LaTeX">$\rho = 0.500$ </tex-math></inline-formula> and Spearman correlation coefficients <inline-formula> <tex-math notation="LaTeX">$\rho = 0.400$ </tex-math></inline-formula>). In the second study, PSI-LR also shows a high correlation with the longitudinal changes of consciousness in ischemic stroke patients (Pearson correlation coefficients <inline-formula> <tex-math notation="LaTeX">$\rho = 0.884$ </tex-math></inline-formula> and Spearman correlation coefficients <inline-formula> <tex-math notation="LaTeX">$\rho = 0.887$ </tex-math></inline-formula>). Furthermore, the linear regression model combining the six quantitative EEG (QEEG) features shows a determination coefficient of 44.2% in cerebral hemorrhage patients and 83.8% in longitudinal ischemic stroke investigations, respectively. The PSI-LR is an effective indicator in not only identifying the disturbance of consciousness in cerebral hemorrhage patients, but also monitoring the changes of consciousness in ischemic stroke patients. A linear combination of the six QEEG features investigated in this paper is a new measure to improve the assessment of consciousness.