Currently, the more commonly used clinical methods to evaluate the state of consciousness and its severity include the Glasgow Coma Scale, the Rappaport Coma Scale, and the JFK Coma Recovery Scale. These scales have difficulty capturing small changes in the state of consciousness, especially in patients in a vegetative state, minimally conscious state, dominant hemisphere impairment, and aphasia. In addition, any psychological test is only based on external behavioral performance or results to infer the higher mental activity of the human brain, so it is often somewhat subjective. The EEG signal contains a wealth of information about the cortical network level, especially the degree of synchronization of local neuronal networks and the coupling of distant cortical networks; the EEG signal contains a wealth of information related to conscious cognition. In addition, the cerebral cortex is the “terminal” of the effects of consciousness, i.e., the recovery of consciousness and the degree of inhibition are achieved through the functional activity of the cerebral cortex. Traditional EEG is mainly based on spectral analysis. Studies have shown that EEG waves in patients with disorders of consciousness can be classified as benign, malignant and indeterminate. Among them, malignant EEG types include diffuse slow waves, burst suppression, alpha coma, theta coma, and diffuse periodic complex waves. Certain EEG types are associated with poor prognosis and can be used as a predictor of eventual survival. However, conventional EEG analysis utilizes only a portion of the raw EEG information for analysis, which is bound to lose EEG information to the extent that it may affect the analysis of consciousness and cognitive function. Therefore, traditional EEG analysis can only be used as a crude and qualitative analysis. From the results of our study, we can see that after neuronal stimulation (e.g., nociceptive, acoustic stimulation, etc.), the neuronal network activity in the corresponding brain area increases, which is manifested as an increase in the complexity of neuronal network activity; the difference between the EEG nonlinear index in the state of sound stimulation and nociceptive stimulation in normal conscious persons compared with the state of quiet and closed eyes is statistically significant, indicating that sound and nociceptive stimulation can cause functional brain activity changes and were captured by EEG nonlinear analysis. We compared the difference between the nonlinear indices of sound or nociceptive stimulation and the quiet eyes-closed state in awake and non-awake patients, and showed that the difference in EEG nonlinear indices was significantly higher in awake patients than in non-awake patients in the nociceptive stimulation state. This result indicates that nociceptive stimulation can cause an increase in cortical functional activity in awakened patients, as indicated by an increase in the nonlinear index (similar to that of normally conscious individuals, except that the complexity of cortical functional activity is not increased to the same extent as in normally conscious individuals). In conclusion, EEG nonlinear analysis can quantitatively assess the degree of cortical inhibition in PVS and MCS patients. EEG nonlinear indices may have value in the prediction of awakening in PVS and MCS, and a good response to painful stimuli may imply a good prognosis.