An EEG diagnosis system for quasi brain death based on complexity and energy analyses

Electroencephalogram (EEG) is often used in confirmatory test for brain death determination in clinical practice. Because the EEG measuring and monitoring is relatively safe and reliable for deep comatose patients, it is believed to be valuable for reducing the risk of diagnosis or prevent mistaken diagnosis of brain death. In this paper, we present EEG complexity analysis and EEG energy analyses for the EEG acquisition of 35 adult patients. In EEG complexity analysis, we firstly report statistically significant differences of quantitative statistics in this clinical study. Next, for the patient-wise case study, we develop a dynamical calculating entropy method to monitor the symptom change of patients. In EEG energy analysis, we firstly accumulate the EEG energy from the extracted components that are related to the brain activities. Then, we evaluate the energy differences between deep comatose patients and brain death. The empirical results reported in this paper suggest some promising directions and valuable clues for clinical practice.