Abstract
EEG (electroencephalography) energy is an important evaluation indicator in brain death determination based on EEG analysis. In related works, the static EEG energy value can be discovered using EMD (empirical mode decomposition), MEMD (multivariate empirical mode decomposition) and 2T-EMD (turning tangent empirical mode decomposition) for EEG-based coma and quasi-brain-death analysis. However such methods are not time-varying and feasible. In this paper, we firstly propose the Dynamic 2T-EMD algorithm to evaluate the dynamic patients' EEG energy variation by the means of time window and time step method. With the time window sliding along the time axis in a time step, EEG energy of corresponding time step is computed and stored. The proposed algorithm is applied to analyze 19 cases of coma patients' EEG and 17 cases of quasi-brain-death patients' EEG. Two typical patients in coma and quasi-brain-death state and one special case who was from coma to quasi-brain-death have been taken as examples to give the algorithm performance. Results show that EEG energy in coma state are obviously higher than that in quasi-brain-death state, and even present the EEG energy change trend of every case, which can prevent loss of information and wrong analysis results caused by noise interference and provide scientific basis for doctors to evaluate patients' consciousness levels in brain death determination. The proposed algorithm will be very helpful to develop the real time brain death diagnostic system.
Highlights
Brain death is strictly defined that the complete, irreversible and permanent loss of brain and brain-stem function (Becheer et al, 1968; Wijdicks EFM et al, 2002)
The portable electroencephalograph with NEUROSCAN ESI-64 system was applied, where 7 electrodes were placed on the forehead of patients, respectively 6 exploring electrodes (Fp1, Fp2, F3, F4, F7, F8) and 1 ground electrode (GND), and 2 electrodes (A1, A2) as reference electrodes were placed on earlobes
We have proposed the Dynamic 2T-EMD by extending 2T-EMD to analyze dynamically EEG energy
Summary
Brain death is strictly defined that the complete, irreversible and permanent loss of brain and brain-stem function (Becheer et al, 1968; Wijdicks EFM et al, 2002). 2010), and 2T-EMD (Julien Fleureau et al, 2011) are applied to analyze coma and quasi-brain-death patients' EEG. Niedermeyer et al, 1991), and EMD based static algorithms such as EMD, MEMD, and 2T-EMD were all applied to process EEG and compute EEG energy We firstly propose the Dynamic 2T-EMD to analyze dynamically coma and quasi-brain-death patients' EEG. Because of the non-stationarity feature of EEG, the results obtained can reflect dynamically patients' status of the whole period of measurement time and avoid the loss of information and wrong results caused by noise interference, which can provide doctors with the objective and scientific criterian for the clinical diagnosis of brain death determination. The developed algorithm is extremely important to the real time brain death diagnostic system
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