Complexity measurements of Electroencephalograph (EEG) recordings using sample entropy algorithm in patients with temporal lobe epilepsy
一种改进的近似熵——样品熵及其在颞叶癫痫患者脑电信号分析中的应用

The potential application of entropy measurements to analyze short-term Electrocephalograph (EEG) traces of patients with temporal lobe epilepsy (TLE) was investigated. Total eight channels EEG signals, collected from 8 patients and 10 healthy subjects, were analyzed by both algorithms of the approximate entropy (ApEn) and sample entropy (SampEn). Two sliding windows and 5 different filters levels r were used and discussed. The entropies of EEG were significantly lower in patients with TLE than that in healthy one. The degree of complexity in the epileptic focus hemisphere was lower than in the non-focus hemisphere in patients. Small sliding window may provide more details associated with the seizure. The filter level r must not be smaller than 0.15% SD for 1 s-window whilst it must not be smaller than 10% SD for 4 s-window. The results have demonstrated that entropy measurements could be alternative nonlinear approaches for analyzing short-term EEG signals. The observed lower values in the complexity of the EEG signal for patients with TLE provide preliminary support for the notion that the complex nonlinear nature of brain electrical activity may be the result of isolation or impairment of the neural information transmission within the brain.