Complexity Analysis of EEG Data with Multiscale Permutation Entropy

摘要：

In this study, we propose a powerful tool, called multiscale permutation entropy (MPE), to evaluate the dynamical characteristics of electroencephalogram (EEG) at the duration of epileptic seizure and seizure-free states. Numerical simulation analysis shows that MPE method is able to distinguish between the stochastic noise and deterministic chaotic data. The real EEG data analysis shows that a high entropy value is assigned to seizure-free EEG recordings and a low entropy value is assigned to seizure EEG recordings at the major scales. This result means that EEG signals are more complex in the seizure-free state than in the seizure state.

关键词： Multiscale permutation entropy Epileptic EEG Complexity

作者: Gaoxiang Ouyang Chuangyin Dang Xiaoli Li

作者单位: Department of MEEM, City University of Hong Kong, Kowloon, Hong Kong

会议类型: 国际会议

会议名称: The Second International Conference on Cognitive Neurodynamics--2009(第二届国际认知神经动力学会议)

会议地点: 杭州

会议语种:英文

页码: 741-746

在线出版日期: 2009-11-15（万方平台首次上网日期，不代表论文的发表时间）