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Study on non-linear bistable dynamics model based EEG signal discrimination analysis method

机译:基于非线性双稳态动力学模型的脑电信号判别分析方法研究

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摘要

Electroencephalogram (EEG) is the recording of electrical activity along the scalp. EEG measures voltage fluctuations generating from ionic current flows within the neurons of the brain. EEG signal is looked as one of the most important factors that will be focused in the next 20 years. In this paper, EEG signal discrimination based on non-linear bistable dynamical model was proposed. EEG signals were processed by non-linear bistable dynamical model, and features of EEG signals were characterized by coherence index. Experimental results showed that the proposed method could properly extract the features of different EEG signals.
机译:脑电图(EEG)是沿头皮的电活动记录。脑电图测量由离子流在大脑神经元内产生的电压波动。脑电信号被视为未来20年将关注的最重要因素之一。提出了基于非线性双稳态动力学模型的脑电信号识别方法。用非线性双稳态动力学模型处理脑电信号,并用相干指数表征脑电信号的特征。实验结果表明,该方法能够正确提取不同脑电信号的特征。

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