| 基于分形理论的麻醉监测诱发脑电信号识别方法研究 |
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| 引用本文： | 张烈平,莫玮.基于分形理论的麻醉监测诱发脑电信号识别方法研究[J].微电子学与计算机,2010,27(2). |
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| 作者姓名： | 张烈平 莫玮 |
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| 作者单位： | 1. 桂林理工大学,机械与控制工程学院,广西,桂林,541004
2. 工业和信息化部,北京,100804 |
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| 摘 要： | 提出了一种基于分形理论的麻醉监测诱发脑电信号识别方法.首先给出了麻醉监测中潜伏期听觉诱发脑电信号的数学模型,产生与实际信号相符的模拟脑电信号,然后对脑电信号进行小波降噪,提取降噪后脑电信号的关联维数,最后通过关联维数的大小识别麻醉状态下中潜伏期听觉诱发脑电信号的类型.实验仿真结果表明:提出的识别方法具有较高的识别率.
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| 关 键 词： | 分形理论 关联维数 小波变换 中潜伏期诱发脑电 麻醉监测 信号识别 |
Research on the Method of Identification Evoked Potential Signal During Anesthesia Monitoring Based on Fractal Theory |
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| ZHANG Lie-ping,MO Wei.Research on the Method of Identification Evoked Potential Signal During Anesthesia Monitoring Based on Fractal Theory[J].Microelectronics & Computer,2010,27(2). |
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| Authors: | ZHANG Lie-ping MO Wei |
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| Abstract: | A identification method based on fractal theory was proposed. First, the simulation model of mid - latency auditory evoked potentials (MLAEP) signal is gave out and the simulation MLAEP signal which is according with reality during anesthesia monitoring is built up. Then, the noise in evoked potential signal is denoised through the wavelet transform method and the correlation dimensions are computed. Finally, according to the correlation dimension, the signal type is I-dentified for evoked potential signal during anesthesia monitoring. The experimental simulation results show that the proposed method has higher identification rate for MLAEP during anesthesia states. |
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| Keywords: | fractal theory correlation dimension wavelet transform MLAEP anesthesia monitoring signal identification |
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