从标准EEG记录中预测发作
M Le Van Quyen1, J Martinerie, V Navarro
1Laboratoire de Neurosciences Cognitives et Imagerie Cérébrale, CNRS UPR 640, H pital de la Pitié-Salpêtrière, Paris, France.
Lancet (London, England)
|February 24, 2001
概括
现在可以使用标准头皮脑电图 (EEG) 信号预测发作. 对EEG数据的非线性分析可以提前几分钟预测发作,提高患者的安全性和临床应用.
科学领域:
- 神经科学是一个神经科学.
- 生物医学工程 生物医学工程
- 信号处理 信号处理
背景情况:
- 对内录像的非线性分析可以预测发作之前的情况.
- 使用标准头皮脑电图 (EEG) 预测发作仍然具有挑战性.
- 在临床应用中,从头皮EEG中获取前体变化至关重要.
研究的目的:
- 研究使用标准头皮EEG信号的非线性分析预测发作的可行性.
- 为了确定头皮脑电图记录中是否可以检测到前性变化.
主要方法:
- 分析了来自23名叶患者的26个头皮EEG/视频录像.
- 同时的头皮和内EEG记录被用于5名患者的比较.
- 非线性相似度用于实时识别长期扣押前变化.
主要成果:
- 在26个录音中,有25个预计会发作,平均预测时间为7分钟.
- 在头皮EEG中检测到的前性变化与同时进行的内EEG记录有很好的相关性.
- 非线性分析方法被证明对文物有很强的抵抗力.
结论:
- 头皮脑电图信号包含足够的动态信息来分析脑前的变化.
- 使用头皮EEG实时预测发作对于临床应用是可行的.
- 潜在的应用包括患者预警系统和预防干预.
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