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Time Series Prediction for Biomedical Measurements using Fuzzy Logic

机译:模糊逻辑的生物医学测量时间序列预测

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In this paper is proposed an algorithm of prediction fuzzy for chaotic time series. This approach has been select because, in presence of specific pathologies, biomedical data may be represented as a chaotic time series. In particular, we are interested in monitoring the intracranial pressure (IP) of some patients in a state of coma who were suffering from intracranial hypertension syndrome. In these particular cases, prediction is necessary (from a diagnostic point of view) if you want to operate at the right moment on IP abnormal conditions. The proposed approach is based on a prediction multi-factor algorithm which doesn't need the knowledge of the mathematical working model of the biologic phenomenon, translating the real time series into a fuzzy time series.
机译:本文提出了一种用于混沌时间序列的预测模糊算法。这种方法已经选择,因为在特定病理学存在下,生物医学数据可以表示为混沌时间序列。特别是,我们有兴趣监测一些患有患有颅内高血压综合征的昏迷状态的患者的颅内压力(IP)。在这些特定的情况下,如果您想在IP异常情况下在正确的时刻运行,则需要预测(从诊断的角度来看)。该方法基于预测多因素算法,该算法不需要生物学现象的数学工作模型,将实时序列翻译成模糊时间序列。

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