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Application of Mathematical Modelling as a Tool to Analyze the EEG Signals in Rat Model of Focal Cerebral Ischemia

机译:数学模型作为分析局灶性脑缺血大鼠脑电信号的工具

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The present paper envisages the application of mathematical modelling with the autoregressive (AR) model method as a tool to analyze electroencephalogram data in rat subjects of transient focal cerebral ischemia. This modelling method was used to determine the frequencies and characteristic changes in brain waveforms which occur as a result of disorders or fluctuating physiological states. This method of analysis was utilized to ensure actual correlation of the different mathematical paradigms. The EEG data was obtained from different regions of the rat brain and was modelled by AR method in a MATLAB platform. AR modelling was utilized to study the long-term functional outcomes of a stroke and also is preferable for EEG signal analysis because the signals consist of discrete frequency intervals. Modern spectral analysis, namely AR spectrum analysis, was used to correlate the conditional and prevalent changes in brain function in response to a stroke.
机译:本文设想将自回归(AR)模型方法作为数学模型在分析短暂性局灶性脑缺血大鼠脑电图数据中的应用。这种建模方法用于确定由于疾病或生理状态波动而出现的脑部波形的频率和特征变化。这种分析方法被用来确保不同数学范式的实际相关性。脑电数据是从大鼠大脑的不同区域获得的,并通过AR方法在MATLAB平台中建模。 AR建模用于研究中风的长期功能结果,并且由于信号由离散的频率间隔组成,因此对于脑电信号分析也更适用。现代光谱分析,即AR光谱分析,用于关联中风后脑功能的条件性变化和普遍变化。

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