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Low-complexity Power Spectral Density Estimation

机译:低复杂性功率谱密度估计

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This paper presents a method of feature extraction to detect seizure in epileptic patients. Epileptic seizures are characterized by high amplitude and synchronized electrocephalogram (EEG) waveforms. Power spectral density (PSD) of the EEG signal plays an important role in diagnosis of epilepsy. Many automated diagnostic systems for epileptic seizure detection have emerged in recent years. This paper proposes a method of extracting PSD of EEG sub-bands using lowcomplex PSD estimation method which would reduce the automatic diagnostic system complexity and also enhances the speed. Low-complexity PSD estimation method was implemented in digital signal processor (TMS320C6713), and the result was very much similar to traditional Welch PSD estimation method with 30 % reduction in computation time.
机译:本文介绍了一种特征提取方法,以检测癫痫患者的癫痫发作。癫痫发作的特征在于高振幅和同步的电气图(EEG)波形。 EEG信号的功率谱密度(PSD)在癫痫诊断中起重要作用。近年来出现了许多用于癫痫癫痫发作检测的自动诊断系统。本文采用了利用低曲目PSD估计方法提取了EEG子带的PSD的方法,这将降低自动诊断系统复杂性,并增强速度。在数字信号处理器(TMS320C6713)中实现了低复杂性PSD估计方法,结果非常类似于传统的Welch PSD估计方法,计算时间减少30%。

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