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周期图和自回归谱分析在脑电图信号中的应用。

Application of periodogram and AR spectral analysis to EEG signals.

作者信息

Akin M, Kiymik M K

机构信息

Department of Electrical Engineering, Dicle University, Diyarbakir/Turkey.

出版信息

J Med Syst. 2000 Aug;24(4):247-56. doi: 10.1023/a:1005553931564.

Abstract

In this study, in order to analyze the EEG signal, the conventional and modern spectral methods were investigated. Interpretation and performance of these methods were detected for clinical applications. For this purpose EEG data obtained from different persons were processed by PC computer using periodogram and AR model algorithms. Periodogram and AR modeling approaches were compared for their resolution and interpretation performance. It was determined that the AR approach is better for the use in clinical and research areas, because of the clear spectra that are obtained by it.

摘要

在本研究中,为了分析脑电图(EEG)信号,对传统和现代频谱方法进行了研究。检测了这些方法在临床应用中的解释和性能。为此,使用周期图和自回归(AR)模型算法,通过个人计算机对从不同人获取的EEG数据进行处理。比较了周期图和AR建模方法的分辨率和解释性能。结果表明,由于AR方法能获得清晰的频谱,因此在临床和研究领域的应用中表现更佳。

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