Algorithm based on the short-term Rényi entropy and IF estimation for noisy EEG signals analysis

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• 作者：Jonatan Lerga^a ; ^{jlerga@riteh.hr}Author Vitae ; Nicoletta Saulig^b ; ^{nsaulig@riteh.hr}Author Vitae ; Vladimir Mozetič^c ; ^{vladimir.mozetic@ri.t-com.hr}Author Vitae
• 关键词：Ré ; nyi entropy ; Short-term Ré ; nyi entropy (STRE) ; Instantaneous frequency (IF) estimation ; EEG signals ; Time-frequency signal analysis
• 刊名：Computers in Biology and Medicine
• 出版年：2017
• 出版时间：1 January 2017
• 年：2017
• 卷：80
• 期：Complete
• 页码：1-13
• 全文大小：1396 K
• 卷排序：80

文摘

Modification of Renyi entropy was proposed and applied to EEG analysis in timefrequency domain. Renyi entropy was upgraded by the component separation and instantaneous frequency estimation. The proposed method was tested on both noisy and noise-free EEG signals. Achieved results showed that proposed method was robust up to moderate noise levels. Extracting EEG components and IF estimation show large potential to enhance clinical diagnostics.