期刊
出版社
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S0218348X23500111
关键词
Age; Electroencephalogram (EEG) Signals; Complexity; Fractal Theory; Sample Entropy; Sleep
One important research area in neuroscience is investigating how brain activity changes during aging. In this study, complexity techniques were used to analyze the age-related changes in brain activity during sleep. By analyzing the EEG signals of 22 subjects induced by sleep medication using fractal theory and sample entropy, it was found that the fractal dimension and sample entropy of EEG signals decrease with aging. Therefore, it was concluded that aging leads to lower complexity in EEG signals during sleep. The employed method of analysis can be applied to study the effects of aging on the activity variations of other organs, such as the heart and muscles, by analyzing their related physiological signals, such as ECG and EMG.
One of the important areas of research in neuroscience is to investigate how brain activity changes during aging. In this research, we employ complexity techniques to analyze how brain activity changes based on the age of subjects during sleep. For this purpose, we analyze the Electroencephalogram (EEG) signals of 22 subjects induced by sleep medication using fractal theory and sample entropy. The analysis showed that the fractal dimension and sample entropy of EEG signals decrease due to aging. Therefore, we concluded that aging causes lower complexity in EEG signals during sleep. The employed method of analysis could be applied to analyze the effect of aging on the variations of the activity of other organs (e.g. heart, muscle) during aging by studying their related physiological signals (e.g. ECG, EMG).
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