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The Detrended Fluctuation Analysis of EEG Signals: A Meditation-Based Study

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Computing, Communication and Signal Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 810))

Abstract

The Detrended Fluctuation Analysis is a widely used method for analysis of non-stationary time series which has been applied to EEG signals. The Detrended Fluctuation Analysis (DFA) of the EEG signals in pre- and post-meditation (mindfulness) intervention are compared. It is observed that the EEG data obtained from 8 subjects out of total 11 subjects shows reduction in the DFA values. The reduction in DFA values represents the lower intrinsic fluctuations in the EEG time series, which is a measure of better (higher) complexity of these vital rhythms. The reduced DFA values after 8 weeks of Focused Attention (mindfulness) meditation practice in more number of subjects, indicates that the meditation practice enhances the ability to handle complexity. The reduced DFA values indicate improved neuronal functioning of these subjects.

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Correspondence to Sunil R. Hirekhan .

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Hirekhan, S.R., Manthalkar, R., Phutke, S. (2019). The Detrended Fluctuation Analysis of EEG Signals: A Meditation-Based Study. In: Iyer, B., Nalbalwar, S., Pathak, N. (eds) Computing, Communication and Signal Processing . Advances in Intelligent Systems and Computing, vol 810. Springer, Singapore. https://doi.org/10.1007/978-981-13-1513-8_78

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  • DOI: https://doi.org/10.1007/978-981-13-1513-8_78

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  • Print ISBN: 978-981-13-1512-1

  • Online ISBN: 978-981-13-1513-8

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