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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kantelhardt, J.W., Koscielny-Bunde, E., Rego, H.H.A., Havlin, S., Bunde, A.: Detrended long-range correlations with detrended fluctuation analysis. Physica A: Stat. Mech. Appl. 296, 441–454 (2001)
Adda, A., Benoudnine, H.: Detrended fluctuation analysis of EEG recordings for epileptic seizure detection. In: IEEE International Conference on Bio-engineering for Smart Technologies (BioSMART), pp. 1–4 (2016)
Peng, C.K., Havlin, S., Stanley, H.E., Goldberger, A.: Quantification of scaling exponents and crossover phenomena in non-stationary heartbeat time series. CHAOS 5(1), 85–87 (1995)
Jospin, M., Caminal, P., Jensen, E.W., Litvan, H., Vallverdú, M., Struys, M.M.R.F., Vereecke, H.E.M., Kaplan, D.T.: Detrended fluctuation analysis of EEG as a measure of depth of anesthesia. IEEE Trans. Biomed. Eng. 54(5), 840–846 (2007)
Varela, M., Vigil, L., Rodriguez, C., Vargas, B., GarcÃa-Carretero, R.: Delay in the detrended fluctuation analysis crossover point as a risk factor for type 2 diabetes mellitus. J. Diabetes Res. 1–6 (2016)
RodrÃguez de Castro, C., Vigil, L., Vargas, B., Delgado, E.G., Carretero, R.G., Ruiz-Galiana, J., Varela, M.: Glucose time series complexity as a predictor of type 2 diabetes. Diabetes/Metab. Res. Rev. 33, 1–9 (2017)
Zebende, G.F., Oliveira Filho, F.M., Leyva Cruz, J.A.: Auto-correlation in the motor/imaginary human EEG signals: a vision about the FDFA fluctuations. PLoS ONE 12(9), 1–13 (2017)
Hardstone, R., Poil, S.S., Schiavone, G., Jansen, R., Nikulin, V.V., Mansvelder, H.D., Linkenkaer-Hansen, K.: Detrended fluctuation analysis: a scale-free view on neuronal oscillations. Front. Physiol. 3(450), 1–13 (2012)
Weissman, A., Binah, O.: The fractal nature of blood glucose fluctuations. J. Diabetes Complicat. 28 646–651(2014)
Abasolo´, D., Hornero, R., Escudero, J., Espino, P.: A study on the possible usefulness of detrended fluctuation analysis of the electroencephalogram background activity in Alzheimer’s disease. IEEE Trans. Biomed. Eng. 55 (9) 2171–2179 (2008)
Phothisonothai, M., Nakagawa, M.: Fractal-based EEG data analysis of body parts movement imagery tasks. J. Physiol. Sci. 57(4) 217–226 (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-981-13-1513-8_78
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-1512-1
Online ISBN: 978-981-13-1513-8
eBook Packages: EngineeringEngineering (R0)