Time Series Data Analysis of Mindfulness Breathing Method Using Electroencephalogram

Author: Eiichi Togo1
Affiliation: <sup>1</sup> Faculty of Nursing/Department of Nursing, Hyogo University, Kakogawa City, Japan.
Conference/Journal: SAGE Open Nurs
Date published: 2024 Jan 23
Other: Volume ID: 10 , Pages: 23779608231226073 , Special Notes: doi: 10.1177/23779608231226073. , Word Count: 207


Introduction:
Workers and students are often stressed and distressed by a variety of factors, including work and study. However, support for individual psychological stress is not yet well established.

Objective:
This study aimed to evaluate the effect of mindfulness breathing on the mental load of college students using an electroencephalogram (EEG).

Methods:
Twenty participants were randomly allocated into treatment or control groups, with 10 participants in each group. Mindfulness breathing was applied to participants in the treatment group, while those in the control group received no treatment. The regression equation was evaluated from the EEG, and time series analysis was performed based on autocorrelation and partial autocorrelation.

Results:
In the After condition after mindfulness breathing exercises in the Mi group, the alpha wave content of the regression equation at eye closure after task performance showed an upward trend, and the autocorrelation coefficient showed repeated upward and downward fluctuations.

Conclusion:
It was suggested that alpha wave content may increase over time with mindfulness breathing exercises. The EEG after mindfulness breathing exercises was shown not to be constant and to have non-linear characteristics. This suggested that the effects of mindfulness breathing exercises could be evaluated using time series data.

Keywords: electroencephalogram; mindfulness breathing; time series data.

PMID: 38268948 PMCID: PMC10807306 DOI: 10.1177/23779608231226073