Time Series Data Analysis of Mindfulness Breathing Method Using Electroencephalogram

Area of Science:

• Neuroscience
• Psychology
• Cognitive Science

Background:

• Work and study-related stress are prevalent among students.
• Effective interventions for psychological stress require further establishment.
• Mental load assessment in students is crucial for well-being.

Purpose of the Study:

• To evaluate the impact of mindfulness breathing on college students' mental load.
• To utilize electroencephalogram (EEG) for objective measurement of mental load.
• To explore the relationship between mindfulness breathing and EEG patterns.

Main Methods:

• Randomized controlled trial with 20 college students (10 per group).
• Treatment group received mindfulness breathing; control group received no intervention.
• EEG data analyzed using regression equations and time series analysis (autocorrelation).

Main Results:

• Mindfulness breathing showed an upward trend in alpha wave content post-intervention.
• EEG data exhibited non-linear characteristics and fluctuations.
• Autocorrelation coefficients demonstrated repeated upward and downward trends.

Conclusions:

• Mindfulness breathing may enhance alpha wave activity, potentially indicating reduced mental load.
• EEG time series analysis is a viable method for assessing mindfulness effects.
• The non-linear nature of EEG post-intervention suggests dynamic changes due to mindfulness.