Neurofeedback training for stress reduction and sleep improvement

Sleep disorders and chronic stress are pervasive issues in modern society. The "Stress Resistance" training program in the Mind Tracker BCI application aims to address these problems. This program consists of 25 levels, each involving a ten-minute neurofeedback session designed to teach users how to modulate their brain rhythms—specifically, increasing alpha wave power while decreasing beta wave power. The difficulty of each level adapts based on individual electroencephalogram (EEG) readings.

Alpha waves, with a frequency range of 8-12 Hz, are detectable in 85-95% of healthy adults, primarily in the occipital lobes. These waves reach their highest amplitude during relaxed wakefulness, especially with closed eyes, and are enhanced during meditation and relaxation. Alpha rhythm was the first brain wave utilized in neurofeedback systems (Kamiya, 2011). Today, alpha training, which aims to increase alpha wave power, is one of the most extensively researched and widely applied neurofeedback protocols. It has shown efficacy in treating various mental disorders and chronic pain, as well as in reducing anxiety and improving memory, cognitive function, and overall performance (Angelakis et al., 2007; Marzbani et al., 2016; Zoefel et al., 2011).

Beta waves oscillate at frequencies between 14-30 Hz and are most prominent in the frontal lobes during cognitive tasks, concentration, mental exertion, and emotional arousal. However, excessive beta activity has been associated with anxiety, attention disorders (Roohi-Azizi et al., 2017), and chronic stress (Díaz et al., 2019; Vanhollebeke et al., 2022; Jena, 2015).

Research has shown that increasing the ratio of alpha wave power to beta wave power, or to all other brain rhythms, contributes to improved sleep quality (Benatti et al., 2023; Gomes et al., 2016) and reduced stress levels (Hafeez et al., 2016, 2019).

This study evaluates the impact of the "Stress Resistance" training program in Mind Tracker BCI on these two key parameters: sleep quality and stress levels.

The study recruited 10 healthy participants (mean age 34 ± 4.4 years, mean ± SD) who reported ongoing sleep issues and chronic stress in a preliminary survey but had not sought medical intervention for these problems. The stress experienced by participants was predominantly work-related.

Participants completed two questionnaires at the beginning and end of the study:

Participants were instructed to complete the "Stress Resistance" training in the Mind Tracker BCI application daily, if possible, and to abstain from sleep aids and sedatives for the duration of the study. They also maintained a brief daily log, answering four questions about sleep duration, time to fall asleep, and subjective ratings of sleep quality and stress levels on a 10-point scale.

EEG data were recorded using the Neiry Headband device, which employs dry electrodes on four channels (O1, O2, T3, T4) with a sampling rate of 250 Hz.

Standard statistical tests were applied to process the collected data.

Upon completion of the study, 70% of participants reported perceived improvements in sleep quality and reduced stress levels. However, analysis of the daily subjective assessments of sleep quality and stress levels over the 25-day training period did not reveal significant changes. While the average sleep duration across the group remained stable, a significant decrease in sleep onset latency was observed (p < 0.01). The Mann-Kendall test was employed to identify trends in the data.

[Figure 1: Change in average time to fall asleep over 25 days of training. Data points represent the group average time to fall asleep for each day. The solid line indicates linear regression, with the shaded area representing the 95% confidence interval.]

Analysis of the questionnaire data revealed notable changes in participants' conditions (Figure 2). The Pittsburgh Sleep Quality Index (PSQI) uses a threshold score of 5 to indicate sleep problems. Prior to the study, the mean PSQI score for the group was 7.4 ± 2.29 (mean ± SD). Post-intervention, this score decreased to 5.6 ± 2.13, approaching the threshold for normal sleep quality. A Wilcoxon signed-rank test showed these changes to be statistically significant (p < 0.05).

The Psychological Stress Measure (PSM-25) also showed a reduction in scores, although this change was not statistically significant. The mean PSM-25 score decreased from 95.5 ± 25.61 pre-intervention to 78.0 ± 31.32 post-intervention. For context, scores below 100 indicate normal adaptation stress, scores between 100 and 155 suggest moderate stress, and scores above 155 indicate severe chronic stress. The lack of statistical significance may be attributed to the fact that most participants' initial scores were already within the range of normal psychological adaptation.

[Figure 2: A - Results of the Pittsburgh Sleep Quality Index (PSQI) before and after training. B - Results of the Psychological Stress Measure (PSM-25) before and after training.]

[Figure 3: Changes in relative power of brain rhythms across training levels. Data points represent group average values for each training level. Regression lines are shown with 95% confidence intervals indicated by shaded areas.]

As participants progressed through the training levels, we observed a decrease in the group average power of alpha rhythm and a concurrent decrease in beta rhythm power, aligning with the intended outcomes of the training program. These changes are consistent with previous research indicating that such shifts in brain wave activity can contribute to improved sleep quality, reduced stress levels, enhanced cognitive function and memory, and decreased anxiety (Gomes et al., 2016; Marzbani et al., 2016; Roohi-Azizi et al., 2017).

The 25-day "Stress Resistance" neurofeedback training program in Mind Tracker BCI demonstrated positive effects on participants' sleep quality. This improvement was evidenced by participants' subjective assessments at the study's conclusion, a significant reduction in average sleep onset latency throughout the study period, and improved scores on the Pittsburgh Sleep Quality Index.

While 70% of participants reported perceived reductions in stress levels, this was not consistently supported by other data. This discrepancy may be due to the fact that most participants' initial stress levels were already within the normal range according to the Psychological Stress Measure (PSM-25).

EEG data analysis revealed changes in brain rhythm ratios, specifically a decrease in relative beta power and an increase in relative alpha power. These changes align with existing literature correlating such shifts with improved sleep quality and reduced stress levels.

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