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نمایش مقاله

Title:

Evaluation of the Effects of tDCS on Neurological Complications of COVID-19 Using QEEG

Subject:

Clinical Applications of Brain Mappin

Presenter Author:
Name:	Mohadeseh Poradali

Author:
Name 1:	Mohadeseh Poradali - Corresponding - Presenter
Affiliation 1:	Imam Reza International University

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Abstract

Original Research

introduction :

The global outbreak of COVID-19 in late 2019 affected not only physical health but also neurological and psychological systems. The virus can directly or indirectly influence the central nervous system, leading to fatigue, behavioral changes, and emotional disorders such as anxiety and depression. This study aimed to evaluate post-COVID-19 stress and anxiety using Quantitative Electroencephalography (QEEG) and to investigate the effects of Transcranial Direct Current Stimulation (tDCS) as a non-invasive treatment method. Nonlinear analytical measures including Correlation Dimension, Lyapunov Exponent, and Higuchi Fractal Dimension were employed to analyze EEG signals from 12 patients diagnosed with post-COVID-19 stress and anxiety. The results revealed clear differences between pre- and post-stimulation brain activity patterns, indicating reduced stress and improved neural stability after tDCS sessions.

Methods:

In this study, EEG data were recorded using QEEG before and after tDCS stimulation. Nonlinear dynamic analysis was applied to quantify brain complexity using Correlation Dimension, Lyapunov Exponent, and Higuchi Fractal Dimension. The Correlation Dimension showed minor variations across all channels; however, these small numerical changes reflected significant information flow alterations in the brain. The Lyapunov Exponent varied across individuals, generally decreasing in frontal, temporal, and parietal regions and increasing in central and occipital areas after stimulation. The Higuchi Fractal Dimension decreased in most datasets, suggesting reduced signal complexity and neural stress. Additionally, theta wave intensity became more normalized post-stimulation, indicating relaxation. Alpha-band connectivity showed decreased interactions between frontal and posterior regions, consistent with reduced anxiety. FFT analysis was also performed for frequency-based validation but was found less informative than nonlinear metrics for representing global brain dynamics.

Results:

Statistical and visual analyses of EEG signals demonstrated clear distinctions between pre- and post-stimulation states. The mean Correlation Dimension decreased after tDCS, indicating lower neural complexity and reduced cognitive tension. The Lyapunov Exponent showed region-specific changes, reflecting dynamic shifts in brain stability. The Higuchi Fractal Dimension decreased in most participants, correlating with reduced anxiety and enhanced calmness. Theta wave normalization and altered alpha-band connectivity patterns supported the observed relaxation effects. Overall, nonlinear EEG measures provided more reliable indicators of stress reduction compared to traditional frequency-domain methods.

Conclusion:

This study demonstrates that tDCS, as a non-invasive neuromodulation technique, effectively reduces post-COVID-19 stress and anxiety by altering brain activity patterns measurable through QEEG and nonlinear analysis. The combined use of Correlation Dimension, Lyapunov Exponent, and Higuchi Fractal Dimension offers valuable insight into brain dynamics beyond traditional frequency analysis. Although the sample size was limited and demographic variables such as age and gender were not controlled, the results clearly show significant improvement in neural stability and mental relaxation after tDCS. Personalized stimulation protocols further highlight the case-based nature of this treatment. Therefore, integrating QEEG and nonlinear signal analysis provides an effective and quantitative approach for evaluating and guiding neurostimulation-based therapies in post-COVID-19 patients.

Keywords:

COVID-19, Nervous System, Stress, Anxiety, tDCS, QEEG, Correlation Dimension, Lyapunov Exponent, Higuchi Fractal Dimension