Количественный анализ электроэнцефалографии у амбулаторных пациентов с психосоматическими проявлениями после COVID-19: НОВЫЕ ТЕХНОЛОГИИ В МЕДИЦИНЕ

Никита Юрьевич  Кипятков; Сергей Александрович  Лытаев; Нина Валентиновна  Скребцова; Виктория Витальевна  Гайворонская; Ксения Алексеевна  Бельская

doi:10.56871/RBR.2026.94.16.008

Quantitative electroencephalography analysis data in outpatient patients with psychosomatic manifestations following COVID-19

NEW TECHNOLOGIES IN MEDICINE

Nikita Yu. Kipyatkov Saint Petersburg State Pediatric Medical University https://orcid.org/0000-0003-3280-3679
Sergey A. Lytaev Saint Petersburg State Pediatric Medical University https://orcid.org/0000-0002-1291-0381
Nina V. Skrebtsova Saint Petersburg State Pediatric Medical University https://orcid.org/0009-0006-5641-8571
Victoria V. Gaivoronskaia Saint Petersburg State Pediatric Medical University https://orcid.org/0000-0001-6462-462X
Ksenia A. Belskaya Saint Petersburg State Pediatric Medical University https://orcid.org/0000-0002-9267-0639

Keywords:

electroencephalography EEG post-COVID condition spectral analysis EEG coherence analysis электроэнцефалография ЭЭГ постковид спектральный анализ когерентный анализ ЭЭГ

Abstract

Introduction.The electroencephalography is considered as the most important tool for assessing the spatiotemporal features of the electrical activity of the brain in the examination of patients with neurological manifestations of COVID-19, especially in cases of encephalopathy, seizures and epileptic status.Aim.It was planned to identify various electroencephalography patterns characteristic of the COVID-19 group of patients with visual electroencephalography analysis and to evaluate possible focal changes using quantitative methods such as spectral and coherent analysis.Materials and methods.The electroencephalography of 125 outpatient patients aged 16 to 68 years who were under observation at a neuropsychiatric dispensary with a history of COVID-19 and psychosomatic complaints at the time of the examination was recorded. The control group consisted of 45 healthy subjects.Results.The obtained results made it possible to divide the results of electroencephalography registration and analysis into three types of patterns: polymorphic low-frequency activity; low-frequency polymorphic activity with a predominance of slow waves (delta and theta bands); high-frequency electroencephalography with a dominant in the beta1 band.Conclusions.The formation of focal changes of a slow-wave nature with a characteristic localization in the right temporal region is noted in 20% of patients. The correlation index in the alpha range is stable for the electroencephalography of the control group, where 90% of the subjects had correlation coefficients in the alpha range of more than 0.6. On the contrary, a polymorphic pattern is observed among patients, stable indicators with a coefficient of more than 0.6 for all studied connections, both between the hemispheres and within the hemispheres, were recorded only in 25% of cases. The analysis of coherence coefficients in patients, on the contrary, shows a higher stability of interhemispheric connections and various options for reducing connections within the hemispheres, which often have a mirror character.

Author Biographies

Nikita Yu. Kipyatkov, Saint Petersburg State Pediatric Medical University

Cand. Sci. (Med.), Associate Professor, Department of Normal Physiology

Sergey A. Lytaev, Saint Petersburg State Pediatric Medical University

Dr. Sci. (Med.), Professor, Head of the Department of Normal Physiology

Nina V. Skrebtsova, Saint Petersburg State Pediatric Medical University

Dr. Sci. (Med.), Associate Professor, Department of Normal Physiology

Victoria V. Gaivoronskaia, Saint Petersburg State Pediatric Medical University

Cand. Sci. (Med.), Associate Professor, Department of Normal Physiology

Ksenia A. Belskaya, Saint Petersburg State Pediatric Medical University

Cand. Sci. (Med.), Associate Professor,Department of Normal Physiology

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Quantitative electroencephalography analysis data in outpatient patients with psychosomatic manifestations following COVID-19: NEW TECHNOLOGIES IN MEDICINE. (2026). Russian Biomedical Research, 11(1), 77-90. https://doi.org/10.56871/RBR.2026.94.16.008

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