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  • БОС-тренинг в реабилитации пациентов с неврологическими нарушениями при постковидном синдроме: рандомизированное контролируемое исследование
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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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БОС-тренинг в реабилитации пациентов с неврологическими нарушениями при постковидном синдроме: рандомизированное контролируемое исследование

Анналы клинической и экспериментальной неврологии. 2025. Т. 19. № 3. С. 14–26.
Черкасова А. Н., Иконникова Е. С., Люкманов Р. Х., Кириченко О. А., Mokienko O., Конышев В. А., Зонов А. А., Супонева Н. А., Пирадов М. А.

Introduction. The high prevalence of post-COVID syndrome (PCS), which frequently manifests with emotional disturbances, cognitive impairment, and asthenia, necessitates effective rehabilitation methods. One potential approach is electroencephalography (EEG)-based biofeedback (BFB) therapy, though its use in PCS management has been explored in only a few studies to date.

The study aimed to evaluate the effects of EEG α-rhythm BFB training on emotional state and cognitive function recovery, and reduction of astheniа symptoms in PCS patients.

Materials and methods. Patients diagnosed with U09. Post-COVID-19 condition were randomly assigned to two groups of 10 participants each. The main group underwent 12–15 sessions of EEG α-rhythm BFB training using the NeuroPlay-6C headset with the Neurocorrection of COVID-19 Psychoemotional Consequences protocol, while the control group received identical training without biofeedback. Assessments performed before and after the intervention included: emotional state evaluation (State-Trait Anxiety Inventory [STAI], Short Health Anxiety Inventory [SHAI], Beck Depression Inventory [BDI], Psychological Stress Measure [PSM-25]), cognitive function assessment (Addenbrooke’s Cognitive Examination III [ACE-III], Schulte tables, Stroop test, Tower of London test, N-back test, 10-word memory test), assessment of asthenia (Multidimensional Fatigue Inventory [MFI]), and sleep quality evaluation (Insomnia Severity Index [ISI]).

Results. In both groups, the training resulted in a significant reduction of personal anxiety, psychological stress, depression, and asthenia. The main group additionally demonstrated decreased health-related anxiety and improved information retention parameters. Intergroup comparison revealed more pronounced dynamics in the main group: greater reduction of general fatigue manifestations, increased immediate word recall volume, and improved retention of verbal information in working memory. The proportion of patients transitioning to milder symptom severity levels on individual scales was comparable between both groups.

Conclusion. EEG α-rhythm biofeedback training can be implemented at the outpatient rehabilitation stage for PCS patients.

Research target: Clinical Medicine Medical Technologies Psychology
Language: Russian
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Keywords: нарушения эмоциональной сферыкогнитивные нарушенияcognitive impairmentpost-COVID syndromeemotional disordersastheniaelectroencephalographic biofeedbackпостковидный синдромастениябиологическая обратная связь по электроэнцефалографии
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