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  • Инвазивные интерфейсы мозг–компьютер: 25 лет клинических испытаний, научные и практические вопросы
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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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Инвазивные интерфейсы мозг–компьютер: 25 лет клинических испытаний, научные и практические вопросы

Вестник Российской академии медицинских наук. 2024. Т. 79. № 5. С. 424–431.
Mokienko O.

A brain-computer interface (BCI) is a system that measures brain activity and converts it in real-time into functionally useful outputs to replace, restore, enhance, supplement, and/or improve the natural outputs of the brain. In invasive BCIs, electrodes are placed intracranially for more accurate and faster data exchange between the brain and external devices. The primary medical objective of these technologies is to compensate for motor or speech function in patients with tetraparesis and anarthria. In recent years, the emergence of new neuroimplants for BCIs and the results demonstrated in clinical trials have led to a notable increase in interest in these systems from the scientific community, investors, and the public. This review compares different types of medical invasive BCIs, analyzes and discusses the achievements and unsolved problems of clinical application of these neurotechnologies, as well as possible consequences and risks of their wider use.

Research target: Medical Technologies Basic Medicine Clinical Medicine
Language: Russian
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Keywords: интерфейс мозг-компьютерbrain-computer intefacetetraplegialocked-in syndromeтетраплегиясиндром запертого человека
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