Lower limb muscle activity during neurointerface control: neurointerface based on motor imagery of walking

The question of the activity of muscles that provide the realization of imaginary movement is essential in the rehabilitation of motor disorders using neurointerfaces. The literature data on this issue are contradictory. The paper analyzes the EMG activity of the shin and thigh muscles of 40 healthy volunteers when working with a neurointerface based on kinesthetic motor imagery of walking in place and supplemented with the «Biokin» robotic limb movement device (mechanotherapy), activated in case of successful motor imagery. It is shown that working with a neurointerface, on average for subjects, leads to an increase in muscle activity when motor imagery of walking compared to rest, and activation of the mechanical training device (AM) further increases muscle activity, with its effect being more pronounced in the muscles of the leg from which motor imagery of walking begins. The nature of muscle reactions to the task of motor imagery of walking is individual. AM when working with a neurointerface, the number of subjects with pronounced EMG activity increases, as does the number of significant correlations between the activity of the muscles of the lower limbs. Thus, the use of neurointerfaces based on motor imagery of walking and the addition of AM as feedback allows activating the muscles of the lower extremities, which is important in clinical practice in the rehabilitation of movements.

Authors

Institutions

Publication Details

Journal
Журнал высшей нервной деятельности им И П Павлова
Published
2024-11-27
DOI
https://doi.org/10.31857/s0044467724050042
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Lower limb muscle activity during neurointerface control: neurointerface based on motor imagery of walking

В. В. Решетникова, Yury Gerasimenko, М. Р. Исаев, Pavel Bobrov et al.
Журнал высшей нервной деятельности им И П Павлова
EEG and Brain-Computer Interfaces
article

Lower limb muscle activity during neurointerface control: neurointerface based on motor imagery of walking

В. В. Решетникова, Yury Gerasimenko, М. Р. Исаев, Pavel Bobrov, E. V. Bobrova, N. A. Chsherbakova, Е. А. Вершинина, И. Н. Богачева, А. А. Гришин
article en

Abstract

The question of the activity of muscles that provide the realization of imaginary movement is essential in the rehabilitation of motor disorders using neurointerfaces. The literature data on this issue are contradictory. The paper analyzes the EMG activity of the shin and thigh muscles of 40 healthy volunteers when working with a neurointerface based on kinesthetic motor imagery of walking in place and supplemented with the «Biokin» robotic limb movement device (mechanotherapy), activated in case of successful motor imagery. It is shown that working with a neurointerface, on average for subjects, leads to an increase in muscle activity when motor imagery of walking compared to rest, and activation of the mechanical training device (AM) further increases muscle activity, with its effect being more pronounced in the muscles of the leg from which motor imagery of walking begins. The nature of muscle reactions to the task of motor imagery of walking is individual. AM when working with a neurointerface, the number of subjects with pronounced EMG activity increases, as does the number of significant correlations between the activity of the muscles of the lower limbs. Thus, the use of neurointerfaces based on motor imagery of walking and the addition of AM as feedback allows activating the muscles of the lower extremities, which is important in clinical practice in the rehabilitation of movements.

Журнал высшей нервной деятельности им И П ПавловаVol. 74(5)
Pirogov Russian National Research Medical University (RU), Pavlov Institute of Physiology of the Russian Academy of Sciences (RU), Institute of Higher Nervous Activity and Neurophysiology (RU)
Good health and well-being
Openalex Percentile: Top 78%
EEG and Brain-Computer Interfaces
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.