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pro vyhledávání: '"Pengna Wei"'
Study of the Brain Functional Connectivity Processes During Multi-Movement States of the Lower Limbs
Publikováno v:
Sensors, Vol 24, Iss 21, p 7016 (2024)
Studies using source localization results have shown that cortical involvement increased in treadmill walking with brain–computer interface (BCI) control. However, the reorganization of cortical functional connectivity in treadmill walking with BCI
Externí odkaz:
https://doaj.org/article/0151b92a83a04c55a8f18cc00774a273
Publikováno v:
Frontiers in Neuroscience, Vol 15 (2021)
The classification of gait phases based on surface electromyography (sEMG) and electroencephalogram (EEG) can be used to the control systems of lower limb exoskeletons for the rehabilitation of patients with lower limb disorders. In this study, the s
Externí odkaz:
https://doaj.org/article/de8da106de7a4293b02ccd7a7a7f80ec
Publikováno v:
Frontiers in Neuroscience
Frontiers in Neuroscience, Vol 15 (2021)
Frontiers in Neuroscience, Vol 15 (2021)
The classification of gait phases based on surface electromyography (sEMG) and electroencephalogram (EEG) can be used to the control systems of lower limb exoskeletons for the rehabilitation of patients with lower limb disorders. In this study, the s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::143a3a236c2766d1ecab5eb68827207b
https://doi.org/10.3389/fnins.2021.607905
https://doi.org/10.3389/fnins.2021.607905
Correlations between Cortical and Locomotor Muscle in the Seven Gait Phases during Treadmill Walking
Background: Previous researchers have found that cortex is involved in the regulation of treadmill walking. However, cortico-muscular interaction analysis in a ‘fine’ gait phase (such as seven phases of the gait cycle) remains lacking in the time
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5183f580457c7e7e6e871e2b710f75e
https://doi.org/10.21203/rs.2.22753/v1
https://doi.org/10.21203/rs.2.22753/v1
Publikováno v:
Biomedical Signal Processing and Control. 68:102587
Surface electromyography (sEMG) and electroencephalogram (EEG) can be utilized to discriminate gait phases. However, the classification performance of various combination methods of the features extracted from sEMG and EEG channels for seven gait pha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb56ff091f5573a31caf89b1d549c7ca
https://doi.org/10.1016/j.bspc.2021.102587
https://doi.org/10.1016/j.bspc.2021.102587