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 control is largely unknown. To investigate this, a public dataset, a mobile brain-body imaging dataset recorded during treadmill walking with a brain-computer interface, was used.
View Article and Find Full Text PDFThe 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 slope sign change (SSC) and mean power frequency (MPF) features of EEG and sEMG were used to recognize the seven gait phases [loading response (LR), mid-stance (MST), terminal stance (TST), pre-swing (PSW), initial swing (ISW), mid-swing (MSW), and terminal swing (TSW)]. Previous researchers have found that the cortex is involved in the regulation of treadmill walking.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2020
This research focuses on the gait phase recognition using different sEMG and EEG features. Seven healthy volunteers, 23-26 years old, were enrolled in this experiment. Seven phases of gait were divided by three-dimensional trajectory of lower limbs during treadmill walking and classified by Library for Support Vector Machines (LIBSVM).
View Article and Find Full Text PDFAnn Biomed Eng
January 2019
The goal of this study was to examine the optimal strategies for the recognition of gait phase based on surface electromyogram (sEMG) of leg muscles while children with cerebral palsy (CP) walked on a treadmill. Ten children with CP were recruited to participate in this study. sEMG from eight leg muscles and leg position signals were recorded while subjects walked on a treadmill.
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