A comparison of neural networks algorithms for EEG and sEMG features based gait phases recognition

P Wei, J Zhang, F Tian, J Hong - Biomedical Signal Processing and Control, 2021 - Elsevier
Surface electromyography (sEMG) and electroencephalogram (EEG) can be utilized to
discriminate gait phases. However, the classification performance of various combination …

A multi-modal modified feedback self-paced BCI to control the gait of an avatar

B Alchalabi, J Faubert, DR Labbe - Journal of Neural Engineering, 2021 - iopscience.iop.org
Brain–computer interfaces (BCIs) have been used to control the gait of a virtual self-avatar
with a proposed application in the field of gait rehabilitation. Some limitations of existing …

Real-time decoding of eeg gait intention for controlling a lower-limb exoskeleton system

J Choi, H Kim - 2019 7th International Winter Conference on …, 2019 - ieeexplore.ieee.org
In this study, we demonstrate real-time gait intention recognition algorithm which can
decode voluntary gait execution from electroencephalography (EEG) for controlling the …

Different sEMG and EEG features analysis for gait phase recognition

P Wei, J Zhang, P Wei, B Wang… - 2020 42nd Annual …, 2020 - ieeexplore.ieee.org
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 …

Gaze based implicit intention inference with historical information of visual attention for human-robot interaction

Y Nie, X Ma - Intelligent Robotics and Applications: 14th International …, 2021 - Springer
Human-robot interaction (HRI) is the key capability for assistive robots to provide support for
the elders and impaired in daily activities. Implicit intention understanding is a challenge …