Human motion intention (HMI) has increasingly gained concerns in lower limb exoskeletons
(LLEs). HMI recognition (HMIR) is the precondition for realizing active compliance control in …

Background and objective For patients with movement disorders, the main clinical focus is
on exercise rehabilitation to help recover lost motor function, which is achieved by relevant …

Considerable progress has been made in pattern recognition of surface electromyography
(sEMG) with deep learning, bringing improvements to sEMG-based gesture classification …

In order to reduce the gap between the laboratory environment and actual use in daily life of
human-machine interaction based on surface electromyogram (sEMG) intent recognition …

The cross-user gesture recognition is a puzzle in the myoelectric control system, owing to
great variability in muscle activities across different users. To address this problem, a novel …

Continuous motion prediction plays a significant role in realizing seamless control of robotic
exoskeletons and orthoses. Explicitly modeling the relationship between coordinated …

A long history has passed since electromyography (EMG) signals have been explored in
human-centered robots for intuitive interaction. However, it still has a gap between scientific …

How to learn informative representations from Electromyography (EMG) signals is of vital
importance for myoelectric control systems. Traditionally, hand-crafted features are extracted …

The electroencephalogram (EEG) and surface electromyogram (sEMG) fusion has been
widely used in the detection of human movement intention for human–robot interaction, but …

Objective: To address cross-user variability problem in the myoelectric pattern recognition, a
novel method for domain generalization and adaptation using both mix-up and adversarial …