Myoelectric control for prosthetic hands is an important topic in the field of rehabilitation.
Intuitive and intelligent myoelectric control can help amputees to regain upper limb function …

Upper limb functional impairments persisting after stroke significantly affect patients' quality
of life. Precise adjustment of robotic assistance levels based on patients' motion intentions …

Human-machine interfaces frequently use electromyography (EMG) signals. Based on
previous work, feature extraction has a great deal of influence on the performance of EMG …

Simulating the behavior of operators through a digital human model (DHM) is an intuitive
way to reflect the human factors in the assembly process, which is important for ergonomics …

Simultaneous and proportional control (SPC) based on surface electromyographic (sEMG)
signals has led to a broad range of applications. However, due to the limitation in the …

Natural control of assistive devices requires continuous positional encoding and decoding of
the user's volition. Human movement is encoded by recruitment and rate coding of spinal …

In human-robot interaction systems oriented to rehabilitation training, surface
electromyogram (sEMG)-based human motion intention recognition has essential …

Automated source separation algorithms have become a central tool in neuroengineering
and neuroscience, where they are used to decompose neurophysiological signal into its …

Decoding surface electromyography (sEMG) to recognize human movement intentions
enables us to achieve stable, natural and consistent control in the field of human computer …

Surface electromyography (sEMG) offers a novel method in human–machine interactions
(HMIs) since it is a distinct physiological electrical signal that conceals human movement …