Intelligent poststroke rehabilitation has attracted great attention worldwide, since the high
incidence rate of stroke with the aging of the population. It is well known that effective …

Human motion intention recognition is a key to achieve perfect human‐machine
coordination and wearing comfort of wearable robots. Surface electromyography (sEMG), as …

A current challenge with robot-assisted rehabilitation is to combine the active involvement
and voluntary participation of patients into the rehabilitation training process to enhance …

Robot-assisted rehabilitation is a growing field that can provide an intensity, quality, and
quantity of treatment that exceed therapist-mediated rehabilitation. Several control …

Interest in developing techniques for acquiring and decoding biological signals is on the rise
in the research community. This interest spans various applications, with a particular focus …

A machine learning model for regression of interrupted Surface Electromyography (sEMG)
signals to future control-oriented signals (eg, robot's joint angle and assistive torque) of an …

Estimation of the force exerted by muscles from their electromyographic (EMG) activity may
be useful to control robotic devices. Approximating end-point forces as a linear combination …

Human-machine interaction is a key component in the wearable robotics field. Because
surface electromyography (sEMG) generates prior to the corresponding motion and reflects …

Wearable exoskeleton robots can promote the rehabilitation of patients with physical
dysfunction. And improving human-computer interaction performance is a significant …

Surface electromyographic (sEMG) signals is one most commonly used control source of
exoskeleton for hand rehabilitation. Due to the characteristics of non-invasive, convenient …