Electromyography (EMG) signal is one of the widely used biological signals for human motor
intention prediction, which is an essential element in human-robot collaboration systems …

To get a compliant active exoskeleton controller, the force interaction controllers are mostly
used in form of either the impedance or admittance controllers. The impedance or …

To find out the feasibility of different neural networks in sEMG-based force estimation, in this
paper, three types of networks, namely convolutional neural network (CNN), long short-term …

Decoding movement intentions from motor unit (MU) activities to represent neural drive
information plays a central role in establishing neural interfaces, but there remains a great …

Numerous techniques have been used to minimize error in relating the surface
electromyogram (EMG) to elbow joint torque. We compare the use of three techniques to …

In the past decade, advanced technologies in robotics have been explored to enhance the
rehabilitation of post-stroke patients. Previous works have shown that gait assistance for …

Surface electromyography (sEMG) signal is one of the widely applied biological signals in
the research field of the force intention prediction. However, due to the severe cross-talk …

Electromyogram (EMG) signal has been long used in human-robot interface in literature,
especially in the area of rehabilitation. Recent rapid development in artificial intelligence (AI) …

Tele-assessment systems are crucial for home-based rehabilitation, as they allow therapists
to assess the status of patients and adjust the parameters of various home-based training …

To accurately estimate muscle forces using electromyogram (EMG) signals, precise EMG
amplitude estimation, and a modeling scheme capable of coping with the nonlinearities and …