Multi-modal fusion combines multiple modal information to overcome the limitation of
incomplete information expressed by a single modality, so as to realize the complementarity …

Electroencephalography (EEG) and electromyography (EMG) are widespread and well-
known quantitative techniques used for gathering biological signals at cortical and muscular …

Surface electromyography (sEMG) and electroencephalogram (EEG) can be utilized to
discriminate gait phases. However, the classification performance of various combination …

More than 85% of stroke survivors suffer from different degrees of disability for the rest of
their lives. They will require support that can vary from occasional to full time assistance …

This paper reviews model-based and model-free approaches for continuous prediction of
human joint motion using surface electromyography (EMG) signals. The review focuses on …

Effective control of an exoskeleton robot (ER) using a human-robot interface is crucial for
assessing the robot's movements and the force they produce to generate efficient control …

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

Surface electromyogram (sEMG) is widely used in active rehabilitation control for stroke
patients. However, the accuracy of movement recognition using sEMG signals is affected by …

Wearable robotic exoskeletons have emerged as an exciting new treatment tool for
disorders affecting mobility; however, the human–machine interface, used by the patient for …

Musculoskeletal disorders are the biggest cause of disability worldwide and wearable
mechatronic rehabilitation devices have been proposed as a potential tool for providing …