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 …

Dexterous control of robotic hand driven by human motor intent has drawn a lot of attention
in both industrial and rehabilitation scenarios. Providing simultaneous and proportional …

Exoskeleton robot is an essential tool in active rehabilitation training for patients with lower
limb motor dysfunctions. Accurate and real-time recognition in human motion intention is a …

In myoelectric control, simultaneous and proportional (SP) control of multiple degrees of
freedom (DOFs) can realize a high level of dexterity. This study proposed a new control …

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

This study introduces a novel approach for real-time hand gesture classification through the
integration of a Frequency-based Attention Neural Network (FANN) with Subject-Adaptive …

This study comprehensively assesses various recurrent neural networks (RNNs) for
decoding the elbow angle from electromyogram (EMG) signals, a crucial aspect in …

The estimation of lower-limb joint moments during locomotive activities can provide valuable
feedback in joint-injury risk evaluation and clinical diagnosis. The use of inertial …

Multi-stream signals are increasingly being used in robot-assisted rehabilitation training,
where the timely and accurate prediction of a patient's motor intentions is frequently required …

In this paper, a novel long short memory network–adaptive robust iterative learning control
(LSTM-ARILC) framework is proposed to achieve accurate continuous motion estimation …