Wearable sensors have the potential to enable comprehensive patient characterization and
optimized clinical intervention. Critical to realizing this vision is accurate estimation of …

Robotic-assisted rehabilitation therapy has been shown to be effective in improving upper
limb motor function and the daily behavior of patients with motor dysfunction. At present, the …

Objective: Current limitations in Electromyography (EMG)-driven Neuromusculoskeletal
(NMS) modeling for control of wearable robotics are the requirement of both Motion Capture …

The novel human-computer interface (HCI) using bioelectrical signals as input is a valuable
tool to improve the lives of people with disabilities. In this paper, surface electromyography …

As one of the most direct indicators of the transparency between a human and an
exoskeleton, interactive force has rarely been fused with electromyography (EMG) in the …

The objectives of this study are five‐fold:(i) design an extended Kalman filter (EKF) for the
single‐muscle and two‐muscle Hill models;(ii) design an EKF for unknown‐input estimation …

Accurate force control plays a crucial role but still faces many challenges in functional
electrical stimulation (FES) based neuroprosthesis applications. This study proposes an …

The purpose of this research was to continuous knee joint angle estimation from sEMG
during squat using artificial neural networks. sEMG signals of vastus medialis, rectus …

The interaction with robotic devices by means of physiological human signals has become
of great interest in the last years because of the capability of catching human intention of …

We propose a digital biomarker related to muscle strength and muscle endurance (DB/MS
and DB/ME) for the diagnosis of muscle disorders based on a multi-layer perceptron (MLP) …