Lower-limb robotic exoskeletons have become powerful tools to assist or rehabilitate the gait
of subjects with impaired walking, even when they are designed to act only partially over the …

Human motion intention (HMI) has increasingly gained concerns in lower limb exoskeletons
(LLEs). HMI recognition (HMIR) is the precondition for realizing active compliance control in …

This research presents an Assist-as-Needed (AAN) Algorithm for controlling a bio-inspired
exoskeleton, specifically designed to aid in elbow-rehabilitation exercises. The algorithm is …

Objective. Neuroprostheses typically operate under supervised learning, in which a machine-
learning algorithm is trained to correlate neural or myoelectric activity with an individual's …

Advances in powered assistive device technology, including the ability to provide net
mechanical power to multiple joints within a single device, have the potential to dramatically …

Objective: A unilateral, lightweight powered hip exoskeleton has been shown to improve
walking economy in individuals with above-knee amputations. However, the mechanism …

Wrist function is a top priority for transradial amputees. However, the combined functional,
biomechanical, and cognitive impact of using a powered prosthetic wrist is unclear. Here, we …

This review aims to provide a systematic analysis of the literature focused on the use of
intelligent control systems in robotics for physical rehabilitation, identifying trends in recent …

Intuitive regression control of prostheses relies on training algorithms to correlate biological
recordings to motor intent. The quality of the training dataset is critical to run-time regression …

Electromyographic controls based on machine learning rely on the stability and repeatability
of signals related to muscular activity. However, such algorithms are prone to several issues …