Early research on physical human–robot interaction (pHRI) has necessarily focused on
device design—the creation of compliant and sensorized hardware, such as exoskeletons …

Significant advances in bionic prosthetics have occurred in the past two decades. The field's
rapid expansion has yielded many exciting technologies that can enhance the physical …

The loss of a hand disrupts the sophisticated neural pathways between the brain and the
hand, severely affecting the level of independence of the patient and the ability to carry out …

Introduction Myoelectric control systems translate different patterns of electromyographic
(EMG) signals into the control commands of diverse human-machine interfaces via hand …

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 …

Background Eye tracking technology not only reveals the acquisition of visual information at
fixation but also has the potential to unveil underlying cognitive processes involved in …

Pattern recognition (PR)-based myoelectric control systems can naturally provide
multifunctional and intuitive control of upper limb prostheses and restore lost limb function …

Objective. The objective of this study was to assess the impact of delayed feedback training
on the retention of novel myoelectric skills, and to demonstrate the use of this training …

Background This research aims to improve the control of assistive devices for individuals
with hemiparesis after stroke by providing intuitive and proportional motor control. Stroke is …

Background Lack of standardized assessments that explicitly quantify performance during
prosthetic grip selection poses difficulty determining whether efforts to improve the design of …