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

One of the hottest topics in rehabilitation robotics is that of proper control of prosthetic
devices. Despite decades of research, the state of the art is dramatically behind the …

Traditional electromyogram (EMG) pattern recognition does not take into account the effect
of confounding factors, preventing its effective clinical application. In this paper, we …

This paper provides a comprehensive survey of current state of the bio-sensing technologies
focusing on hand motion capturing and its application to interfacing hand prostheses. These …

The temporal-difference methods TD (λ) and Sarsa (λ) form a core part of modern
reinforcement learning. Their appeal comes from their good performance, low computational …

Advanced human–machine interfaces render robotic devices applicable to study and
enhance human cognition. This turns robots into formidable neuroscientific tools to study …

Background: Myoelectric prostheses currently used by amputees can be difficult to control.
Machine learning, and in particular learned predictions about user intent, could help to …

The development of advanced and effective human–machine interfaces, especially for
amputees to control their prostheses, is very high priority and a very active area of research …

It is evident that user training significantly affects performance of pattern-recognition-based
myoelectric prosthetic device control. Despite plausible classification accuracy on offline …

The intelligent machine vision technology based on man-machine interaction mode has the
advantages of weak intrusion, low adhesion and no device binding. With the development …