In ergonomics, strength prediction has typically been accomplished using linked-segment biomechanical models, and independent estimates of strength about each axis of the wrist, elbow and shoulder joints. It has recently been shown that multiple regr...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Dec 31, 2015
Robotic gait training is gaining ground in rehabilitation. Room for improvement lies in reducing donning and doffing time, making training more task specific and facilitating active balance control, and by allowing movement in more degrees of freedom...
The shoulder complex in the human body consists of the scapula, clavicle, humerus, and thorax and bears the load imposed by arm movements while at the same time realizing a wide range of motions. To mimic and exploit its role, several musculoskeletal...
Neural networks : the official journal of the International Neural Network Society
Nov 4, 2015
We present an extension of a neurobiologically inspired robotics model, termed CoRLEGO (Choice reaching with a LEGO arm robot). CoRLEGO models experimental evidence from choice reaching tasks (CRT). In a CRT participants are asked to rapidly reach an...
This article presents a Lyapunov function based neural network tracking (LNT) strategy for single-input, single-output (SISO) discrete-time nonlinear dynamic systems. The proposed LNT architecture is composed of two feedforward neural networks operat...
Journal of neuroengineering and rehabilitation
Oct 9, 2015
BACKGROUND: Assistive and robotic training devices are increasingly used for rehabilitation of the hemiparetic arm after stroke, although applications for the wrist and hand are trailing behind. Furthermore, applying a training device in domestic set...
In the field of human motor control, the motor synergy hypothesis explains how humans simplify body control dimensionality by coordinating groups of muscles, called motor synergies, instead of controlling muscles independently. In most applications o...
Digital implementations of control laws typically involve discretization with respect to both time and space, and a control law that can achieve a task at coarser levels of discretization can be said to require less control attention, and also reduce...
Prosthetics and orthotics international
Sep 30, 2015
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 reduce the time and cognitive load required by amputees while operatin...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 30, 2015
In this study, we test the feasibility of the synergy- based approach for application in the realistic and clinically oriented framework of multi-degree of freedom (DOF) robotic control. We developed and tested online ten able-bodied subjects in a se...