23 research outputs found
Advanced technology for gait rehabilitation --- An overview
Most gait training systems are designed for acute and subacute neurological inpatients. Many systems are used for
relearning gait movements (nonfunctional training) or gait cycle training (functional gait training). Each system presents
its own advantages and disadvantages in terms of functional outcomes. However, training gait cycle movements is not
sufficient for the rehabilitation of ambulation. There is a need for new solutions to overcome the limitations of existing
systems in order to ensure individually tailored training conditions for each of the potential users, no matter the complexity
of his or her condition. There is also a need for a new, integrative approach in gait rehabilitation, one that encompasses
and addresses all aspects of physical as well as psychological aspects of ambulation in real-life multitasking
situations. In this respect, a multidisciplinary multinational team performed an overview of the current technology for
gait rehabilitation and reviewed the principles of ambulation training
Role of Muscle Synergies in Real-Time Classification of Upper Limb Motions using Extreme Learning Machines
EMG-based teleoperation of a robot arm in planar catching movements using ARMAX model and trajectory monitoring techniques
Teleoperation of a robot arm in 2D catching movements using EMG signals and a bio-inspired motion law
Navigation functions learning from experiments: Application to anthropomorphic grasping
Abstract—This paper proposes a method to construct Nav-igation Functions (NF) from experimental trajectories in an unknown environment. We want to approximate an unknown obstacle function and then use it within an NF. When nav-igating the same destinations with the experiments, this NF should produce the same trajectories as the experiments. This requirement is equivalent to a partial differential equation (PDE). Solving the PDE yields the unknown obstacle function, expressed with spline basis functions. We apply this new method to anthropomorphic grasping, producing automatic trajectories similar to the observed ones. The grasping experiments were performed for a set of different objects, Principal Component Analysis (PCA) allows reduction of the configuration space dimension, where the learning NF method is then applied. I