1,720,999 research outputs found
How a discontinuous mechanism can produce continuous patterns in trajectory formation and Handwriting
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Multijoint arm stiffness during movements following stroke: Implications for robot therapy
No full textImpaired arm movements in stroke appear as a set of stereotypical kinematic patterns, characterized by abnormal joint coupling, which have a direct consequence on arm mechanics and can be quantified by the net arm stiffness at the hand. The current available measures of arm stiffness during functional tasks have limited clinical use, since they require several repetitions of the same test movement in many directions. Such procedure is difficult to obtain in stroke survivors who have lower fatigue threshold and increased variability compared to unimpaired individuals. The present study proposes a novel, fast quantitative measure of arm stiffness during movements by means of a Time-Frequency technique and the use of a reassigned spectrogram, applied on a trial-by-trial basis with a single perturbation. We tested the technique feasibility during robot mediated therapy, where a robot helped stroke survivors to regain arm mobility by providing assistive forces during a hitting task to 13 targets covering the entire reachable workspace. The endpoint stiffness of the paretic arm was estimated at the end of each hitting movements by suddenly switching of the assistive forces and observing the ensuing recoil movements. In addition, we considered how assistive forces influence stiffness. This method will provide therapists with improved tools to target the treatment to the individual's specific impairment and to verify the effects of the proposed exercises
Dynamic brain-machine interface: A novel paradigm for bidirectional interaction between brains and dynamical systems
No full textBrain-Machine Interfaces (BMIs) are systems which mediate communication between brains and artificial devices. Their long term goal is to restore motor functions, and this ultimately demands the development of a new generation of bidirectional brain-machine interfaces establishing a two-way brain-world communication channel, by both decoding motor commands from neural activity and providing feedback to the brain by electrical stimulation. Taking inspiration from how the spinal cord of vertebrates mediates communication between the brain and the limbs, here we present a model of a bidirectional brain-machine interface that interacts with a dynamical system by generating a control policy in the form of a force field. In our model, bidirectional communication takes place via two elements: (a) a motor interface decoding activities recorded from a motor cortical area, and (b) a sensory interface encoding the state of the controlled device into electrical stimuli delivered to a somatosensory area. We propose a specific mathematical model of the sensory and motor interfaces guiding a point mass moving in a viscous medium, and we demonstrate its performance by testing it on realistically simulated neural responses
Connecting Brains to Robots: An Artificial Body for Studying the Computational Properties of Neural Tissues
No full textWe have created a hybrid neuro-robotic system that establishes two-way communication between the brain of a lamprey and a small mobile robot. The purpose of this system is to offer a new paradigm for investigating the behavioral, computational, and neurobiological mechanisms of sensory-motor learning in a unified context. The mobile robot acts as an artificial body that delivers sensory information to the neural tissue and receives command signals from it. The sensory information encodes the intensity of light generated by a fixed source. The closed-loop interaction between brain and robot generates autonomous behaviors whose features are strictly related to the structure and operation of the neural preparation. We provide a detailed description of the hybrid system, and we present experimental findings on its performance. In particular, we found (a) that the hybrid system generates stable behaviors, (b) that different preparations display different but systematic responses to the presentation of an optical stimulus, and (c) that alteration of the sensory input leads to short- and long-term adaptive changes in the robot responses. The comparison of the behaviors generated by the lamprey's brain stem with the behaviors generated by network models of the same neural system provides us with a new tool for investigating the computational properties of synaptic plasticity
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