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We present a method for recognizing intended grasp type based on data from the Microsoft Kinect. A computer vision algorithm estimates the vertical and the transversal distance of the hand from the center of the object and the hand orientation from the Kinect depth images. Based on this set of features in the reaching phase of grasp artificial neural network recognizes the intended grasp type. This...
Recent developments in neural interface systems hold the promise to restore movement in people with paralysis. In search of neural signals for control of neural interface systems, previous studies have investigated primarily single and multiunit activity, as well as low frequency local field potentials (LFPs). In this paper, we investigate the information content about grasping motion of a broad band...
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