1 citations · 1 across the 4 of their papers we have counts for
5 papers
Deep-learning-based identification of individual motion characteristics from upper-limb trajectories towards disorder stage evaluation
Tim Sziburis, Susanne Blex, Tobias Glasmachers +1
The identification of individual movement characteristics sets the foundation for the assessment of personal rehabilitation progress and can provide diagnostic information on level…
Ruhr Hand Motion Catalog of Human Center-Out Transport Trajectories in 3D Task-Space Captured by a Redundant Measurement System
Tim Sziburis, Susanne Blex, Tobias Glasmachers +1
Neurological conditions are a major source of movement disorders. Motion modelling and variability analysis have the potential to identify pathology but require profound data. We i…
Instance-based Learning with Prototype Reduction for Real-Time Proportional Myocontrol: A Randomized User Study Demonstrating Accuracy-preserving Data Reduction for Prosthetic Embedded Systems
Tim Sziburis, Markus Nowak, Davide Brunelli
This work presents the design, implementation and validation of learning techniques based on the kNN scheme for gesture detection in prosthetic control. To cope with high computati…
KNN Learning Techniques for Proportional Myocontrol in Prosthetics
Tim Sziburis, Markus Nowak, Davide Brunelli
This work has been conducted in the context of pattern-recognition-based control for electromyographic prostheses. It presents a k-nearest neighbour (kNN) classification technique…
Biologically Inspired Model for Timed Motion in Robotic Systems
Sebastian Doliwa, Muhammad Ayaz Hussain, Tim Sziburis +1
The goal of this work is the development of a motion model for sequentially timed movement actions in robotic systems under specific consideration of temporal stabilization, that i…