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A Geometric Approach for the Comparison of Kinematic Synergy Postures

Federico Tessari, A. Michael West, Neville Hogan

Year
2025
Citations
1

Abstract

The analysis of human movements has highlighted the presence of stereotyped coordination patterns among the different joints of the human body. These patterns are commonly referred to as kinematic synergies. Synergies have been used to both elucidate the underlying neuromotor control strategies adopted by humans during coordinated motion and inform the design and control of assistive and rehabilitative devices such as prostheses and exoskeletons. A particularly thorny problem in the analysis of synergies is the comparison of the synergy postures i.e., the hyper-dimensional vectors containing the contribution of each analyzed feature (e.g., joint angles) to the considered synergies. Often, synergy postures are compared using cosine similarity, which is sensitive to the dimensionality of the input data and does not offer an intuitive understanding of the synergies' similarities and differences. In this study, we introduce a new geometric method, Geometric Configuration Similarity (GCS), specifically designed to compare kinematic synergy postures, with a particular emphasis on hand kinematic synergies. GCS provides a more intuitive geometric understanding of how these postures relate to one another. We demonstrate its advantages over cosine similarity through experimental and numerical results, offering the human motor control and rehabilitation robotics communities a new tool for analyzing kinematic hand synergies and improving the design and control of assistive systems.

Keywords

KinematicsComputer scienceArtificial intelligenceComputer visionPhysicsClassical mechanics

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