A Geometrodynamic Haptic Orthosis for State-Space Navigation and Motor Learning
Abstract An invention is disclosed which provides a system and method for enhancing human motor learning and performance. The system comprises a sensor module for capturing high-dimensional state data from a user, a processing unit for mapping this data onto a dynamic, non-Euclidean geometric manifold, and a haptic actuator module for providing proactive, geodesic-based guidance. The invention's novelty lies in its fundamental departure from conventional reactive feedback systems. Instead, it employs a first-principles geometrodynamic model of reality to actively guide a user along a mathematically optimal trajectory within a unified, 11-dimensional state-space. This transforms the device from a simple feedback mechanism into a "learnohaptic orthosis," a system that actively participates in and shapes the learning process by making the most efficient path of action the path of least physical resistance. The system is preferably embodied as a hardware accessory for a mobile computing device, leveraging its processing capabilities to execute the complex computational model.
Institutions
- Istanbul Medipol University (TR)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-10-11
- DOI
- https://doi.org/10.5281/zenodo.17317780
- Primary Topic
- Advanced Battery Materials and Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00