Adaptive control method and system for upper limb rehabilitation robot based on game theory and surface electromyography (sEMG)
US12057224B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 25, 2022 |
| Grant date | Aug 6, 2024 |
| Priority date | — |
| Expiry date | Jul 25, 2042 |
Classification
- Technology area (CPC A)Human Necessities
- CPC primaryA61H2230/605
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
An adaptive control method and system for an upper limb rehabilitation robot based on a game theory and surface Electromyography (sEMG) is disclosed. A movement trajectory that a robot is controlled to run within a training time is designed during subject operation. An sEMG-based Back Propagation Neural Network (BPNN) muscle force estimation model establishes a nonlinear dynamic relationship between an sEMG signal and end force by constructing a three-layer neural network. A human-computer interaction system is analyzed by the game theory principle, and a role of the robot is deduced. The control rate between the robot and a subject is updated by Nash equilibrium, and adaptive weight factors of the robot and the subject are determined. The robot adaptively adjusts the training mode thereof according to a movement intention of the subject during operation and a weight coefficient obtained by the game theory principle.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.