Name
Title | ||
|---|---|---|
A Motor Rehabilitation Bmi System Design Through Improving The Sjit Model And Introducing An Mpc-Based Auxiliary Controller |
Abstract | ||
|---|---|---|
In the brain-machine interface (BMI) system, improving the motor recovery function of the joint and enabling the joint to adequately track the target trajectory are our main concerns. In this paper, to further improve the motor recovery effectiveness, two tasks are completed. First, a classical single-joint information transmission (SJIT) model is analyzed and improved by introducing several neurons. Second, an auxiliary controller that provides control inputs to the cerebral cortex is designed based on the model predictive control (MPC) strategy and is used to formulate a closed-loop motor rehabilitation BMI system based on the improved model. The simulation results show that the improved model can more accurately track the target movement trajectory than the SJIT model, and the designed BMI system can adequately recover the motor function of the joint. The sum of squared error (SSE) between the desired joint position trajectory and the output joint position trajectory is only 1.2842x10(-5). In addition, under noises and disturbances, the BMI system can well recover the motor function of the joint. The model improvement and the designed BMI system are both effective. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1007/s12559-021-09878-x | COGNITIVE COMPUTATION |
Keywords | DocType | Volume |
Brain-machine interface, Model improvement, Model predictive control, Auxiliary controller, Closed-loop system | Journal | 13 |
Issue | ISSN | Citations |
4 | 1866-9956 | 1 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongguang Pan | 1 | 3 | 1.40 |
| Wenyu Mi | 2 | 3 | 1.03 |
| Weimin Zhong | 3 | 79 | 14.18 |
| Jinggao Sun | 4 | 1 | 0.34 |