公开(公告)号：US20240206728A1

公开(公告)日：2024-06-27

申请号：US18022758

申请日：2022-06-28

Applicant: SOUTHEAST UNIVERSITY

Inventor： Hong ZENG ,  Xiao LI ,  Qingqing CHEN ,  Jianxi ZHANG ,  Aiguo SONG

IPC: A61B3/113 ,  A63B22/00 ,  G16H20/30

CPC classification number: A61B3/113 ,  A63B22/00 ,  G16H20/30 ,  A63B2022/0092

Abstract: A robot-assisted hand-eye coordination training system based on a smooth pursuit eye movement and a guidance force field includes a virtual interactive scene module, a smooth pursuit eye movement detection module, a robot-assisted interception module and an impact force rendering module. The virtual interactive scene module can generate a virtual interactive scene having a virtual moving object and a virtual handle agent. The smooth pursuit eye movement detection module collects an eye movement signal of a user when the user performs pursuit eye movements on the virtual moving object to detect a smooth pursuit eye movement event. The robot-assisted interception module estimates a movement direction of the virtual moving object, generates an interception and guidance force field, and therefore generates assisting force to assist the user in interception. The impact force rendering module generates impact force according to an impact force computation model after collision is detected.

公开(公告)号：US20240096483A1

公开(公告)日：2024-03-21

申请号：US18031152

申请日：2022-07-25

Applicant: SOUTHEAST UNIVERSITY

Inventor： Hong ZENG ,  Qingqing CHEN ,  Xiao LI ,  Yinxin DUAN ,  Jianxi ZHANG ,  Aiguo SONG

IPC: G16H40/63 ,  A61H1/02 ,  G05B13/02

CPC classification number: G16H40/63 ,  A61H1/0274 ,  G05B13/027 ,  A61H2201/1659 ,  A61H2201/5007 ,  A61H2230/605

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.

公开(公告)号：US20230256296A1

公开(公告)日：2023-08-17

申请号：US18138154

申请日：2023-04-24

Applicant: SOUTHEAST UNIVERSITY

Inventor： Hong ZENG ,  Yinxin DUAN ,  Xiao LI ,  Qingqing CHEN ,  Aiguo SONG

IPC: A63B23/14 ,  A61B5/397 ,  A63F13/212

CPC classification number: A63B23/14 ,  A61B5/397 ,  A63F13/212 ,  A61B2505/09

Abstract: A wrist rehabilitation training system based on muscle coordination and variable stiffness impedance control includes the following modules: an electromyographic signal collection and preprocessing module, a muscle co-decomposition and mapping model obtaining module, a man-machine interactive control module, and a virtual reality serious game module; collects a surface electromyographic signal of a forearm of a user, obtains time-domain coordination through non-negative matrix factorization, establishes a position and stiffness estimation model, and controls motion of a target in a serious game through variable stiffness impedance control, so as to complete a training task.