Training method and system for rope traction upper limb rehabilitation robot based on admittance control

A rehabilitation robot and training method technology, applied in the field of medical rehabilitation, can solve the problems of insufficient active participation of patients and complex algorithms, etc., and achieve the effect of enhancing active participation and improving the effect

Active Publication Date: 2018-12-28
SUN YAT SEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Myoelectric control judges the user's movement intention based on the user's myoelectric signal, and the patient's active participation is strong; Professor Ai Qingsong of Wuhan University of Technology conducts pattern recognition on the myoelectric signal, combined with the variable impedance control strategy, and applies it to the 6-degree-of-freedom rehabilitation of the lower limbs Robots;...

Method used

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  • Training method and system for rope traction upper limb rehabilitation robot based on admittance control
  • Training method and system for rope traction upper limb rehabilitation robot based on admittance control
  • Training method and system for rope traction upper limb rehabilitation robot based on admittance control

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Embodiment 1

[0038] see figure 1 , the embodiment of the present invention provides a kind of training method based on the rope traction upper limb rehabilitation robot of admittance control, comprises the following steps:

[0039] S1. When the user performs upper limb joint rehabilitation training exercise, real-time collection of the interactive force signal and the kinematic signal of the upper limb exerted by the user's upper limb on the rope traction rehabilitation robot;

[0040] When the user performs rehabilitation training exercises, the admittance control does not preset the trajectory, and the target trajectory is determined only by the collected interactive force signal exerted by the user's upper limbs on the rope-tracted rehabilitation robot.

[0041] Such as figure 2 As shown, the step S1 specifically includes the steps:

[0042] S11. Reset the end effector of the rope traction rehabilitation robot to the designated starting position, guide the user to place the upper lim...

Embodiment 2

[0055] An embodiment of the present invention provides a training method for a rope-tracted upper limb rehabilitation robot based on admittance control, the steps of which are as follows: Figure 4 Shown:

[0056] S0, when the user performs the maximum tension test, collect the maximum tension signal, and preset the threshold according to the collected maximum tension signal;

[0057] In this step, the maximum pulling force signal is taken as a preset threshold as a percentage. The percentage is formulated according to the motor function of different users.

[0058] S1. When the user performs upper limb joint rehabilitation training exercise, real-time collection of the interactive force signal and the kinematic signal of the upper limb exerted by the user's upper limb on the rope traction rehabilitation robot;

[0059] This step is the same as step S1 in the first embodiment, and also includes steps S11, S12, and S13.

[0060] S1 / 1. Judging whether the interaction force...

Embodiment 3

[0094] The present invention also provides a training system for a rope-tracted upper limb rehabilitation robot based on admittance control, which can implement the training method in the above-mentioned embodiments.

[0095] see Figure 5 , is a schematic structural diagram of a training system for a rope-tracted upper limb rehabilitation robot based on admittance control provided by the present invention. The training system of the rope traction upper limb rehabilitation robot based on admittance control includes a signal acquisition module A, a signal transmission module B, a host control module C and a host interaction module D.

[0096] Each module of the training system of the rope traction upper limb rehabilitation robot based on the admittance control of the present embodiment is described in detail as follows:

[0097] The signal acquisition module A is used to collect the interactive force signal and the kinematic signal of the upper limb applied to the rope tractio...

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Abstract

The invention discloses a training method and system for a rope traction upper limb rehabilitation robot based on admittance control. When a user performs an upper limb joint rehabilitation training exercise, an interaction force signal of the upper limbs of the user applied to the rope traction rehabilitation robot and a kinematic signal of the upper limbs are collected in real time; the interaction force signal is converted into a motion parameter of a desired motion trajectory through an admittance model, and a motion parameter of a target motion trajectory is determined according to the motion parameter of the desired motion trajectory and the kinematic signal of the upper limbs; the determined motion parameter serves as a controlled variable to be converted into a motor control variable of the rope traction rehabilitation robot, and corresponding motor output is controlled to achieve a self-control rehabilitation training movement of the user, thereby increasing the active participation of the user.

Description

technical field [0001] The present invention relates to the technical field of medical rehabilitation, in particular to a training method and system for a rope traction upper limb rehabilitation robot based on admittance control. Background technique [0002] Stroke is characterized by high morbidity, disability and mortality, and is the primary disease that threatens human health. According to statistics, there are 2 million stroke patients in my country every year, and the incidence rate is as high as 1.20 / 100,000. With the aging of my country's population, the incidence rate of stroke is showing an upward trend year by year. 75% of stroke survivors have varying degrees of motor dysfunction, have lost their labor force or are unable to take care of themselves to varying degrees, and 25% of them still cannot use the affected limb freely five years after the stroke; especially the function of the upper limbs Recovery is often slower than that of the lower extremities due to...

Claims

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Application Information

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IPC IPC(8): A63B23/12A63B24/00G06F3/01
CPCA63B21/00178A63B21/00181A63B23/12A63B24/0087A63B2024/0093A63B2220/51G06F3/011
Inventor 宋嵘杨倩倩牛杰
Owner SUN YAT SEN UNIV
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