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Horizontal type lower limb rehabilitation intelligent interactive robot group system based on ad-hoc network navigation for ICU (Intensive Care Unit) sickroom

A rehabilitation robot and robot group technology, which can be applied to devices that cause sleep or relaxation, passive exercise equipment, physical therapy, etc., can solve the problems of inability to accurately control training time and intensity, labor burden, and single rehabilitation training mode. Achieve the effect of improving credibility and credibility, reducing labor burden, and improving treatment efficiency

Pending Publication Date: 2019-05-28
ZHENGZHOU UNIV
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  • Summary
  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] Rehabilitation medicine studies have shown that patients with cerebral palsy or lower limb injuries who have not performed lower limb training for a long time will lead to muscle "disuse" atrophy and cannot be cured. Carrying out physical rehabilitation training is helpful to restore the normal functions of the limbs; however, due to the movement disorder of the lower limbs of patients with cerebral palsy or lower limb injuries, they cannot complete the physical rehabilitation training independently, and generally require medical staff with certain nursing knowledge to help patients complete exercise training repeatedly. This brings a huge labor burden to the medical staff in the ICU ward. The training time and intensity cannot be accurately controlled, which makes it difficult to achieve the best therapeutic effect in ICU training. The more important limitation is that patients are divided into two types: total paralysis and hemiplegia. Different types of patients have different emphases in the treatment process. It is not possible to flexibly exchange training programs for unilateral or bilateral patients, and it is not possible to perform rehabilitation training for both lower limbs of patients with total paralysis at the same time, and it is not possible to target multiple joints of the lower limbs of patients. Coordinated rehabilitation training; secondly, the patient’s rehabilitation status cannot be monitored in real time, resulting in untimely feedback of repeated training and treatment effects, which is not conducive to the effective adjustment of rehabilitation training plans by medical staff according to the recovery effect of ICU patients
[0003] The following problems generally exist in the control system of existing lower limb rehabilitation devices: 1) The rehabilitation training mode is single, and the rehabilitation needs of patients in each rehabilitation stage cannot be effectively met; the type of rehabilitation parts is single, and the robot can only perform rehabilitation training on some joints of the patient at a time , the patient’s recovery efficiency is low; 2) The robot interaction method is single and cumbersome. Doctors must manually control the robot multiple times to complete the rehabilitation treatment. Some patients with cerebral palsy cannot move their limbs and cannot interact with the robot. The robot can only be used for rehabilitation on the limbs. It cannot be used for the psychological rehabilitation of patients; 3) The robots cannot cooperate with each other, and cannot cooperate to complete the treatment tasks that require cooperation between different robots, such as one side or both sides of the patient, and the efficiency of the ICU ward is too low; Rehabilitation robots or rehabilitation systems test different rehabilitation methods for ICU patients. Data communication cannot be performed between different types of rehabilitation robots or rehabilitation systems. Only human judgment can be used to determine the rehabilitation training methods suitable for ICU patients. To a certain extent, the labor burden of the hospital's medical staff is increased; 4) The robot's movement method is relatively primitive, and a single robot cannot autonomously avoid obstacles and move to the designated location according to the navigation route set by the doctor; multiple robots cannot sense each other, locate, Navigate routes, methodically work collaboratively between wards

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  • Horizontal type lower limb rehabilitation intelligent interactive robot group system based on ad-hoc network navigation for ICU (Intensive Care Unit) sickroom
  • Horizontal type lower limb rehabilitation intelligent interactive robot group system based on ad-hoc network navigation for ICU (Intensive Care Unit) sickroom
  • Horizontal type lower limb rehabilitation intelligent interactive robot group system based on ad-hoc network navigation for ICU (Intensive Care Unit) sickroom

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Embodiment

[0036] Before rehabilitation training, medical staff use APP to set the navigation route of each robot in the rehabilitation robot group. Each rehabilitation robot uses navigation algorithms to achieve close-range and precise navigation. During the movement, the lower limb rehabilitation robot uses lidar for obstacle avoidance detection; After the rehabilitation robot arrives at the designated location, the medical staff disinfects it outside the ICU ward and connects it rigidly to the bed. Then the doctor fixes the patient’s lower limbs with the rehabilitation robot’s lower limb exoskeleton and adjusts its structure to meet the patient’s needs Comfortable requirements; when the power is turned on, the rehabilitation robot group conducts various data inspections on the ICU patients during the rehabilitation training process, and conducts data synthesis and processing through the robot communication module. The rehabilitation evaluation system provides the most suitable ICU patien...

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Abstract

The invention discloses a horizontal type lower limb rehabilitation intelligent interactive robot group system based on ad-hoc network navigation for an ICU (Intensive Care Unit) sickroom. The systemcomprises a human body physical sign data acquisition module, a base module, a lower limb outer skeleton, a control and rehabilitation evaluation module, a positioning navigation and mapping module, agroup communication module, an intelligent interaction module and a cloud platform; based on a modularized design, movement evaluation and rehabilitation training of each joint of unilateral and bilateral sides of a lower limb of a human body can be realized aiming at patients with different features; a robot group is controlled by adopting tissue properties of MAS and unilateral and bilateral lower limb rehabilitation of different patients can be realized through close cooperation; based on a wireless ad-hoc network communication technology, each robot is used for collecting measured positions and obstacle data to a base station through an ad-hoc network, and a map is constructed, so that automatic navigation of the robot group is realized, and the capability of automatic movement of robots in groups is greatly improved; based on a zone chain technology, the data transmission and storage safety is improved.

Description

Technical field [0001] The invention belongs to the field of medical rehabilitation equipment, and specifically relates to an ICU ward horizontal lower limb rehabilitation intelligent interactive robot group system based on self-organizing network navigation, which meets the unilateral and bilateral lower limb rehabilitation evaluation and rehabilitation training requirements of different patients in the intensive care ward. Background technique [0002] Rehabilitation medicine studies have shown that patients with cerebral palsy or lower extremity injuries who have not undergone lower extremity training for a long time will cause "disuse" muscle atrophy and cannot be cured. Therefore, after the postoperative intensive care unit (ICU) patients have stable physical signs, they should be as soon as possible Rehabilitation training of the limbs will help them restore normal function of the limbs; however, due to the lower limb movement disorder of patients with cerebral palsy or lowe...

Claims

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Application Information

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IPC IPC(8): A61H1/02G16H20/30A61M21/02
Inventor 任海川麻晓东段航琪李嘉刘青林张朔闫家玉张静孙翔宇李志洋
Owner ZHENGZHOU UNIV
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