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一种具有肌肉对肌肉接口的新型机器人康复系统的开发。

Development of a Novel Robotic Rehabilitation System With Muscle-to-Muscle Interface.

作者信息

Bong Jae Hwan, Jung Suhun, Park Namji, Kim Seung-Jong, Park Shinsuk

机构信息

Department of Mechanical Engineering, Korea University, Seoul, South Korea.

School of Dentistry, Seoul National University, Seoul, South Korea.

出版信息

Front Neurorobot. 2020 Feb 18;14:3. doi: 10.3389/fnbot.2020.00003. eCollection 2020.

DOI:10.3389/fnbot.2020.00003
PMID:32132916
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7040493/
Abstract

In this study, we developed a novel robotic system with a muscle-to-muscle interface to enhance rehabilitation of post-stroke patients. The developed robotic rehabilitation system was designed to provide patients with stage appropriate physical rehabilitation exercise and muscular stimulation. Unlike the position-based control of conventional bimanual robotic therapies, the developed system stimulates the activities of the target muscles, as well as the joint movements of the paretic limb. The robot-assisted motion and the electrical stimulation on the muscles of the paretic side are controlled by on-line comparison of the motion and the muscle activities between the paretic and unaffected sides. With the developed system, the rehabilitation exercise can be customized and modulated depending on the patient's stage of motor recovery after stroke. The system can be operated in three different modes allowing both passive and active exercises. The effectiveness of the developed system was verified with healthy human subjects, where the subjects were paired to serve as the unaffected side and the paretic side of a hemiplegic patient.

摘要

在本研究中,我们开发了一种具有肌肉对肌肉接口的新型机器人系统,以增强中风后患者的康复效果。所开发的机器人康复系统旨在为患者提供适合阶段的身体康复锻炼和肌肉刺激。与传统双手机器人疗法基于位置的控制不同,所开发的系统刺激目标肌肉的活动以及患侧肢体的关节运动。机器人辅助运动和患侧肌肉的电刺激通过比较患侧和未受影响侧之间的运动和肌肉活动进行在线控制。使用所开发的系统,康复锻炼可以根据中风后患者的运动恢复阶段进行定制和调整。该系统可以在三种不同模式下运行,允许进行被动和主动锻炼。所开发系统的有效性在健康人体受试者中得到验证,其中将受试者配对作为偏瘫患者的未受影响侧和患侧。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/2dcd724a9565/fnbot-14-00003-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/e90c79aa06cb/fnbot-14-00003-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/70d7487206d7/fnbot-14-00003-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/e596802bcb29/fnbot-14-00003-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/8e1bf012990a/fnbot-14-00003-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/2d6db6a7c0e0/fnbot-14-00003-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/0b2b8c98757b/fnbot-14-00003-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/950b0af0ecc7/fnbot-14-00003-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/2dcd724a9565/fnbot-14-00003-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/e90c79aa06cb/fnbot-14-00003-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/7f70aeed3f67/fnbot-14-00003-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/6b7519deb69d/fnbot-14-00003-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/70d7487206d7/fnbot-14-00003-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/e596802bcb29/fnbot-14-00003-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/8e1bf012990a/fnbot-14-00003-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/2d6db6a7c0e0/fnbot-14-00003-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/0b2b8c98757b/fnbot-14-00003-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/950b0af0ecc7/fnbot-14-00003-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2667/7040493/2dcd724a9565/fnbot-14-00003-g010.jpg

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本文引用的文献

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Effects of Robot-Assisted Therapy for the Upper Limb After Stroke.机器人辅助治疗对中风后上肢的影响。
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A novel feature extraction for robust EMG pattern recognition.一种用于稳健肌电图模式识别的新型特征提取方法。
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