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Real-Time Evaluation of the Signal Processing of sEMG Used in Limb Exoskeleton Rehabilitation System

机译:肢体外骨骼康复系统中sEMG信号处理的实时评估

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摘要

As an important branch of medical robotics, a rehabilitation training robot for the hemiplegic upper limbs is a research hotspot of rehabilitation training. Based on the motion relearning program, rehabilitation technology, human anatomy, mechanics, computer science, robotics, and other fields of technology are covered. Based on an sEMG real-time training system for rehabilitation, the exoskeleton robot still has some problems that need to be solved in this field. Most of the existing rehabilitation exoskeleton robotic systems are heavy, and it is difficult to ensure the accuracy and real-time performance of sEMG signals. In this paper, we design a real-time training system for the upper limb exoskeleton robot based on the EMG signal. It has four main characteristics light weight, portability, high precision, and low delay. This work includes the structure of the rehabilitation robotic system and the method of signal processing of the sEMG. An experiment on the accuracy and time delay of the sEMG signal processing has been done. In the experimental results, the recognition accuracy of the sEMG is 94%, and the average delay time is 300 ms, which meets the accuracy and real-time requirements.
机译:作为医疗机器人学的重要分支,偏瘫上肢康复训练机器人是康复训练的研究热点。根据运动学习程序,涵盖了康复技术,人体解剖学,力学,计算机科学,机器人技术和其他技术领域。基于用于康复的sEMG实时培训系统,外骨骼机器人在该领域仍存在一些需要解决的问题。现有的大多数康复外骨骼机器人系统都很笨重,很难确保sEMG信号的准确性和实时性。本文基于肌电信号设计了上肢外骨骼机器人的实时训练系统。它具有四个主要特征:重量轻,便携性,高精度和低延迟。这项工作包括康复机器人系统的结构和sEMG的信号处理方法。进行了sEMG信号处理的准确性和时延的实验。在实验结果中,sEMG的识别精度为94%,平均延迟时间为300µms,满足了精度和实时性的要求。

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