首页> 外文会议>ASME International Mechanical Engineering Congress and Exposition >DESIGN AND DEVELOPMENT OF A LOW COST PROSTHETIC ARM CONTROL SYSTEM BASED ON sEMG SIGNAL
【24h】

DESIGN AND DEVELOPMENT OF A LOW COST PROSTHETIC ARM CONTROL SYSTEM BASED ON sEMG SIGNAL

机译:基于SEMG信号的低成本假臂控制系统的设计与开发

获取原文

摘要

The aim of this paper is to design and develop a low-cost prosthetic arm based on surface electromyography (sEMG) signal activities of the biceps muscle during upper-limb movement. Different methods are described in the literature, but many problems are encountered in dealing with the online processing of raw EMG (rEMG) signals, such as signal sampling and memory requirements. In this paper, the enveloped EMG (eEMG) signal is used as a control signal that reduces signal sampling rate and memory requirements. The relationship between elbow motion and the activity level of the biceps muscle is characterized using relevant extracted features (root mean square (RMS)). Validation of the proposed low-cost system is conducted using comparison with a professional biomedical system (Bioback MP150). In addition, the estimated equation of movements of each subject is estimated based on the recorded data. From this equation, the angle of motion is calculated as the control of the movement of the robotic arm. Finally, the system proposed in this paper considers the eEMG signal rather than the rEMG signal and deals with the signal based on a sample of 1 KHz rather than 10 KHz. This system reduces our target cost (reduction in hardware requirements and processing time) with acceptable accuracy. The experimental results illustrate that the eEMG signal has the same features-print as that of the rEMG signal, and the eEMG signal can generate the control signal required to move the prosthetic arm.
机译:本文的目的是根据肢体运动期间基于二头肌肌的表面肌电学(SEMG)信号活动来设计和开发低成本的假体臂。文献中描述了不同的方法,但在处理RAW EMG(REMG)信号的在线处理时遇到了许多问题,例如信号采样和存储器要求。在本文中,包络的EMG(EEMG)信号用作控制信号,可降低信号采样率和存储器要求。使用相关提取特征(均方根(RMS))表征弯头运动与二头肌肌的活性水平的关系。使用与专业生物医学系统(BioBack MP150)的比较进行所提出的低成本系统的验证。另外,基于记录的数据估计每个对象的估计的运动的估计方程。从这个等式中,运动角度计算为机器人臂的移动的控制。最后,本文提出的系统考虑了EEMG信号而不是REMG信号,并根据1kHz而不是10kHz的样本处理信号。该系统可通过可接受的准确度降低我们的目标成本(减少硬件要求和处理时间)。实验结果表明,EEMG信号具有与REMG信号的特征相同的特征,并且EEMG信号可以产生移动假体臂所需的控制信号。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号