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Finger Movements Classification for the Dexterous Control of Upper Limb Prosthesis Using EMG Signals

机译:使用EMG信号灵活控制上肢假肢的手指运动分类

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摘要

Nowadays, there are thousands of disabled people around the world who had lost a limb. The majority of them are hand amputees with different level of amputation ranging from elbow disarticulation to upper digits amputation[l]. To bring those people back to normal life, amputees used artificial hand prosthesis controlled by the muscle signal known as Surface Electromyography (sEMG) recorded form the skin surface of residual limb of the amputee. The muscle signal is also commonly named as myoelectric signal. These devices will help amputees to improve their lives and make them self-confident. It has been reported that EMG activity recorded from the amputee forearm muscles after hand amputation are similar to EMG of healthy subjects [2, 3]. Therefore, there is still an EMG signal when the amputee intends to perform a movement. This fact has inspired researchers to develop EMG signal processing algorithms for the control of a prosthetic hand with the electrical signal of the muscles.
机译:如今,世界各地有成千上万的残疾人失去了肢体。他们大多数是截肢水平不同的截肢者,从肘关节脱臼到高位截肢[1]。为了使这些人恢复正常生活,截肢者使用了人工肌肉假体,该人工假体受肌肉信号控制,称为“表面肌电图(sEMG)”,记录在截肢者残肢的皮肤表面。肌肉信号通常也称为肌电信号。这些设备将帮助截肢者改善生活,使他们更加自信。据报道,截肢后从截肢者前臂肌肉记录的EMG活性与健康受试者的EMG相似[2,3]。因此,当被截肢者打算进行移动时,仍然存在一个EMG信号。这一事实启发了研究人员开发EMG信号处理算法,以利用肌肉的电信号控制假手。

著录项

  • 来源
    《Advances in autonomous robotics》|2012年|434-435|共2页
  • 会议地点 Bristol(GB)
  • 作者单位

    School of Computing and Mathematics, Plymouth University, Plymouth, UK;

    School of Computing and Mathematics, Plymouth University, Plymouth, UK;

    School of Computing and Mathematics, Plymouth University, Plymouth, UK;

    School of Computing and Mathematics, Plymouth University, Plymouth, UK;

    School of Computing and Mathematics, Plymouth University, Plymouth, UK;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
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