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Surface EMG pattern recognition for real-time control of a wrist exoskeleton

机译:表面肌电图模式识别可实时控制手腕外骨骼

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摘要

BackgroundSurface electromyography (sEMG) signals have been used in numerous studies for the classification of hand gestures and movements and successfully implemented in the position control of different prosthetic hands for amputees. sEMG could also potentially be used for controlling wearable devices which could assist persons with reduced muscle mass, such as those suffering from sarcopenia. While using sEMG for position control, estimation of the intended torque of the user could also provide sufficient information for an effective force control of the hand prosthesis or assistive device. This paper presents the use of pattern recognition to estimate the torque applied by a human wrist and its real-time implementation to control a novel two degree of freedom wrist exoskeleton prototype (WEP), which was specifically developed for this work.
机译:背景技术表面肌电(sEMG)信号已在众多研究中用于手势和动作的分类,并成功地用于截肢者的不同假手的位置控制中。 sEMG还可以潜在地用于控制可穿戴设备,这些设备可以帮助肌肉量减少的人,例如肌肉减少症患者。在使用sEMG进行位置控制时,用户预期扭矩的估算还可以提供足够的信息,以有效地控制手部假体或辅助设备的力。本文介绍了使用模式识别来估算人手腕施加的扭矩及其实时实现,以控制新颖的两自由度手腕外骨骼原型(WEP),该原型是专为这项工作而开发的。

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