An exoskeletal robot for human elbow motion support-sensor fusion, adaptation, and control

Kiguchi, Kazuo; Kariya, S.; Watanabe, Keigo; Izumi, Kiyotaka; Fukuda, Toshio

doi:10.1109/3477.931520

Cited by 143 publications

(72 citation statements)

References 22 publications

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“…The robot is used to assist the motion of physically weak persons such as elderly, disabled and injured [37][38][39]. Although EMG signals directly reflect the human motion intention, it is difficult to control the robotic exoskeleton since the strength of EMG varies with factors like physical and physiological conditions, placement of electrodes, shift of electrodes and high nonlinearity of muscle activity for a certain motion.…”

Section: Emg Based Neuro-fuzzy Control Methodsmentioning

confidence: 99%

Recent Trends in EMG-Based Control Methods for Assistive Robots

Gopura¹,

Bandara²,

Gunasekara³

et al. 2013

Electrodiagnosis in New Frontiers of Clinical Research

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Section: Emg Based Neuro-fuzzy Control Methodsmentioning

confidence: 99%

Recent Trends in EMG-Based Control Methods for Assistive Robots

Gopura¹,

Bandara²,

Gunasekara³

et al. 2013

Electrodiagnosis in New Frontiers of Clinical Research

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“…By adjusting the amount of force generated by these muscles, the elbow angle can be arbitrary controlled. 15 …”

Section: Experiments Protocolmentioning

confidence: 99%

Comparison of contact interface factors for surface electromyography control wearable device

Wang

Sun

Tang

2018

Advances in Mechanical Engineering

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Surface electromyography is commonly used as control signals for wearable devices. Compared to physical sensors, bioelectric signal are more sensitive to pressure and placement of interface. Discussion of these factors includes not only ergonomic issues but also control issues. Variations of the two factors in setup could lead to variability in output values. In this article, we mainly discussed the influence of the two factors, including contact pressure and placement, to estimate the elbow joint angles based on surface electromyography. To our knowledge, there has been no research about this problem. We first measured the surface electromyography signal with elbow flexion and extension motion, then estimated the angles of motion through the pattern recognition method, and finally assessed the distribution of contact pressure and the accuracy of regression. Our results indicated that the accuracy of angle recognition depends on the consistency of pressure distribution over the contact surface. The contact surface can be placed in the anterior of the upper arm at lower contact pressures. When high contact pressure is required, the placement of the strap should cover the muscle belly. The main contribution of this study is that our results can be used to guide the human-machine interface design of wearable devices.

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“…Consequently, biceps and a part triceps are biparticular muscles. By adjusting the amount of force generated by these muscles, the elbow angle and impedance can be arbitrary controlled (Kiguchi et al, 2001). Contraction of the biceps brachii flexes the elbow.…”

Section: Muscle Anatomymentioning

confidence: 99%