Exoskeleton for human upper-limb motion support

Kiguchi, Kazuo; Tanaka, Tomokazu; Watanabe, Keigo; Fukuda, Toshio

doi:10.1109/robot.2003.1241921

Cited by 27 publications

(8 citation statements)

References 14 publications

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“…ANN can be used to represent both linear and non-linear relationships but as the number of input increases, complexity of network also increases which is the drawback of this method (Boca and Park, 1994;Badri, 2010;Fahlaman and Liebiere, 1990;Chowdhury et al, 2013;Cheron et al, 1996). Fuzzy logic is simple phenomena and has ability to tolerate certain degree of contradictions in the data (Kiguchi et al, 2004;Khezri, 2011;Francis et al, 2000;Kiguchi et al, 2003;Weir and Ajiboye, 2003). ICA is recommended only if a huge number of features are used as input to the classifier in order to reduce the computational complexity of classifiers (Comon, 1994;Staudenmann et al, 2007;Naik et al, 2010;García et al, 2003).…”

Section: Discussionmentioning

confidence: 99%

“…The inference engine maps each rule's fuzzy input sets into each rule's fuzzy output set. Kiguchi et al (2003) developed a fuzzy controller to control the elbow and shoulder joint angles of the exoskeleton based on the moving average value of EMG signals from arm and shoulder muscles and the generated wrist force. There have been many works on applying the fuzzy approach to EMG classification and control of assistive devices.…”

Section: Fuzzy Logicmentioning

confidence: 99%

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Advancements in soft computing methods for EMG classification

Kaur

Singh

Shaw

2016

IJBET

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Electromyography (EMG) signals that represent the electrical activity of muscles are increasingly used for various clinical and biomedical applications. Detection, processing and classification of EMG signals require advanced soft computing methods to gain better understanding and precise evaluation of these signals in various applications such as rehabilitation technology, neurophysiological disorders and assistive technological findings. This paper provides comprehensive overview of the different methods for classification of EMG signals.

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Section: Discussionmentioning

confidence: 99%

Section: Fuzzy Logicmentioning

confidence: 99%

Advancements in soft computing methods for EMG classification

Kaur

Singh

Shaw

2016

IJBET

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“…So it is expected that motor driven system should be used to make the exoskeleton robot simple. Researchers are also trying to control the actuation through EMG sensors using fuzzy algorithm [10]. Generally impedance control is usually implemented in which the Cartesian forces applied at the joint are converted into joint torque commands using the Jacobian [1] matrix.…”

Section: The Literature Reviewmentioning

confidence: 99%

A Bioinspired 10 DOF Wearable Powered Arm Exoskeleton for Rehabilitation

Manna

Bhaumik

2013

Journal of Robotics

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The developed exoskeleton device (Exorn) has ten degrees of freedom to control joints starting from shoulder griddle to wrist to provide better redundancy, portability, and flexibility to the human arm motion. A 3D conceptual model is being designed to make the system wearable by human arm. All the joints are simple revolute joints with desired motion limit. A Simulink model of the human arm is being developed with proper mass and length to determine proper torque required for actuating those joints. Forward kinematics of the whole system has been formulated for getting desired dexterous workspace. A proper and simple Graphical User Interface (GUI) and the required embedded system have been designed for providing physiotherapy lessons to the patients. In the literature review it has been found that researchers have generally ignored the motion of shoulder griddle. Here we have implemented those motions in our design. It has also been found that people have taken elbow pronation and supination motion as a part of shoulder internal and external rotation though both motions are quite different. A predefined resolved motion rate control structure with independent joint control is used so that all movements can be controlled in a predefined way.

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“…Upper-limb exoskeletons were mainly designed for rehabilitation of stroke patients or for helping people in performing painful tasks. Kiguchiet al designed a 3 degrees-of-freedom (DOF) exoskeleton for only shoulder and elbow motions [2]. Later, Gopura et al designed a 7 DOF arm exoskeleton called SUEFUL-7 [3], which uses realtime control method based on skin surface electromyographic (EMG) signals.…”

Section: Introductionmentioning

confidence: 99%

Assessing neuromuscular mechanisms in human-exoskeleton interaction

Sylla

Bonnet²,

Venture³

et al. 2014

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Abstract-In this study, we propose to evaluate a 7 DOF exoskeleton in terms of motion control. Using criteria from the human motor control literature, inverse optimization was performed to assess an industrial screwing movement. The results of our study show that the hybrid composition of the free arm movement was accurately determined. At contrary, when wearing the exoskeleton, which produces an arbitrary determined torque compensation, the motion is different from the naturally adopted one. This study is part of the evaluation and comprehension of the complex neuromuscular mechanism resulting in wearing an exoskeleton several hours per day for industrial tasks assistance.

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Exoskeleton for human upper-limb motion support

Cited by 27 publications

References 14 publications

Advancements in soft computing methods for EMG classification

Advancements in soft computing methods for EMG classification

A Bioinspired 10 DOF Wearable Powered Arm Exoskeleton for Rehabilitation

Assessing neuromuscular mechanisms in human-exoskeleton interaction

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