A human-assisting manipulator teleoperated by EMG signals and arm motions

By O. Fukuda, T. Tsuji, M. Kaneko, A. Otsuka. IEEE Trans. Robotics Autom., 2003

524 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/d0707d722817f8bb75c8627b9cc6a5b4d23181e4

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In Mechanical Engineering

Citations in the corpus

Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use. (2011, background): “been shown during extended use [67] and for specifically”
Myoelectric control systems - A survey (2007, methodology): “MCS in the hand-wrist part of a human-assisting manipulator [14].”
Support Vector Machine-Based Classification Scheme for Myoelectric Control Applied to Upper Limb (2008, unknown): “Furthermore, Huang et al. [13] and Fukuda et al. [14] developed a GMM as a classifier in their MCS; the former showed an accuracy of approximately 97%.”
Teleoperation of a robot manipulator using a vision-based human-robot interface (2005, methodology): “Commonly used mechanical human–machine interfaces for teleoperation, include a variety of devices worn by an operator, such as exoskeletal mechanical devices [1], instrumented gloves [2], [3], electromagnetic [4] or inertial [4], [5] motion tracking sensors, or electromyographic muscular activity se”
Online customization of teleoperation interfaces (2012, background): “While there are many interfaces for teleoperation, especially for robot manipulators [8]–[10], the retargetting function is usually designed a-priori and cannot be changed.”
Deep Learning with Convolutional Neural Networks Applied to Electromyography Data: A Resource for the Classification of Movements for Prosthetic Hands (2016, methodology): “The sEMG electrodes are positioned in order to combine two methods that are common in the field, i.e., a dense sampling approach (Fukuda et al., 2003; Tenore et al., 2009; Li et al., 2010) and a precise anatomical positioning strategy (De Luca, 1997; Castellini et al., 2009).”
Teleoperation with intelligent and customizable interfaces (2013, methodology): “…& Jenkins, 2008) has applied function approximation techniques to learn the policy from examples provided by a human or another robot.1 We adopt the same principle, and use an extension to Online Learning with Kernel Machines(Kivinen, Smola, & Williamson, 2004) as the function approximator.”