Literature DB >> 29504071

A 3-DOF hemi-constrained wrist motion/force detection device for deploying simultaneous myoelectric control.

Wei Yang1, Dapeng Yang2,3, Yu Liu1, Hong Liu1.   

Abstract

For describing the state of the wrist, either the force or movement of wrist can be measured as the training target in the simultaneous electromyography control. However, the relationship between the force and movement is so complex that only the force or movement is not precise enough to describe its actual situations. In this paper, we propose a novel platform that can acquire three degrees of freedom (DOF) wrist motion/force synchronously with multi-channel electromyography signals in a hemi-constraint way. The self-made wrist force-movement mapping device establishes a stable relationship between the wrist movement and force. Meanwhile, the elicited wrist movement can be directly fed back to the subjects via laser cursor. The information of the cursor can directly reflect the 3-DOF movement of the wrist without any decoupling algorithms. Through this platform, the support vector regression model learned from the training data can well predict the arbitrary combinations of 3-DOF wrist movements. The cross-validation result indicates that the regression accuracy of free 3-DOF movements can reach a similar performance to that of 2-DOF regular movements (in terms of R2, regular movement vs. free movement, p > 0.1). Graphical abstract The hemi-constrained platform used for detecting 3-DOF wrist movements.

Keywords:  Regression; Simultaneous control; Surface electromyography; Wrist motion

Mesh:

Year:  2018        PMID: 29504071     DOI: 10.1007/s11517-018-1807-2

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  14 in total

1.  Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use.

Authors:  Erik Scheme; Kevin Englehart
Journal:  J Rehabil Res Dev       Date:  2011

2.  Support vector machine-based classification scheme for myoelectric control applied to upper limb.

Authors:  Mohammadreza Asghari Oskoei; Huosheng Hu
Journal:  IEEE Trans Biomed Eng       Date:  2008-08       Impact factor: 4.538

3.  Extracting simultaneous and proportional neural control information for multiple-DOF prostheses from the surface electromyographic signal.

Authors:  Ning Jiang; Kevin B Englehart; Philip A Parker
Journal:  IEEE Trans Biomed Eng       Date:  2008-10-31       Impact factor: 4.538

4.  Enhanced EMG signal processing for simultaneous and proportional myoelectric control.

Authors:  Johnny L G Nielsen; Steffen Holmgaard; Ning Jiang; Kevin Englehart; Dario Farina; Philip Parker
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

5.  Selective classification for improved robustness of myoelectric control under nonideal conditions.

Authors:  Erik J Scheme; Kevin B Englehart; Bernard S Hudgins
Journal:  IEEE Trans Biomed Eng       Date:  2011-02-10       Impact factor: 4.538

6.  Hough transform from the radon transform.

Authors:  S R Deans
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  1981-02       Impact factor: 6.226

7.  Wrist torque estimation during simultaneous and continuously changing movements: surface vs. untargeted intramuscular EMG.

Authors:  Ernest N Kamavuako; Erik J Scheme; Kevin B Englehart
Journal:  J Neurophysiol       Date:  2013-03-20       Impact factor: 2.714

8.  Continuous and simultaneous estimation of finger kinematics using inputs from an EMG-to-muscle activation model.

Authors:  Jimson G Ngeo; Tomoya Tamei; Tomohiro Shibata
Journal:  J Neuroeng Rehabil       Date:  2014-08-14       Impact factor: 4.262

9.  EMG-based simultaneous and proportional estimation of wrist/hand kinematics in uni-lateral trans-radial amputees.

Authors:  Ning Jiang; Johnny L G Vest-Nielsen; Silvia Muceli; Dario Farina
Journal:  J Neuroeng Rehabil       Date:  2012-06-28       Impact factor: 4.262

Review 10.  Control Capabilities of Myoelectric Robotic Prostheses by Hand Amputees: A Scientific Research and Market Overview.

Authors:  Manfredo Atzori; Henning Müller
Journal:  Front Syst Neurosci       Date:  2015-11-30
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  1 in total

Review 1.  Improving the functionality, robustness, and adaptability of myoelectric control for dexterous motion restoration.

Authors:  Dapeng Yang; Yikun Gu; Nitish V Thakor; Hong Liu
Journal:  Exp Brain Res       Date:  2018-11-30       Impact factor: 1.972

  1 in total

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