Literature DB >> 21659017

The effects of electrode size and orientation on the sensitivity of myoelectric pattern recognition systems to electrode shift.

Aaron J Young1, Levi J Hargrove, Todd A Kuiken.   

Abstract

Myoelectric pattern recognition systems for prosthesis control are often studied in controlled laboratory settings, but obstacles remain to be addressed before they are clinically viable. One important obstacle is the difficulty of maintaining system usability with socket misalignment. Misalignment inevitably occurs during prosthesis donning and doffing, producing a shift in electrode contact locations. We investigated how the size of the electrode detection surface and the placement of electrode poles (electrode orientation) affected system robustness with electrode shift. Electrodes oriented parallel to muscle fibers outperformed electrodes oriented perpendicular to muscle fibers in both shift and no-shift conditions (p < 0.01). Another finding was the significant difference (p < 0.01) in performance for the direction of electrode shift. Shifts perpendicular to the muscle fibers reduced classification accuracy and real-time controllability much more than shifts parallel to the muscle fibers. Increasing the size of the electrode detection surface was found to help reduce classification accuracy sensitivity to electrode shifts in a direction perpendicular to the muscle fibers but did not improve the real-time controllability of the pattern recognition system. One clinically important result was that a combination of longitudinal and transverse electrodes yielded high controllability with and without electrode shift using only four physical electrode pole locations.

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Year:  2011        PMID: 21659017      PMCID: PMC4234036          DOI: 10.1109/TBME.2011.2159216

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  25 in total

1.  A wavelet-based continuous classification scheme for multifunction myoelectric control.

Authors:  K Englehart; B Hudgins; P A Parker
Journal:  IEEE Trans Biomed Eng       Date:  2001-03       Impact factor: 4.538

2.  Classification of the myoelectric signal using time-frequency based representations.

Authors:  K Englehart; B Hudgins; P A Parker; M Stevenson
Journal:  Med Eng Phys       Date:  1999 Jul-Sep       Impact factor: 2.242

3.  Geometrical factors in surface EMG of the vastus medialis and lateralis muscles.

Authors:  A Rainoldi; M Nazzaro; R Merletti; D Farina; I Caruso; S Gaudenti
Journal:  J Electromyogr Kinesiol       Date:  2000-10       Impact factor: 2.368

Review 4.  Control of multifunctional prosthetic hands by processing the electromyographic signal.

Authors:  M Zecca; S Micera; M C Carrozza; P Dario
Journal:  Crit Rev Biomed Eng       Date:  2002

5.  Independence of myoelectric control signals examined using a surface EMG model.

Authors:  Madeleine M Lowery; Nikolay S Stoykov; Todd A Kuiken
Journal:  IEEE Trans Biomed Eng       Date:  2003-06       Impact factor: 4.538

6.  A robust, real-time control scheme for multifunction myoelectric control.

Authors:  Kevin Englehart; Bernard Hudgins
Journal:  IEEE Trans Biomed Eng       Date:  2003-07       Impact factor: 4.538

7.  Innervation zones of the upper and lower limb muscles estimated by using multichannel surface EMG.

Authors:  K Saitou; T Masuda; D Michikami; R Kojima; M Okada
Journal:  J Hum Ergol (Tokyo)       Date:  2000-12

8.  Effects of electrode location on myoelectric conduction velocity and median frequency estimates.

Authors:  S H Roy; C J De Luca; J Schneider
Journal:  J Appl Physiol (1985)       Date:  1986-10

9.  Determining the optimal window length for pattern recognition-based myoelectric control: balancing the competing effects of classification error and controller delay.

Authors:  Lauren H Smith; Levi J Hargrove; Blair A Lock; Todd A Kuiken
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2010-12-30       Impact factor: 3.802

10.  A three-state myo-electric control.

Authors:  D S Dorcas; R N Scott
Journal:  Med Biol Eng       Date:  1966-07
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  39 in total

1.  Improving myoelectric pattern recognition robustness to electrode shift by changing interelectrode distance and electrode configuration.

Authors:  Aaron J Young; Levi J Hargrove; Todd A Kuiken
Journal:  IEEE Trans Biomed Eng       Date:  2011-11-29       Impact factor: 4.538

Review 2.  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

3.  An Epidermal Stimulation and Sensing Platform for Sensorimotor Prosthetic Control, Management of Lower Back Exertion, and Electrical Muscle Activation.

Authors:  Baoxing Xu; Aadeel Akhtar; Yuhao Liu; Hang Chen; Woon-Hong Yeo; Sung Ii Park; Brandon Boyce; Hyunjin Kim; Jiwoo Yu; Hsin-Yen Lai; Sungyoung Jung; Yuhao Zhou; Jeonghyun Kim; Seongkyu Cho; Yonggang Huang; Timothy Bretl; John A Rogers
Journal:  Adv Mater       Date:  2015-10-15       Impact factor: 30.849

4.  Application of an LDA Classifier for Determining User-Intent in Multi-DOF Quasi-Static Shoulder Tasks in Individuals with Chronic Stroke: Preliminary Analysis.

Authors:  Joseph V Kopke; Levi J Hargrove; Michael D Ellis
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2018-07

5.  Analysis of electrode shift effects on wavelet features embedded in a myoelectric pattern recognition system.

Authors:  Juan M Fontana; Alan W L Chiu
Journal:  Assist Technol       Date:  2014

6.  Classification of simultaneous movements using surface EMG pattern recognition.

Authors:  Aaron J Young; Lauren H Smith; Elliott J Rouse; Levi J Hargrove
Journal:  IEEE Trans Biomed Eng       Date:  2012-12-10       Impact factor: 4.538

7.  Training Strategies for Mitigating the Effect of Proportional Control on Classification in Pattern Recognition Based Myoelectric Control.

Authors:  Erik Scheme; Kevin Englehart
Journal:  J Prosthet Orthot       Date:  2013-04-01

8.  Patient training for functional use of pattern recognition-controlled prostheses.

Authors:  Ann M Simon; Blair A Lock; Kathy A Stubblefield
Journal:  J Prosthet Orthot       Date:  2012-04

9.  Multi-position Training Improves Robustness of Pattern Recognition and Reduces Limb-Position Effect in Prosthetic Control.

Authors:  Robert J Beaulieu; Matthew R Masters; Joseph Betthauser; Ryan J Smith; Rahul Kaliki; Nitish V Thakor; Alcimar B Soares
Journal:  J Prosthet Orthot       Date:  2017-04

Review 10.  The future of upper extremity rehabilitation robotics: research and practice.

Authors:  Philip P Vu; Cynthia A Chestek; Samuel R Nason; Theodore A Kung; Stephen W P Kemp; Paul S Cederna
Journal:  Muscle Nerve       Date:  2020-06       Impact factor: 3.217

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