Literature DB >> 31009829

Two degrees of freedom, dynamic, hand-wrist EMG-force using a minimum number of electrodes.

Chenyun Dai1, Ziling Zhu2, Carlos Martinez-Luna3, Thane R Hunt4, Todd R Farrell3, Edward A Clancy5.   

Abstract

Few studies have related the surface electromyogram (EMG) of forearm muscles to two degree of freedom (DoF) hand-wrist forces; ones that have, used large high-density electrode arrays that are impractical for most applied biomechanics research. Hence, we researched EMG-force in two DoFs-hand open-close paired with one wrist DoF-using as few as four conventional electrodes, comparing equidistant placement about the forearm to optimized site selection. Nine subjects produced 1-DoF and 2-DoF uniformly distributed random forces (bandlimited to 0.75 Hz) up to 30% maximum voluntary contraction (MVC). EMG standard deviation (EMGσ) was related to force offline using linear dynamic regression models. For 1-DoF forces, average RMS errors using two optimally-sited electrodes ranged from 8.3 to 9.0 %MVC, depending on the DoF. For 2-DoFs, overall performance was best when training from both 1- and 2-DoF trials, giving average RMS errors using four optimally-sited electrodes of 9.2 %MVC for each DoF pair (hand open-close paired with one wrist DoF). For each model, additional optimally-sited electrodes showed little statistical improvement. Electrodes placed equidistant performed noticeably poorer than an equal number of electrodes that were optimally sited. The results suggest that reliable 2-DoF hand-wrist EMG-force with a small number of electrodes may be feasible.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  EMG signal processing; EMG-force; Electromyogram

Mesh:

Year:  2019        PMID: 31009829      PMCID: PMC6556412          DOI: 10.1016/j.jelekin.2019.04.003

Source DB:  PubMed          Journal:  J Electromyogr Kinesiol        ISSN: 1050-6411            Impact factor:   2.368


  45 in total

1.  Relation of human electromyogram to muscular tension.

Authors:  V T INMAN; H J RALSTON; J B SAUNDERS; B FEINSTEIN; E W WRIGHT
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1952-05

2.  Less is more: high pass filtering, to remove up to 99% of the surface EMG signal power, improves EMG-based biceps brachii muscle force estimates.

Authors:  J R Potvin; S H M Brown
Journal:  J Electromyogr Kinesiol       Date:  2004-06       Impact factor: 2.368

Review 3.  A critical evaluation of the force control hypothesis in motor control.

Authors:  David J Ostry; Anatol G Feldman
Journal:  Exp Brain Res       Date:  2003-09-13       Impact factor: 1.972

4.  Influence of advanced electromyogram (EMG) amplitude processors on EMG-to-torque estimation during constant-posture, force-varying contractions.

Authors:  Edward A Clancy; Oljeta Bida; Denis Rancourt
Journal:  J Biomech       Date:  2005-10-20       Impact factor: 2.712

5.  Bayesian filtering of myoelectric signals.

Authors:  Terence D Sanger
Journal:  J Neurophysiol       Date:  2006-12-20       Impact factor: 2.714

Review 6.  Myoelectric signal processing for control of powered limb prostheses.

Authors:  P Parker; K Englehart; B Hudgins
Journal:  J Electromyogr Kinesiol       Date:  2006-10-11       Impact factor: 2.368

7.  Neuromusculoskeletal modeling: estimation of muscle forces and joint moments and movements from measurements of neural command.

Authors:  Thomas S Buchanan; David G Lloyd; Kurt Manal; Thor F Besier
Journal:  J Appl Biomech       Date:  2004-11       Impact factor: 1.833

8.  Effect of elbow joint angle on force-EMG relationships in human elbow flexor and extensor muscles.

Authors:  Emer P Doheny; Madeleine M Lowery; David P Fitzpatrick; Mark J O'Malley
Journal:  J Electromyogr Kinesiol       Date:  2007-05-11       Impact factor: 2.368

Review 9.  Surface electromyography and muscle force: limits in sEMG-force relationship and new approaches for applications.

Authors:  Catherine Disselhorst-Klug; Thomas Schmitz-Rode; Günter Rau
Journal:  Clin Biomech (Bristol, Avon)       Date:  2008-10-11       Impact factor: 2.063

10.  A clinically applicable EMG-force model to quantify active stabilization of the knee after a lesion of the anterior cruciate ligament.

Authors:  Caroline A M Doorenbosch; Jaap Harlaar
Journal:  Clin Biomech (Bristol, Avon)       Date:  2003-02       Impact factor: 2.063

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  3 in total

1.  EMG-Force and EMG-Target Models During Force-Varying Bilateral Hand-Wrist Contraction in Able-Bodied and Limb-Absent Subjects.

Authors:  Ziling Zhu; Carlos Martinez-Luna; Jianan Li; Benjamin E McDonald; Chenyun Dai; Xinming Huang; Todd R Farrell; Edward A Clancy
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2021-01-28       Impact factor: 3.802

2.  Myoelectric Control Performance of Two Degree of Freedom Hand-Wrist Prosthesis by Able-Bodied and Limb-Absent Subjects.

Authors:  Ziling Zhu; Jianan Li; William J Boyd; Carlos Martinez-Luna; Chenyun Dai; Haopeng Wang; He Wang; Xinming Huang; Todd R Farrell; Edward A Clancy
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2022-04-11       Impact factor: 4.528

Review 3.  Estimating Biomechanical Time-Series with Wearable Sensors: A Systematic Review of Machine Learning Techniques.

Authors:  Reed D Gurchiek; Nick Cheney; Ryan S McGinnis
Journal:  Sensors (Basel)       Date:  2019-11-28       Impact factor: 3.576

  3 in total

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