Literature DB >> 22244106

An EMG-driven musculoskeletal model of the shoulder.

A A Nikooyan1, H E J Veeger, P Westerhoff, B Bolsterlee, F Graichen, G Bergmann, F C T van der Helm.   

Abstract

This paper aims to develop an EMG-driven model of the shoulder that can consider possible muscle co-contractions. A musculoskeletal shoulder model (the original model) is modified such that measured EMGs can be used as model-inputs (the EMG-driven model). The model is validated by using the in-vivo measured glenohumeral-joint reaction forces (GH-JRFs). Three patients carrying instrumented hemi-arthroplasty were asked to perform arm abduction and forward-flexion up to maximum possible elevation, during which motion data, EMG, and in-vivo GH-JRF were measured. The measured EMGs were normalized and together with analyzed motions served as model inputs to estimate the GH-JRF. All possible combinations of input EMGs ranging from a single signal to all EMG signals together were tested. The 'best solution' was defined as the combination of EMGs which yielded the closest match between the model and the experiments. Two types of inconsistencies between the original model and the measurements were observed including a general GH-JRF underestimation and a GH-JRF drop above 90° elevation. Both inconsistencies appeared to be related to co-contraction since inclusion of EMGs could significantly (p<.05) improve the predicted GH-JRF (up to 45%). The developed model has shown the potential to successfully take the existent muscle co-contractions of patients into account.
Copyright © 2011 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 22244106     DOI: 10.1016/j.humov.2011.08.006

Source DB:  PubMed          Journal:  Hum Mov Sci        ISSN: 0167-9457            Impact factor:   2.161


  11 in total

Review 1.  Clinical applications of musculoskeletal modelling for the shoulder and upper limb.

Authors:  Bart Bolsterlee; Dirkjan H E J Veeger; Edward K Chadwick
Journal:  Med Biol Eng Comput       Date:  2013-07-20       Impact factor: 2.602

2.  Glenohumeral stability during a hand-positioning task in previously injured shoulders.

Authors:  James Marchi; Dimitra Blana; Edward K Chadwick
Journal:  Med Biol Eng Comput       Date:  2013-05-24       Impact factor: 2.602

3.  Stochastic modelling of muscle recruitment during activity.

Authors:  Saulo Martelli; Daniela Calvetti; Erkki Somersalo; Marco Viceconti
Journal:  Interface Focus       Date:  2015-04-06       Impact factor: 3.906

4.  Musculotendon lengths and moment arms for a three-dimensional upper-extremity model.

Authors:  Jeffery W Rankin; Richard R Neptune
Journal:  J Biomech       Date:  2012-04-19       Impact factor: 2.712

5.  Determining the Online Measurable Input Variables in Human Joint Moment Intelligent Prediction Based on the Hill Muscle Model.

Authors:  Baoping Xiong; Nianyin Zeng; Yurong Li; Min Du; Meilan Huang; Wuxiang Shi; Guoju Mao; Yuan Yang
Journal:  Sensors (Basel)       Date:  2020-02-21       Impact factor: 3.576

6.  sEMG-assisted inverse modelling of 3D lip movement: a feasibility study towards person-specific modelling.

Authors:  Merijn Eskes; Alfons J M Balm; Maarten J A van Alphen; Ludi E Smeele; Ian Stavness; Ferdinand van der Heijden
Journal:  Sci Rep       Date:  2017-12-18       Impact factor: 4.379

7.  A Matlab toolbox for scaled-generic modeling of shoulder and elbow.

Authors:  Ehsan Sarshari; Yasmine Boulanaache; Alexandre Terrier; Alain Farron; Philippe Mullhaupt; Dominique Pioletti
Journal:  Sci Rep       Date:  2021-10-21       Impact factor: 4.379

8.  EMGD-FE: an open source graphical user interface for estimating isometric muscle forces in the lower limb using an EMG-driven model.

Authors:  Luciano Luporini Menegaldo; Liliam Fernandes de Oliveira; Kin K Minato
Journal:  Biomed Eng Online       Date:  2014-04-04       Impact factor: 2.819

9.  A New Skeleton Model and the Motion Rhythm Analysis for Human Shoulder Complex Oriented to Rehabilitation Robotics.

Authors:  Song Zhibin; Ma Tianyu; Nie Chao; Niu Yijun
Journal:  Appl Bionics Biomech       Date:  2018-06-03       Impact factor: 1.781

10.  Estimating the Effects of Awareness on Neck-Muscle Loading in Frontal Impacts with EMG and MC Sensors.

Authors:  Simon Krašna; Srđan Đorđević
Journal:  Sensors (Basel)       Date:  2020-07-15       Impact factor: 3.576

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