Literature DB >> 30737118

Musculoskeletal model-based inverse dynamic analysis under ambulatory conditions using inertial motion capture.

Angelos Karatsidis1, Moonki Jung2, H Martin Schepers3, Giovanni Bellusci3, Mark de Zee4, Peter H Veltink5, Michael Skipper Andersen6.   

Abstract

Inverse dynamic analysis using musculoskeletal modeling is a powerful tool, which is utilized in a range of applications to estimate forces in ligaments, muscles, and joints, non-invasively. To date, the conventional input used in this analysis is derived from optical motion capture (OMC) and force plate (FP) systems, which restrict the application of musculoskeletal models to gait laboratories. To address this problem, we propose the use of inertial motion capture to perform musculoskeletal model-based inverse dynamics by utilizing a universally applicable ground reaction force and moment (GRF&M) prediction method. Validation against a conventional laboratory-based method showed excellent Pearson correlations for sagittal plane joint angles of ankle, knee, and hip (ρ=0.95, 0.99, and 0.99, respectively) and root-mean-squared-differences (RMSD) of 4.1 ± 1.3°, 4.4 ± 2.0°, and 5.7 ± 2.1°, respectively. The GRF&M predicted using IMC input were found to have excellent correlations for three components (vertical: ρ=0.97, RMSD = 9.3 ± 3.0 %BW, anteroposterior: ρ=0.91, RMSD = 5.5 ± 1.2 %BW, sagittal: ρ=0.91, RMSD = 1.6 ± 0.6 %BW*BH), and strong correlations for mediolateral (ρ=0.80, RMSD = 2.1 ± 0.6 %BW) and transverse (ρ=0.82, RMSD = 0.2 ± 0.1 %BW*BH). The proposed IMC-based method removes the complexity and space restrictions of OMC and FP systems and could enable applications of musculoskeletal models in either monitoring patients during their daily lives or in wider clinical practice.
Copyright © 2019 IPEM. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Gait analysis; Ground reaction forces and moments; Inertial motion capture; Inverse dynamics; Musculoskeletal modeling

Mesh:

Year:  2019        PMID: 30737118     DOI: 10.1016/j.medengphy.2018.12.021

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  15 in total

1.  Flexible Machine Learning Algorithms for Clinical Gait Assessment Tools.

Authors:  Christian Greve; Hobey Tam; Manfred Grabherr; Aditya Ramesh; Bart Scheerder; Juha M Hijmans
Journal:  Sensors (Basel)       Date:  2022-06-30       Impact factor: 3.847

2.  Accuracy and Repeatability of Spatiotemporal Gait Parameters Measured with an Inertial Measurement Unit.

Authors:  Jorge Posada-Ordax; Julia Cosin-Matamoros; Marta Elena Losa-Iglesias; Ricardo Becerro-de-Bengoa-Vallejo; Laura Esteban-Gonzalo; Carlos Martin-Villa; César Calvo-Lobo; David Rodriguez-Sanz
Journal:  J Clin Med       Date:  2021-04-21       Impact factor: 4.241

3.  Indirect measurement of anterior-posterior ground reaction forces using a minimal set of wearable inertial sensors: from healthy to hemiparetic walking.

Authors:  Dheepak Arumukhom Revi; Andre M Alvarez; Conor J Walsh; Stefano M M De Rossi; Louis N Awad
Journal:  J Neuroeng Rehabil       Date:  2020-06-29       Impact factor: 4.262

Review 4.  Wearable Inertial Sensors for Gait Analysis in Adults with Osteoarthritis-A Scoping Review.

Authors:  Dylan Kobsar; Zaryan Masood; Heba Khan; Noha Khalil; Marium Yossri Kiwan; Sarah Ridd; Matthew Tobis
Journal:  Sensors (Basel)       Date:  2020-12-13       Impact factor: 3.576

5.  Accuracy and Acceptability of Wearable Motion Tracking for Inpatient Monitoring Using Smartwatches.

Authors:  Chaiyawan Auepanwiriyakul; Sigourney Waibel; Joanna Songa; Paul Bentley; A Aldo Faisal
Journal:  Sensors (Basel)       Date:  2020-12-19       Impact factor: 3.576

6.  Intra- and inter-rater reliability of joint range of motion tests using tape measure, digital inclinometer and inertial motion capturing.

Authors:  Laura Fraeulin; Fabian Holzgreve; Mark Brinkbäumer; Anna Dziuba; David Friebe; Stefanie Klemz; Marco Schmitt; Anna-Lena Theis A; Sarah Tenberg; Anke van Mark; Christian Maurer-Grubinger; Daniela Ohlendorf
Journal:  PLoS One       Date:  2020-12-10       Impact factor: 3.240

7.  Influence of Treadmill Design on Gait: Does Treadmill Size Affect Muscle Activation Amplitude? A Musculoskeletal Calculation With Individualized Input Parameters of Gait Analysis.

Authors:  Matthias Woiczinski; Carolin Lehner; Thekla Esser; Manuel Kistler; Monica Azqueta; Johannes Leukert; Leandra Bauer; Eduard Kraft
Journal:  Front Neurol       Date:  2022-03-02       Impact factor: 4.003

8.  Wearables-Only Analysis of Muscle and Joint Mechanics: An EMG-Driven Approach.

Authors:  Reed D Gurchiek; Nicole Donahue; Niccolo M Fiorentino; Ryan S McGinnis
Journal:  IEEE Trans Biomed Eng       Date:  2022-01-20       Impact factor: 4.538

Review 9.  Validity and reliability of wearable inertial sensors in healthy adult walking: a systematic review and meta-analysis.

Authors:  Dylan Kobsar; Jesse M Charlton; Calvin T F Tse; Jean-Francois Esculier; Angelo Graffos; Natasha M Krowchuk; Daniel Thatcher; Michael A Hunt
Journal:  J Neuroeng Rehabil       Date:  2020-05-11       Impact factor: 4.262

Review 10.  These legs were made for propulsion: advancing the diagnosis and treatment of post-stroke propulsion deficits.

Authors:  Louis N Awad; Michael D Lewek; Trisha M Kesar; Jason R Franz; Mark G Bowden
Journal:  J Neuroeng Rehabil       Date:  2020-10-21       Impact factor: 4.262

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