Literature DB >> 23445057

Update on grand challenge competition to predict in vivo knee loads.

Allison L Kinney1, Thor F Besier, Darryl D D'Lima, Benjamin J Fregly.   

Abstract

Validation is critical if clinicians are to use musculoskeletal models to optimize treatment of individual patients with a variety of musculoskeletal disorders. This paper provides an update on the annual Grand Challenge Competition to Predict in Vivo Knee Loads, a unique opportunity for direct validation of knee contact forces and indirect validation of knee muscle forces predicted by musculoskeletal models. Three competitions (2010, 2011, and 2012) have been held at the annual American Society of Mechanical Engineers Summer Bioengineering Conference, and two more competitions are planned for the 2013 and 2014 conferences. Each year of the competition, a comprehensive data set collected from a single subject implanted with a force-measuring knee replacement is released. Competitors predict medial and lateral knee contact forces for two gait trials without knowledge of the experimental knee contact force measurements. Predictions are evaluated by calculating root-mean-square (RMS) errors and R(2) values relative to the experimentally measured medial and lateral contact forces. For the first three years of the competition, competitors used a variety of methods to predict knee contact and muscle forces, including static and dynamic optimization, EMG-driven models, and parametric numerical models. Overall, errors in predicted contact forces were comparable across years, with average RMS errors for the four competition winners ranging from 229 N to 312 N for medial contact force and from 238 N to 326 N for lateral contact force. Competitors generally predicted variations in medial contact force (highest R(2 )= 0.91) better than variations in lateral contact force (highest R(2 )= 0.70). Thus, significant room for improvement exists in the remaining two competitions. The entire musculoskeletal modeling community is encouraged to use the competition data and models for their own model validation efforts.

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Year:  2013        PMID: 23445057      PMCID: PMC3597120          DOI: 10.1115/1.4023255

Source DB:  PubMed          Journal:  J Biomech Eng        ISSN: 0148-0731            Impact factor:   2.097


  7 in total

1.  Grand challenge competition to predict in vivo knee loads.

Authors:  Benjamin J Fregly; Thor F Besier; David G Lloyd; Scott L Delp; Scott A Banks; Marcus G Pandy; Darryl D D'Lima
Journal:  J Orthop Res       Date:  2011-12-12       Impact factor: 3.494

2.  An implantable telemetry device to measure intra-articular tibial forces.

Authors:  Darryl D D'Lima; Christopher P Townsend; Steven W Arms; Beverly A Morris; Clifford W Colwell
Journal:  J Biomech       Date:  2005-02       Impact factor: 2.712

3.  A multiaxial force-sensing implantable tibial prosthesis.

Authors:  Bryan Kirking; Janet Krevolin; Christopher Townsend; Clifford W Colwell; Darryl D D'Lima
Journal:  J Biomech       Date:  2006       Impact factor: 2.712

Review 4.  Model-based estimation of muscle forces exerted during movements.

Authors:  Ahmet Erdemir; Scott McLean; Walter Herzog; Antonie J van den Bogert
Journal:  Clin Biomech (Bristol, Avon)       Date:  2006-10-27       Impact factor: 2.063

5.  Implications of increased medio-lateral trunk sway for ambulatory mechanics.

Authors:  Annegret Mündermann; Jessica L Asay; Lars Mündermann; Thomas P Andriacchi
Journal:  J Biomech       Date:  2007-08-03       Impact factor: 2.712

6.  Dual-joint modeling for estimation of total knee replacement contact forces during locomotion.

Authors:  Michael W Hast; Stephen J Piazza
Journal:  J Biomech Eng       Date:  2013-02       Impact factor: 2.097

7.  Design of patient-specific gait modifications for knee osteoarthritis rehabilitation.

Authors:  Benjamin J Fregly; Jeffrey A Reinbolt; Kelly L Rooney; Kim H Mitchell; Terese L Chmielewski
Journal:  IEEE Trans Biomed Eng       Date:  2007-09       Impact factor: 4.538

  7 in total
  19 in total

1.  Prediction of In Vivo Knee Joint Loads Using a Global Probabilistic Analysis.

Authors:  Alessandro Navacchia; Casey A Myers; Paul J Rullkoetter; Kevin B Shelburne
Journal:  J Biomech Eng       Date:  2016-03       Impact factor: 2.097

2.  The Influence of Component Alignment and Ligament Properties on Tibiofemoral Contact Forces in Total Knee Replacement.

Authors:  Colin R Smith; Michael F Vignos; Rachel L Lenhart; Jarred Kaiser; Darryl G Thelen
Journal:  J Biomech Eng       Date:  2016-02       Impact factor: 2.097

3.  Patient-specific computer model of dynamic squatting after total knee arthroplasty.

Authors:  Hideki Mizu-Uchi; Clifford W Colwell; Cesar Flores-Hernandez; Benjamin J Fregly; Shuichi Matsuda; Darryl D D'Lima
Journal:  J Arthroplasty       Date:  2015-01-10       Impact factor: 4.757

4.  Predicted loading on the menisci during gait: The effect of horn laxity.

Authors:  Trent M Guess; Swithin Razu; Hamidreza Jahandar; Antonis Stylianou
Journal:  J Biomech       Date:  2015-03-14       Impact factor: 2.712

5.  Muscle synergies may improve optimization prediction of knee contact forces during walking.

Authors:  Jonathan P Walter; Allison L Kinney; Scott A Banks; Darryl D D'Lima; Thor F Besier; David G Lloyd; Benjamin J Fregly
Journal:  J Biomech Eng       Date:  2014-02       Impact factor: 2.097

6.  Multiscale musculoskeletal modelling, data-model fusion and electromyography-informed modelling.

Authors:  J Fernandez; J Zhang; T Heidlauf; M Sartori; T Besier; O Röhrle; D Lloyd
Journal:  Interface Focus       Date:  2016-04-06       Impact factor: 3.906

7.  Electromyography-Driven Forward Dynamics Simulation to Estimate In Vivo Joint Contact Forces During Normal, Smooth, and Bouncy Gaits.

Authors:  Swithin S Razu; Trent M Guess
Journal:  J Biomech Eng       Date:  2018-07-01       Impact factor: 2.097

8.  Practical approach to subject-specific estimation of knee joint contact force.

Authors:  Brian A Knarr; Jill S Higginson
Journal:  J Biomech       Date:  2015-04-22       Impact factor: 2.712

Review 9.  The nature of in vivo mechanical signals that influence cartilage health and progression to knee osteoarthritis.

Authors:  Thomas P Andriacchi; Julien Favre
Journal:  Curr Rheumatol Rep       Date:  2014-11       Impact factor: 4.592

10.  Neuromusculoskeletal Model Calibration Significantly Affects Predicted Knee Contact Forces for Walking.

Authors:  Gil Serrancolí; Allison L Kinney; Benjamin J Fregly; Josep M Font-Llagunes
Journal:  J Biomech Eng       Date:  2016-08-01       Impact factor: 2.097

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