Literature DB >> 21785529

Design of Optimal Treatments for Neuromusculoskeletal Disorders using Patient-Specific Multibody Dynamic Models.

Benjamin J Fregly1.   

Abstract

Disorders of the human neuromusculoskeletal system such as osteoarthritis, stroke, cerebral palsy, and paraplegia significantly affect mobility and result in a decreased quality of life. Surgical and rehabilitation treatment planning for these disorders is based primarily on static anatomic measurements and dynamic functional measurements filtered through clinical experience. While this subjective treatment planning approach works well in many cases, it does not predict accurate functional outcome in many others. This paper presents a vision for how patient-specific multibody dynamic models can serve as the foundation for an objective treatment planning approach that identifies optimal treatments and treatment parameters on an individual patient basis. First, a computational paradigm is presented for constructing patient-specific multibody dynamic models. This paradigm involves a combination of patient-specific skeletal models, muscle-tendon models, neural control models, and articular contact models, with the complexity of the complete model being dictated by the requirements of the clinical problem being addressed. Next, three clinical applications are presented to illustrate how such models could be used in the treatment design process. One application involves the design of patient-specific gait modification strategies for knee osteoarthritis rehabilitation, a second involves the selection of optimal patient-specific surgical parameters for a particular knee osteoarthritis surgery, and the third involves the design of patient-specific muscle stimulation patterns for stroke rehabilitation. The paper concludes by discussing important challenges that need to be overcome to turn this vision into reality.

Entities:  

Year:  2009        PMID: 21785529      PMCID: PMC3141573     

Source DB:  PubMed          Journal:  Int J Comput Vis Biomech        ISSN: 0973-6778


  79 in total

1.  A new method for estimating joint parameters from motion data.

Authors:  Michael H Schwartz; Adam Rozumalski
Journal:  J Biomech       Date:  2005-01       Impact factor: 2.712

2.  Muscle-tendon interaction and elastic energy usage in human walking.

Authors:  Masaki Ishikawa; Paavo V Komi; Michael J Grey; Vesa Lepola; Gert-Peter Bruggemann
Journal:  J Appl Physiol (1985)       Date:  2005-04-21

3.  Validation of a new model-based tracking technique for measuring three-dimensional, in vivo glenohumeral joint kinematics.

Authors:  Michael J Bey; Roger Zauel; Stephanie K Brock; Scott Tashman
Journal:  J Biomech Eng       Date:  2006-08       Impact factor: 2.097

4.  An optimized image matching method for determining in-vivo TKA kinematics with a dual-orthogonal fluoroscopic imaging system.

Authors:  Jeffrey Bingham; Guoan Li
Journal:  J Biomech Eng       Date:  2006-08       Impact factor: 2.097

5.  Early revision for component malrotation in total knee arthroplasty.

Authors:  Stephen J Incavo; John J Wild; Kathryn M Coughlin; Bruce D Beynnon
Journal:  Clin Orthop Relat Res       Date:  2007-05       Impact factor: 4.176

6.  Relationship between pain and medial knee joint loading in mild radiographic knee osteoarthritis.

Authors:  Laura E Thorp; Dale R Sumner; Markus A Wimmer; Joel A Block
Journal:  Arthritis Rheum       Date:  2007-10-15

7.  Evaluation of a patient-specific cost function to predict the influence of foot path on the knee adduction torque during gait.

Authors:  Benjamin J Fregly; Jeffery A Reinbolt; Terese L Chmielewski
Journal:  Comput Methods Biomech Biomed Engin       Date:  2007-10-15       Impact factor: 1.763

8.  Improvements in speed-based gait classifications are meaningful.

Authors:  Arlene Schmid; Pamela W Duncan; Stephanie Studenski; Sue Min Lai; Lorie Richards; Subashan Perera; Samuel S Wu
Journal:  Stroke       Date:  2007-05-17       Impact factor: 7.914

9.  Muscle-driven forward dynamic simulations for the study of normal and pathological gait.

Authors:  Stephen J Piazza
Journal:  J Neuroeng Rehabil       Date:  2006-03-06       Impact factor: 4.262

10.  Predicting muscle forces of individuals with hemiparesis following stroke.

Authors:  Trisha M Kesar; Jun Ding; Anthony S Wexler; Ramu Perumal; Ryan Maladen; Stuart A Binder-Macleod
Journal:  J Neuroeng Rehabil       Date:  2008-02-27       Impact factor: 4.262

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  5 in total

1.  Modeling and simulating the neuromuscular mechanisms regulating ankle and knee joint stiffness during human locomotion.

Authors:  Massimo Sartori; Marco Maculan; Claudio Pizzolato; Monica Reggiani; Dario Farina
Journal:  J Neurophysiol       Date:  2015-08-05       Impact factor: 2.714

2.  Are subject-specific musculoskeletal models robust to the uncertainties in parameter identification?

Authors:  Giordano Valente; Lorenzo Pitto; Debora Testi; Ajay Seth; Scott L Delp; Rita Stagni; Marco Viceconti; Fulvia Taddei
Journal:  PLoS One       Date:  2014-11-12       Impact factor: 3.240

3.  Knee Cartilage Thickness, T1ρ and T2 Relaxation Time Are Related to Articular Cartilage Loading in Healthy Adults.

Authors:  Sam Van Rossom; Colin Robert Smith; Lianne Zevenbergen; Darryl Gerard Thelen; Benedicte Vanwanseele; Dieter Van Assche; Ilse Jonkers
Journal:  PLoS One       Date:  2017-01-11       Impact factor: 3.240

4.  MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation.

Authors:  Alice Mantoan; Claudio Pizzolato; Massimo Sartori; Zimi Sawacha; Claudio Cobelli; Monica Reggiani
Journal:  Source Code Biol Med       Date:  2015-11-16

5.  Simulation of normal and pathological gaits using a fusion knowledge strategy.

Authors:  Fabio Martínez; Christian Cifuentes; Eduardo Romero
Journal:  J Neuroeng Rehabil       Date:  2013-07-11       Impact factor: 4.262

  5 in total

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