Development and Evaluation of a Musculoskeletal Model of the Elbow Joint Complex

Gonzalez, Roger V.; Hutchins, E. L.; Barr, Ronald E.; Abraham, Lawrence D.

doi:10.1115/1.2795943

Cited by 56 publications

(34 citation statements)

References 24 publications

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“…This information is vital in the design of orthopaedic implants and surgical treatments, the development of upper extremity models [8], as well as in the basic comprehension of human musculoskeletal system mechanics. However, solving for the joint and muscle loads based on a free-body analysis results in an indeterminate problem, and consequently numerous optimization techniques have been developed in an attempt to solve this dilemma.…”

Section: Introductionmentioning

confidence: 99%

Electromyographic activity and strength during maximum isometric pronation and supination efforts in healthy adults

Gordon

Pardo

Johnson

et al. 2004

Journal Orthopaedic Research

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There exists a lack of quantitative data in the literature related to the torque produced during axial forearm rotation and the electromyographic (EMG) activity of the muscles involved. Therefore, the purpose of this study was to compare the relative EMG activity of four forearm muscles during resisted forearm rotation. A custom-built device capable of measuring torque in the absence of grip was employed. Fourteen healthy volunteers performed maximum isometric voluntary contractions in five positions of axial forearm rotation for both pronation and supination. E M G data were collected simultaneously from the supinator, biceps, pronator quadratus (deep and superficial heads), and pronator teres muscles using fine-wire bipolar electrodes. Data were analyzed to determine the contributions of each muscle to pronation and supination torque over five positions of forearm rotation. In the absence of grip no significant difference was found between supination and pronation torque in neutral position. Supination torque generation was greater in the pronated forearm positions, and pronation torque was greater in the supinated positions (p < 0.05). A root-mean-square EMG analysis verified the major contributions of the pronator teres and both heads of the pronator quadratus muscle to pronation torque, and supinator and biceps to supination torque. The deep head of the pronator quadratus was active during both pronation and supination, lending support to the theory that it may act primarily as a dynamic distal radioulnar joint stabilizer. This information may be helpful in upper extremity modeling, surgical treatments, and rehabilitation strategies.

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Section: Introductionmentioning

confidence: 99%

Electromyographic activity and strength during maximum isometric pronation and supination efforts in healthy adults

Gordon

Pardo

Johnson

et al. 2004

Journal Orthopaedic Research

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“…Therefore, computational multibody models of the elbow could be a valuable tool to improve the diagnosis, treatment and rehabilitation of post-traumatic injuries of the elbow joint. Many researchers have used these model to investigate muscle contribution to joint moment (Arnold & Delp, 2001;Gonzalez et al, 1996;Hutchins, Gonzalez, & Barr, 1993;Lemay & Crago, 1996;Murray, Delp, & Buchanan, 1995;van der Helm, 1994a) and body segment motion (Anderson & Pandy, 2001;Gonzalez, Abraham, Barr, & Buchanan, 1999;Nagano, Komura, Yoshioka, & Fukashiro, 2005;Peck, Langenbach, & Hannam, 2000;van der Helm, 1994b). A validated model can be used as a potential biomechanical tool for patient-specific preoperative planning, computer-aided surgery, and computer-aided rehabilitation (Chao, Armiger, Yoshida, Lim, & Haraguchi, 2007;Fernandez & Pandy, 2006;Fisk & Wayne, 2009;Holzbaur, Murray, & Delp, 2005;Kwak et al, 2000;Woo, Debski, Wong, Yagi, & Tarinelli, 1999).…”

Section: Introductionmentioning

confidence: 99%

“…Two main tools have been used in biomechanics for developing computational models: finite element analysis (FEA) (Giddings et al, 2000;Li, Gil, Kanamori, & Woo, 1999;van der Helm, 1994b;Wu, Dong, Smutz, & Schopper, 2003) and multibody dynamics (MBD) (Anderson & Pandy, 2001;Barker, Kirtley, & Ratanapinunchai, 1997;Chaudhari & Andriacchi, 2006;Cohen et al, 2003;Freund & Takala, 2001;Gonzalez, Andritsos, Barr, & Abraham, 1993;Gonzalez et al, 1996;Hirokawa, 1991;Iwasaki et al, 1998;Kwak et al, 2000;Lemay & Crago, 1996;Li et al, 1999;Liacouras & Wayne, 2007;Lin et al, 2005; Morey-Klapsing, Arampatzis, & Bruggemann, 2005;Nagano et al, 2005;Peck et al, 2000;Piazza & Delp, 2001;Raikova, 1992Raikova, , 1996Shelburne et al, 2004;Triolo, Werner, & Kirsch, 2001;Wismans et al, 1980). FEA has the ability to predict the stress and strain within tissue in articulating contacts.…”

Section: Introductionmentioning

confidence: 99%

“…Numerous studies of computational modeling have been developed to investigate joint behavior (Buchanan, Delp, & Solbeck, 1998;Fisk & Wayne, 2009;Garner & Pandy, 2001;Gonzalez et al, 1999;Gonzalez et al, 1996;Holzbaur et al, 2005;Kwak et al, 2000;Lemay & Crago, 1996;Raikova, 1992;Schuind et al, 1991;Spratley & Wayne, 2011;Triolo et al, 2001). Gonzalez et al (1996) developed a computational elbow model to investigate the elbow joint movement, relationship among muscle excitation patterns, and to determine the effects of forearm and elbow position on the recruitment of individual muscles during ballistic movements.…”

Section: Introductionmentioning

confidence: 99%

“…The human elbow joint is a unique joint that produces the complex motion of the forearm for hand positioning and allows humans to accomplish numerous significant activities in their daily life that makes them distinct from other mammals (Gonzalez, Hutchins, Barr, & Abraham, 1996).Unfortunately, this most important joint of the upper extremity (Morrey, 2000) has been recognized as the second most commonly dislocated joint in adults (de Haan et al, 2011). Although not as common as in the knee joint, osteoarthritis of the elbow can cause severe pain in the joint, loss of joint mobility, and can be a cause of entire upper limb disability (Degreef & De Smet, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Development and validation of a computational multibody model of the elbow joint

Rahman

2014

Advances in biomechanics and applications

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Computational multibody models of the elbow joint can provide a powerful tool to study joint biomechanics, examine muscle and ligament function, soft tissue loading, and the effects of joint trauma. Such models can reduce the cost of expensive experimental testing and can predict some parameters that are difficult to investigate experimentally, such as forces within ligaments and contact forces between cartilage covered bones. These parameters can assist surgeons and other investigators to develop better treatments for elbow injuries and thereby increase patient care. Biomechanical computational models of the elbow exist in the literature, but these models are typically limited in their applicability by artificially constraining the joint (e.g. modeling the elbow as a hinge joint), prescribing specific kinematics, simplifying ligament characteristics or ignoring cartilage geometries.The purpose of this thesis was to develop anatomically correct subject specific computational multibody models of elbow joints and validate these models against experimental data. In these models, the joints were constrained by three-dimensional deformable contacts between articulating geometries, passive muscle loading, and multiple bundles of non-linear ligaments wrapped around the bones. iv In this approach, three-dimensional bone geometries for the model were constructed from volume images generated by computed tomography (CT) scans obtained from cadaver elbows. The ligaments and triceps tendon were modeled as spring-damper elements with non-linear stiffness. Articular cartilage was represented as uniform thickness solids covering the articulating bone surfaces. Finally, the model was validated by placing the cadaver elbows in a mechanical testing apparatus and comparing predicted kinematics and triceps tendon forces to experimentally measured values. A small improvement in predicted kinematics was observed compared to experimental values when the lateral ulnar collateral and annular ligament were wrapped around the bone. Some reductions of RMS error were also observed when a non-linear toe region was modeled in the ligament compared to models that had only a linear force-displacement relationship. None of these changes were statistically significant (ANOVA p-value was greater than 0.05).

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Effect of simulated muscle activity on distal radioulnar joint loading in vitro

et al. 2006

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This study investigated the relationship between simulated forearm muscle loads and the joint reaction force in the distal radioulnar joint using an in vitro model. Seven fresh frozen cadaveric specimens were mounted in an upper extremity joint simulator capable of applying pneumatic loads to various (muscle) tendons while restraining the forearm in the three positions of pronation, supination, and neutral rotation. Loads were applied to model four forearm muscles (biceps, pronator teres, pronator quadratus, and supinator) in 10 N increments ranging from 10 N to 80 N for the biceps and pronator teres and in 10 N increments from 10 N to 50 N for the pronator quadratus and the supinator. Distal ulnar arthroplasty was performed on each specimen with a custom instrumented ulnar head replacement implant that quantified loads (via strain gauge instrumentation). The relationship between increasing muscle load and joint load was found to be positive and quasilinear in most cases. The biceps had the greatest influence on the distal radioulnar joint reaction force with a joint force in the range of 8% to 33% of the applied muscle load. The pronator teres, supinator, and pronator quadratus were less influential with a joint reaction force ranging between 6% to 19%, 4% to 9% and 2% to 10% of the applied muscle load, respectively.

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Development and Evaluation of a Musculoskeletal Model of the Elbow Joint Complex

Abstract: i Elbow joint complex (EJC) refers to the articulations responsible for the combined movements of elbow flextonext_nszon, forearm pronation-suptnanon, anti forearm abductaon-adductzon Ipasszve mouonl.https://ntrs.nasa.gov/search.jsp?R=19950004837 2018-05-09T16:41:09+00:00Z

Cited by 56 publications

References 24 publications

Electromyographic activity and strength during maximum isometric pronation and supination efforts in healthy adults

Electromyographic activity and strength during maximum isometric pronation and supination efforts in healthy adults

Development and validation of a computational multibody model of the elbow joint

Effect of simulated muscle activity on distal radioulnar joint loading in vitro

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