Date on Master's Thesis/Doctoral Dissertation

4-2015

Document Type

Master's Thesis

Degree Name

M. Eng.

Department

Bioengineering

Committee Chair

Bertocci, Gina

Committee Co-Chair (if applicable)

Howland, Dena

Committee Member

Howland, Dena

Committee Member

Magnuson, David

Committee Member

Thompson, Angela

Abstract

Intervertebral disc disease (IVDD) is a naturally occurring disease in dogs that produces a spontaneous injury to the spinal cord. IVDD is characterized by mineralization of the intervertebral disc nucleus pulposus, which reduces its load bearing capacity and results in high rates of intervertebral disc herniation (IVDH). IVDH is disproportionately present in Dachshunds compared to other breeds, affecting an estimated 1 in 5 Dachshunds during their lifetime (Levine, J. M. et al., 2011). Assessment of injury severity and recovery in animal models is generally performed using a point scale, where subjects are graded according to metrics such as pain perception, joint movement, and limb coordination (Basso et al., 1995; Levine, G. J. et al., 2009; Olby, N. J. et al., 2001). Although these methods provide a general view of recovery, they are unable to quantify metrics such as joint motion/torque and muscle activation/force produced during specific phases of gait. OpenSim is an open source software package that allows users to estimate joint kinematics/torques and muscle forces/activations in a musculoskeletal model, which can be scaled to a subject’s dimensions (Delp et al., 2007). Generic musculoskeletal models have been developed in the OpenSim platform for humans (Delp et al., 1990), cats (Keshner et al., 1997), and rats (Johnson et al., 2008), however to the author’s knowledge no model has been developed for dogs. April 12, 2016 The purpose of the proposed study was to develop a subject-specific neuromusculoskeletal computer model of a healthy dog using OpenSim software (Delp, Anderson et al. 2007) to deduce patterns of muscle activity during locomotion. The long- term goal of this study is to utilize the model to inform rehabilitation strategies to enhance recovery and function in dogs with SCI based upon an improved understanding of muscle activation patterns. Additionally, the ability to characterize muscle activation patterns will provide a tool for quantifying the efficacy of therapeutic interventions in a canine model that could allow for potential therapeutic advancement in both dogs and humans. The specific aims of this study were: 1. To characterize joint kinematics of healthy Dachshunds during walking gait. 2. To compare model-predicted joint kinematics to measured joint kinematics in healthy Dachshunds during walking gait. H1: Pelvic limb joint range of motion of the model-predicted kinematics will not be different from kinematics calculated from marker trajectory data. H2: Measured motion tracking marker trajectories will not be different from virtual model-predicted marker trajectories. 3. To quantify model sensitivity to changes in maximum muscle isometric force. H3: Varying maximum muscle isometric force will affect peak muscle activation. v April 12, 2016 To address these aims, a bilateral 3D model of the bony structures of the pelvis and pelvic limb (femur, tibia/fibula, phalanges, and metatarsals) and muscles was created using computed tomography (CT) imaging data. Parameters for the OpenSim model such as muscle origins and insertions, muscle cross-sectional area, and tendon slack length were obtained using computed tomography data or values from literature studies. Kinematic and kinetic data were incorporated in OpenSim to estimate joint kinematics and muscle activation patterns during locomotion. In this study a subject-specific canine pelvic limb neuromusculoskeletal OpenSim model was developed based upon anatomically accurate data, as well as parameters of dogs described in literature. This model included representation of bilateral pelvic limb boney segments and muscles. This model was used to predict kinematics, muscle activation patterns and muscle forces during simulated gait. Findings illustrated that the model provided a reasonable approximation of joint kinematics as compared to measured joint kinematics, based on correlation coefficients calculated between modeled and measured joint kinematics and motion tracking marker trajectory data. The extensor digitorum longus, tibialis cranialis, adductor, vastus lateralis/medialis, rectus femoris, and tensor fascia lata were primarily active during stance. The vastus lateralis/medialis, rectus femoris, tensor fascia lata, sartorius and gluteus medius were active during the first half of swing, while the adductor, semimembranosus, semitendinosus, and biceps femoris were active during the second half of swing. These activation patterns compare similarly with those found in the scientific literature, despite vi April 12, 2016 vii inherent differences in the comparison. This study illustrates the utility of an OpenSim model by demonstrating the ability to accurately model kinematic data, and predict muscle activation patterns during gait. Future work should involve further verification of modeled joint torques and muscle parameters, as well as describe small muscles not included in the current model.

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