Simulation of Anterior Cruciate Ligament Deficiency in a Musculoskeletal Model with Anatomical Knees

Abnormal knee kinematics and meniscus injury resulting from anterior cruciate ligament (ACL) deficiency are often implicated in joint degeneration even though changes in tibio-femoral contact location after injury are small, typically only a few millimeters. Ligament reconstruction surgery does not significantly reduce the incidence of early onset osteoarthritis. Increased knowledge of knee contact mechanics would increase our understanding of the effects of ACL injury and help guide ACL reconstruction methods. Presented here is a cadaver specific computational knee model combined with a body-level musculoskeletal model from a subject of similar height and weight as the cadaver donor. The knee model was developed in the multi-body framework and includes representation of the menisci. Experimental body-level measurements provided input to the musculoskeletal model. The location of tibio-menisco-femoral contact as well as contact pressures were compared for models with an intact ACL, partial ACL transection (posterolateral bundle transection), and full ACL transection during a muscle driven forward dynamics simulation of a dual limb squat. During the squat, small changes in femur motion relative to the tibia for both partial and full ACL transection push the lateral meniscus in the posterior direction at extension. The central-anterior region of the lateral meniscus then becomes “wedged” between the tibia and femur during knee flexion. This “wedging” effect does not occur for the intact knee. Peak contact pressure and contact locations are similar for the partial tear and complete ACL transection during the deep flexion portion of the squat, particularly on the lateral side. The tibio-femoral contact location on the tibia plateau shifts slightly to the posterior and lateral direction with ACL transection

Computational Knee Ligament Modeling Using Experimentally Determined Zero-Load Lengths

This study presents a subject-specific method of determining the zero-load lengths of the cruciate and collateral ligaments in computational knee modeling. Three cadaver knees were tested in a dynamic knee simulator. The cadaver knees also underwent manual envelope of motion testing to find their passive range of motion in order to determine the zero-load lengths for each ligament bundle. Computational multibody knee models were created for each knee and model kinematics were compared to experimental kinematics for a simulated walk cycle. One-dimensional non-linear spring damper elements were used to represent cruciate and collateral ligament bundles in the knee models. This study found that knee kinematics were highly sensitive to altering of the zero-load length. The results also suggest optimal methods for defining each of the ligament bundle zero-load lengths, regardless of the subject. These results verify the importance of the zero-load length when modeling the knee joint and verify that manual envelope of motion measurements can be used to determine the passive range of motion of the knee joint. It is also believed that the method described here for determining zero-load length can be used for in vitro or in vivo subject-specific computational models

Multi-disciplinary Collaborations in Measurement of Human Motion

Comparative Medicine - OneHealth and Comparative Medicine Poster SessionBioengineering is a broad and rapidly-growing discipline defined as the application of engineering principles to biological systems. Although bioengineering is diverse in nature, the study of human movement is common to many bioengineering subdisciplines such as biomechanics and biometrics. Biomechanics is the science that examines the forces acting upon and within a biological structure and effects produced by such forces [1]. Measurement of ground reaction forces, limb motion, and muscle activation are fundamental research components in musculoskeletal biomechanics. Researchers in this field have used these measurements to quantify human gait, balance, and posture in a multitude of applications including age-related fall risk [2-4], muscle fatigue [5-7], and balance-related pathologies such as Parkinson's disease [8-10], and stroke [11, 12]. Additionally, these measurements play a vital role in computational biomechanics models. For example, the inverse dynamics method incorporates measured ground reaction forces and body motions to calculate the net reaction forces and torques acting on body joints [13]. Biometrics is the science of confirming or discovering individuals' identities based on their specific biological or behavioral traits [14]. Gait is one such modality which can be used for biometric identification. It is based on the uniqueness of an individual's locomotion patterns [15]. In addition, we are interested in high-speed video analyses of micro-saccades and blink reflexes for spoof-proofing of biometric identification systems, biometric identification, and psychometry. We have shown that startle blink intensity can be derived from high- speed video [18], enabling video-based psychophysiological biometrics for detection of subject-specific affective-cognitive information [19]. The Human Motion Laboratory at the University of Missouri - Kansas City is dedicated to measuring the characteristics of human motion. The lab includes a VICON MX 6-camera motion capture system, 4 AMTI OR6-6 force platforms, and a Delsys Myomonitor IV 16-channel wireless EMG system. This equipment represents an experimental infrastructure mutually supporting the biomechanics and biometrics research efforts of four research labs. The scope of these research efforts includes aging, affective computing, psychophysiological biometrics, orthopedics, and human dynamics pathology. The lab capitalizes on a synergistic environment for characterization and measurement of human movement and the interrelated nature of the research activities. The four main research areas that the Human Motion Laboratory supports are: •Computational Biomechanics •Biometrics of Human Motion •Experimental Biomechanics •Body Area Sensor Network

Clinical and Computational Collaboration in Orthopaedic Biomechanics

Computational Infrastructure and Informatics Poster SessionThe mission of the Comparative Orthopaedic Laboratory at the University of Missouri-Columbia (COL-UMC) is three-fold: 1.To design and conduct the highest quality hypothesis-driven research focused on orthopaedic disorders of . 2. To implement a comparative approach to investigation of joint disease in order to most efficiently and comprehensively address identified problem. 3. To apply basic science research to the clinical situation in order to span the gap that often limits the usefulness of scientific discoveries. The mission of the Musculoskeletal Biomechanics Research Laboratory (MBRL) at the University of Missouri - Kansas City is to: Discover, disseminate, and utilize knowledge pertaining to the loading of joint tissues during dynamic activity. The (COL-UMC) includes an internationally recognized team of scientists and clinicians while the MBRL, in conjunction with the UMKC Human Motion Laboratory, is comprised of biomedical engineers focused on musculoskeletal tissue mechanics and movement simulation. Collaboration between the two labs can provide great benefit for both research programs by combining clinical, computational, and experimental research efforts. The COL-UMC and the MBRL are currently working together on a Missouri Life Sciences Research Board funded project titled, ”Computational Simulation of Canine Biomechanically Induced Unicompartmental Osteoarthritis: a Concurrent Multiscale Approach”. This work combines the internationally recognized expertise in canine osteoarthritis and tissue engineering of the COL-UMC with the musculoskeletal biomechanics expertise and innovative multiscale modeling techniques of the MBRL. Osteoarthritis is a debilitating disease that is not completely understood, but evidence links the severity, progression, and treatment of the disease to the mechanical environment in the knee during everyday activities such as walking, running, and stair climbing. The natural response of articular cartilage to insult or injury is an outcome of complex interconnected factors that include anatomy, biology, and muscle forces. The goal of this project is to develop a predictive, computationally efficient, patient level simulation tool of mechanical osteoarthritis indicators. Specifically, the project is developing computational models of the canine knee that include surrogate models of cartilage tissue behavior. This model is then combined with neuromusculoskeletal models of movement and validated through in-vivo canine models of osteoarthritis. The project addresses a key area in osteoarthritis research that has largely been neglected, the role of muscles in osteoarthritis pathomechanics. Several engineering students from UMKC and medical students from UMC are working on the project and excellent progress has been made in the first year. Project work includes: 1) Mechanical testing to determine material properties of the canine menisci and articular cartilage 2) Magnetic Resonance Imaging and generation of hind limb bone, cartilage, ligament, muscle, and menisci geometries 3) Development of knee and musculoskeletal models of the hind limb 4) Meniscal release procedure to induce unicompartmental osteoarthritis 5)Gait testing at the UMKC Human Motion lab both pre-surgery and post-surgery 6) Hind limb testing to validate developed musculoskeletal models 7) Development of tissue level finite element models of cartilage indentation testing for tissue level surrogates

Force-Time Waveform Shape Reveals Countermovement Jump Strategies of Collegiate Athletes

The purpose of this study was to relate the shape of countermovement jump (CMJ) vertical ground reaction force waveforms to discrete parameters and determine if waveform shape could enhance CMJ analysis. Vertical ground reaction forces during CMJs were collected for 394 male and female collegiate athletes competing at the National Collegiate Athletic Association (NCAA) Division 1 and National Association of Intercollegiate Athletics (NAIA) levels. Jump parameters were calculated for each athlete and principal component analysis (PCA) was performed on normalized force-time waveforms consisting of the eccentric braking and concentric phases. A K-means clustering of PCA scores placed athletes into three groups based on their waveform shape. The overall average waveforms of all athletes in each cluster produced three distinct vertical ground reaction force waveform patterns. There were significant differences across clusters for all calculated jump parameters. Athletes with a rounded single hump shape jumped highest and quickest. Athletes with a plateau at the transition between the eccentric braking and concentric phase (amortization) followed by a peak in force near the end of the concentric phase had the lowest jump height and slowest jump time. Analysis of force-time waveform shape can identify differences in CMJ strategies in collegiate athletes