Eugene J. Alexander

A framework for the in vivo pathomechanics of osteoarthritis at the knee

The in vivo pathomechanics of osteoarthritis (OA) at the knee is described in a framework that is based on an analysis of studies describing assays of biomarkers, cartilage morphology, and human function (gait analysis). The framework is divided into an Initiation Phase and a Progression Phase. The Initiation Phase is associated with kinematic changes that shift load bearing to infrequently loaded regions of the cartilage that cannot accommodate the loads. The Progression Phase is defined following cartilage breakdown. During the Progression Phase, the disease progresses more rapidly with increased load. While this framework was developed from an analysis of in vivopathomechanics, it also explains how the convergence of biological, morphological, and neuromuscular changes to the musculoskeletal system during aging or during menopause lead to the increased rate of idiopathic OA with aging. Understanding the in vivo response of articular cartilage to its physical environment requires an integrated view of the problem that considers functional, anatomical, and biological interactions. The integrated in vivoframework presented here will be helpful for the interpretation of laboratory experiments as well as for the development of new methods for the evaluation of OA at the knee.

A Point Cluster Method for In Vivo Motion Analysis: Applied to a Study of Knee Kinematics

A new method for deriving limb segment motion from markers placed on the skin is described. The method provides a basis for determining the artifact associated with nonrigid body movement of points placed on the skin. The method is based on a cluster of points uniformly distributed on the limb segment. Each point is assigned an arbitrary mass. The center of mass and the inertia tensor of this cluster of points are calculated. The eigenvalues and eigenvectors of the inertia tensor are used to define a coordinate system in the cluster as well as to provide a basis for evaluating non-rigid body movement. The eigenvalues of the inertia tensor remain invariant if the segment is behaving as a rigid body, thereby providing a basis for determining variations for nonrigid body movement. The method was tested in a simulation model where systematic and random errors were introduced into a fixed cluster of points. The simulation demonstrated that the error due to nonrigid body movement could be substantially reduced. The method was also evaluated in a group of ten normal subjects during walking. The results for knee rotation and translation obtained from the point cluster method compared favorably to results previously obtained from normal subjects with intra-cortical pins placed into the femur and tibia. The resulting methodology described in this paper provides a unique approach to the measurement of in vivo motion using skin-based marker systems.

Correcting for deformation in skin-based marker systems

A new technique is described that reduces error due to skin movement artifact in the opto-electronic measurement of in vivo skeletal motion. This work builds on a previously described point cluster technique marker set and estimation algorithm by extending the transformation equations to the general deformation case using a set of activity-dependent deformation models. Skin deformation during activities of daily living are modeled as consisting of a functional form defined over the observation interval (the deformation model) plus additive noise (modeling error). The method is described as an interval deformation technique. The method was tested using simulation trials with systematic and random components of deformation error introduced into marker position vectors. The technique was found to substantially outperform methods that require rigid-body assumptions. The method was tested in vivo on a patient fitted with an external fixation device (Ilizarov). Simultaneous measurements from markers placed on the Ilizarov device (fixed to bone) were compared to measurements derived from skin-based markers. The interval deformation technique reduced the errors in limb segment pose estimate by 33 and 25% compared to the classic rigid-body technique for position and orientation, respectively. This newly developed method has demonstrated that by accounting for the changing shape of the limb segment, a substantial improvement in the estimates of in vivo skeletal movement can be achieved.

Tracking and modeling non-rigid objects with rank constraints

This paper presents a novel solution for flow-based tracking and 3D reconstruction of deforming objects in monocular image sequences. A non-rigid 3D object undergoing rotation and deformation can be effectively approximated using a linear combination of 3D basis shapes. This puts a bound on the rank of the tracking matrix. The rank constraint is used to achieve robust and precise low-level optical flow estimation without prior knowledge of the 3D shape of the object. The bound on the rank is also exploited to handle occlusion at the tracking level leading to the possibility of recovering the complete trajectories of occluded/disoccluded points. Following the same low-rank principle, the resulting flow matrix can be factored to get the 3D pose, configuration coefficients, and 3D basis shapes. The flow matrix is factored in an iterative manner, looping between solving for pose, configuration, and basis shapes. The flow-based tracking is applied to several video sequences and provides the input to the 3D non-rigid reconstruction task. Additional results on synthetic data and comparisons to ground truth complete the experiments.

Studies of human locomotion: past, present and future

The study of human locomotion and its applications are examined from a historical viewpoint. Several critical steps in the advancement of the discipline are considered in the context of addressing a particular need to answer fundamental questions regarding the process of human locomotion. In addition, changes in the methods of observation are discussed in terms of the advancement of the field. As an example, the application of a newly developed point cluster technique to reduce the artifact due to skin movement is described. The method was applied to a study of patients with anterior cruciate ligament (ACL) deficient knees. The results demonstrate that patients with ACL-deficient knees have significantly greater than normal anterior-posterior displacement of the femur relative to the tibia during walking. Many of the advancements in the tools for observation and interpretation have been driven by new demands on our fundamental knowledge. Future advancements in the study of human locomotion will likely be motivated by new treatment modalities that require an in depth understanding of the subtle complexities of human locomotion. Future directions are discussed in the context of new methods for reducing errors associated with skin movement combined with information obtained from other imaging methods, such as magnetic resonance imaging.

Mechanical loads at the knee joint during deep flexion

There is a lack of fundamental information on the knee biomechanics in deep flexion beyond 90°. In this study, mechanical loads during activities requiring deep flexion were quantified on normal knees from 19 subjects, and compared with those in walking and stair climbing. The deep flexion activities generate larger net quadriceps moments (6.9–13.5% body weight into height) and net posterior forces (58.3–67.8% body weight) than routine ambulatory activities. Moreover, the peak net moments and the net posterior forces were generated between 90° and 150° of flexion.

Most favorable camera configuration for a shape-from-silhouette markerless motion capture system for biomechanical analysis

The most common methods for accurate capture of three-dimensional human motion require a laboratory environment and the attachment of markers or fixtures to the body segments. These laboratory conditions can cause unknown experimental artifacts. Thus our understanding of normal and pathological human movement would be enhanced by a method that allows capture of human movement without the constraint of markers or fixtures placed on the body. Markerless methods are not widely available because the accurate capture of human movement without markers is technically challenging. A reported method of constructing a bodys visual hull using shape-from-silhouette (SFS) offers an attractive approach. However, to date the influence of camera placement and number of cameras on construction of visual hulls for biomechanical analysis is largely unknown. The purpose of this study was to evaluate the accuracy of SFS construction of a human form for biomechanical analysis dependent on camera placement and number of cameras. Visual hull construction was sensitive to camera placement and the subjects pose. Uniform camera distributions such as circular and hemispherical camera arrangements provided most favorable results. Setups with less than 8 cameras yielded largely inaccurate visual hull constructions and great fluctuations for different poses and positions across a viewing volume, while setups with 16 and more cameras provided good volume estimations and consistent results for different poses and positions across the viewing volume.