On the problems of describing joint axis alignment

Kinematics of primate midfoot flexibility

This study describes a unique assessment of primate intrinsic foot joint kinematics based upon bone pin rigid cluster tracking. It challenges the assumption that human evolution resulted in a reduction of midfoot flexibility, which has been identified in other primates as the "midtarsal break." Rigid cluster pins were inserted into the foot bones of human, chimpanzee, baboon, and macaque cadavers. The positions of these bone pins were monitored during a plantarflexion-dorsiflexion movement cycle. Analysis resolved flexion-extension movement patterns and the associated orientation of rotational axes for the talonavicular, calcaneocuboid, and lateral cubometatarsal joints. Results show that midfoot flexibility occurs primarily at the talonavicular and cubometatarsal joints. The rotational magnitudes are roughly similar between humans and chimps. There is also a similarity among evaluated primates in the observed rotations of the lateral cubometatarsal joint, but there was much greater rotation observed for the talonavicular joint, which may serve to differentiate monkeys from the hominines. It appears that the capability for a midtarsal break is present within the human foot. A consideration of the joint axes shows that the medial and lateral joints have opposing orientations, which has been associated with a rigid locking mechanism in the human foot. However, the potential for this same mechanism also appears in the chimpanzee foot. These findings demonstrate a functional similarity within the midfoot of the hominines. Therefore, the kinematic capabilities and restrictions for the skeletal linkages of the human foot may not be as unique as has been previously suggested.

Cross-talk correction method for knee kinematics in gait analysis using principal component analysis (PCA): a new proposal

Background

In 3D gait analysis, the knee joint is usually described by the Eulerian way. It consists in breaking down the motion between the articulating bones of the knee into three rotations around three axes: flexion/extension, abduction/adduction and internal/external rotation. However, the definition of these axes is prone to error, such as the “cross-talk” effect, due to difficult positioning of anatomical landmarks. This paper proposes a correction method, principal component analysis (PCA), based on an objective kinematic criterion for standardization, in order to improve knee joint kinematic analysis.

Methods

The method was applied to the 3D gait data of two different groups (twenty healthy subjects and four with knee osteoarthritis). Then, this method was evaluated with respect to three main criteria: (1) the deletion of knee joint angle cross-talk (2) the reduction of variance in the varus/valgus kinematic profile (3) the posture trial varus/valgus deformation matching the X-ray value for patients with knee osteoarthritis. The effect of the correction method was tested statistically on variabilities and cross-talk during gait.

Results

Cross-talk was lower (p<0.05) after correction (the correlation between the flexion-extension and varus-valgus kinematic profiles being annihilated). Additionally, the variance in the kinematic profile for knee varus/valgus and knee flexion/extension was found to be lower and higher (p<0.05), respectively, after correction for both the left and right side. Moreover, after correction, the posture trial varus/valgus angles were much closer to x-ray grading.

Conclusion

The results show that the PCA correction applied to the knee joint eliminates the cross-talk effect, and does not alter the radiological varus/valgus deformation for patients with knee osteoarthritis. These findings suggest that the proposed correction method produces new rotational axes that better fit true knee motion.

A procedure to refine joint kinematic assessments: Functional Alignment

Functional Alignment is a new method to determine the orientation of a joint's primary rotational axis and the associated movement. It employs three unique concepts. First, data analyses are based upon assessment of spatial positions and not upon movement in a time sequence. Second, analyses are conducted on derived joint rotation matrices instead of tracked markers. This permits reanalysis of published biomechanical results and, therefore, provides a basis for unifying perspectives among different research efforts. Finally, the independent perspectives of the move and base segments require the analysis to use two unique descriptors of the joint axis orientation. These two mathematically necessary descriptors are also shown to be obtainable without reference to the original marker data. The combination of these approaches provides opportunities for additional comparisons of kinematic joint features that have been heretofore underappreciated.

Oppugning the assumptions of spatial averaging of segment and joint orientations

Movement scientists frequently calculate "arithmetic averages" when examining body segment or joint orientations. Such calculations appear routinely, yet are fundamentally flawed. Three-dimensional orientation data are computed as matrices, yet three-ordered Euler/Cardan/Bryant angle parameters are frequently used for interpretation. These parameters are not geometrically independent; thus, the conventional process of averaging each parameter is incorrect. The process of arithmetic averaging also assumes that the distances between data are linear (Euclidean); however, for the orientation data these distances are geodesically curved (Riemannian). Therefore we question (oppugn) whether use of the conventional averaging approach is an appropriate statistic. Fortunately, exact methods of averaging orientation data have been developed which both circumvent the parameterization issue, and explicitly acknowledge the Euclidean or Riemannian distance measures. The details of these matrix-based averaging methods are presented and their theoretical advantages discussed. The Euclidian and Riemannian approaches offer appealing advantages over the conventional technique. With respect to practical biomechanical relevancy, examinations of simulated data suggest that for sets of orientation data possessing characteristics of low dispersion, an isotropic distribution, and less than 30 degrees second and third angle parameters, discrepancies with the conventional approach are less than 1.1 degrees . However, beyond these limits, arithmetic averaging can have substantive non-linear inaccuracies in all three parameterized angles. The biomechanics community is encouraged to recognize that limitations exist with the use of the conventional method of averaging orientations. Investigations requiring more robust spatial averaging over a broader range of orientations may benefit from the use of matrix-based Euclidean or Riemannian calculations.