Knee moment outcomes using inverse dynamics and the cross product function in moderate knee osteoarthritis gait: A comparison study

• Published in: Journal of biomechanics 2018-09, Vol.78, p.150-154
• Main Authors: Rutherford, Derek James, Baker, Matthew
• Format: Article
• Language: English
• Subjects: Arthritis; Biocompatibility; Biomechanical Phenomena; Biomechanics; Center of pressure; Complexity; Computation; Computer applications; Conflicts of interest; Cross Product; Data collection; Data processing; Dynamic models; Dynamics; Exercise Test; Gait; Humans; Inverse dynamics; Joint surgery; Kinematics; Kinetics; Knee; Knee Joint - physiopathology; Knee Osteoarthritis; Methods; Middle Aged; Moment; Osteoarthritis; Osteoarthritis, Knee - physiopathology; Pressure; Rotation; Spheres; Surface markers; Walking; Walking Speed
• ISSN: 0021-9290; 1873-2380
• DOI: 10.1016/j.jbiomech.2018.07.021

Inverse dynamics are the cornerstone of biomechanical assessments to calculate knee moments during walking. In knee osteoarthritis, these outcomes have been used to understand knee pathomechanics, but the complexity of an inverse dynamic model may limit the uptake of joint moments in some clinical and research structures. The objective was to determine whether discrete features of the sagittal and frontal plane knee moments calculated using inverse dynamics compare to knee moments calculated using a cross product function. Knee moments from 74 people with moderate knee osteoarthritis were assessed after ambulating at a self-selected speed on an instrumented dual belt treadmill. Standardized procedures were used for surface marker placement, gait speed determination and data processing. Net external frontal and sagittal plane knee moments were calculated using inverse dynamics and the three-dimensional position of the knee joint center with respect to the center of pressure was crossed with the three-dimensional ground reaction forces in the cross product function. Correlations were high between outcomes of the moment calculations (r > 0.9) and for peak knee adduction moment, knee adduction moment impulse and difference between peak flexion and extension moments, the cross product function resulted in absolute values less than 10% of those calculated using inverse dynamics in this treadmill walking environment. This computational solution may allow the integration of knee moment calculations to understand knee osteoarthritis gait without data collection or computational complexity.