A Normative Database of Hip and Knee Joint Biomechanics During Dynamic Tasks Using Four Functional Methods With Three Functional Calibration Tasks.

Although predicted hip joint center (HJC) locations are known to vary widely between functional methods, no previous investigation has detailed functional method-dependent hip and knee biomechanics. The purpose of this study was to define a normative database of hip joint biomechanics during dynamic movements based upon functional HJC methods and calibration tasks. Thirty healthy young adults performed arc, star arc, and two-sided calibration tasks. Motion capture and ground reaction forces were collected during walking, running, and single-leg landings (SLLs). Two sphere-fit (geometric and algebraic) and two coordinate transformation techniques were implemented using each calibration (12 total method-calibration combinations). Surprisingly, the geometric fit-two-sided model placed the HJC at the midline of the pelvis and above the iliac spines, and thus was removed from analyses. A database of triplanar hip and knee kinematics and hip moments and powers was constructed using the mean of all subjects for the eleven method-calibration combinations. A nested analysis of variance approach compared calibration [method] peak hip kinematics and kinetics. Most method differences existed between geometric fit and coordinate transformations (58 of 84 total). No arc-star arc differences were found. Thirty-two differences were found between the two-sided and arc/star arc calibrations. This database of functional method based hip and knee biomechanics serves as an important reference point for interstudy comparisons. Overall, this study illustrates that functional HJC method can dramatically impact hip biomechanics and should be explicitly detailed in future work.

Frontal Plane Tibiofemoral Alignment is Strongly Related to Compartmental Knee Joint Contact Forces and Muscle Control Strategies During Stair Ascent.

Static frontal plane tibiofemoral alignment is an important factor in dynamic knee alignment and knee adduction moments (KAMs). However, little is known about the relationship between alignment and compartment contact forces or muscle control strategies. The purpose of this study was to estimate medial (MCF) and lateral (LCF) compartment knee joint contact forces and muscle forces during stair ascent using a musculoskeletal model implementing subject-specific knee alignments. Kinematic and kinetic data from 20 healthy individuals with radiographically confirmed varus or valgus knee alignments were simulated using alignment specific models to predict MCFs and LCFs. Muscle forces were determined using static optimization. Independent samples t-tests compared contact and muscle forces between groups during weight acceptance and during pushoff. The varus group exhibited increased weight acceptance peak MCFs, while the valgus group exhibited increased pushoff peak LCFs. The varus group utilized increased vasti muscle forces during weight acceptance and adductor forces during pushoff. The valgus group utilized increased abductor forces during pushoff. The alignment-dependent contact forces provide evidence of the significance of frontal plane knee alignment in healthy individuals, which may be important in considering future knee joint health. The differing muscle control strategies between alignments detail-specific neuromuscular responses to control frontal plane knee loads.

A normative database of hip and knee joint biomechanics during dynamic tasks using anatomical regression prediction methods.

Many methodologies exist to predict the hip joint center (HJC), of which regression based on anatomical landmarks appear most common. Despite the fact that predicted HJC locations vary depending upon chosen method, inter-study comparisons and inferences about populations are commonly made. The purpose of this study was to create a normative database of hip and knee biomechanics during walking, running, and single leg landings based on five commonly utilized HJC methods to serve as a reference for inter-study comparisons. Secondarily, we devised to provide comparisons of peak knee angles and hip angles, moments, and powers from the five HJC methods. Thirty healthy young adults performed walking, running, and single leg landing tasks at self-selected speeds (walking/running) and at 90% of their maximum jump height (landing). Three-dimensional motion capture and ground reaction forces were collected during all tasks. Five different HJC prediction methods: Bell, Davis, Hara, Harrington, and Greater Trochanter were implemented separately in a 6 degree of freedom model. Predicted HJC locations, direct kinematics, and inverse dynamics were computed for all tasks. Predicted HJC mediolateral, anteroposterior, and superior-inferior locations differed between methods by an average of 1.3, 2.9, and 1.4 cm, respectively. A database was created using the mean of all subjects for all five methods. In addition, one-way ANOVAs were used to compare triplanar peak angles, moments, and powers between the methods. The database of hip and knee biomechanics illustrates (1) variability between methods increases with more dynamic tasks (running/landing vs. walking) and (2) frontal and transverse plane hip and knee biomechanics are more variable between methods. Comparisons between methods found 38 and 16 main effect differences in hip and knee biomechanics, respectively. The Greater Trochanter method provided the most differences compared with other methods, while the Davis method provided the least differences. The database constructed provides an important reference for inter-study comparisons and details the impact of anatomical regression methods for predicting the HJC.