Biomechanical Study of a Tricompartmental Unloader Brace for Patellofemoral or Multicompartment Knee Osteoarthritis.

Objective: Off-loader knee braces have traditionally focused on redistributing loads away from either the medial or lateral tibiofemoral (TF) compartments. In this article, we study the potential of a novel "tricompartment unloader" (TCU) knee brace intended to simultaneously unload both the patellofemoral (PF) and TF joints during knee flexion. Three different models of the TCU brace are evaluated for their potential to unload the knee joint. Methods: A sagittal plane model of the knee was used to compute PF and TF contact forces, patellar and quadriceps tendon forces, and forces in the anterior and posterior cruciate ligaments during a deep knee bend (DKB) test using motion analysis data from eight participants. Forces were computed for the observed (no brace) and simulated braced conditions. A sensitivity and validity analysis was conducted to determine the valid output range for the model, and Statistical Parameter Mapping was used to quantify the effectual region of the different TCU brace models. Results: PF and TF joint force calculations were valid between ~0 and 100 degrees of flexion. All three simulated brace models significantly (p < 0.001) reduced predicted knee joint loads (by 30-50%) across all structures, at knee flexion angles >~30 degrees during DKB. Conclusions: The TCU brace is predicted to reduce PF and TF knee joint contact loads during weight-bearing activity requiring knee flexion angles between 30 and 100 degrees; this effect may be clinically beneficial for pain reduction or rehabilitation from common knee injuries or joint disorders. Future work is needed to assess the range of possible clinical and prophylactic benefits of the TCU brace.

Comparison of two normative paediatric gait databases.

The availability of age-matched normative data is an essential component of clinical gait analyses. Comparison of normative gait databases is difficult due to the high-dimensionality and temporal nature of the various gait waveforms. The purpose of this study was to provide a method of comparing the sagittal joint angle data between two normative databases. We compared a modern gait database to the historical San Diego database using statistical classifiers developed by Tingley et al. (2002). Gait data were recorded from 60 children aged 1-13 years. A six-camera Vicon 512 motion analysis system and two force plates were utilized to obtain temporal-spatial, kinematic, and kinetic parameters during walking. Differences between the two normative data sets were explored using the classifier index scores, and the mean and covariance structure of the joint angle data from each lab. Significant differences in sagittal angle data between the two databases were identified and attributed to technological advances and data processing techniques (data smoothing, sampling, and joint angle approximations). This work provides a simple method of database comparison using trainable statistical classifiers.

An extended index to quantify normality of gait in children.

Clinical gait analysis aims to quantify and assess the mechanics of walking and identify deviations from 'normal' movement patterns. To facilitate the use of clinical equipment, protocols are required to process data and produce a few meaningful summary measurements which can, in turn, be used to flag gait abnormalities. Earlier work produced a one-dimensional index of gait, calculated from sagittal hip, knee and ankle rotation angle patterns. The objective of this study was to extend the original index, incorporating kinematic and kinetic data from multiple planes, while allowing for correlations between component measures. A one-dimensional index of normal gait was developed, based on normative gait data (N=45 children, aged 3-13 years). The new one-dimensional index was calculated using correlation patterns between seven component indices, each of which has diagnostic interpretation. The effectiveness of the new index was tested using immature normative data (N=14) and hypotonic data (N=10). Approximately 85% of immature normative children and 100% of hypotonic children were classified as either unusual or extreme by the one-dimensional index. These data reduction protocols improve objective gait analyses in the clinical setting.

A comparison of kinetic gait parameters for 3-13 year olds.

BACKGROUND: Normative gait data is essential for diagnosing and treating abnormal gait patterns. The examination of the onset of adult-like kinetic gait patterns in children has generated inconsistent results. The purpose of this study was to identify age-related differences in kinematic and kinetic gait parameters across children aged 3-13 years old. METHODS: A motion capture system and three force plates were employed to compute sagittal joint angles and joint kinetics during walking and compare results between children aged 3-4 years (n=13), 5-6 years (n=10), 7-8 years (n=12), and 9-13 years (n=12). Anthropometric data was estimated using a mathematical model (elliptical cylinder method). Peak flexion and extension joint angles and moments, and peak concentric and eccentric joint powers were analyzed using multivariate analyses of variance. FINDINGS: For most of the variables examined, similar results were obtained across age groups. Reduced peak hip flexion moments and knee extension moments were observed in the 3-4 year olds compared to the oldest group of walkers. Compared to the 9-13 year olds, reduced ankle joint moments and power were observed in most age groups. INTERPRETATION: The results suggest that adult-like kinetic patterns for the hip and knee were attained by 5 years of age. However, for the ankle joint, adult-like patterns are not achieved until nine years of age or older. These findings stress the importance of using age-matched normative data for clinical gait analysis.

Gait analysis.

Gait analysis, or the study of locomotion, has changed dramatically over the last few decades. Advances in computer technology and data analysis techniques have contributed greatly to the progress of this field. Gait analysis has become a valuable tool in the clinical setting. The ability to objectively quantify motion is essential to our understanding of normal and abnormal movement patterns and the evaluation of treatment effectiveness. This paper will discuss the various experimental and analytical techniques currently used for performing clinical gait analyses at the University of New Brunswick, Fredericton, New Brunswick, Canada.