Comprehensive non-dimensional normalization of gait data

Normalizing clinical gait analysis data is required to remove variability due to physical characteristics such as leg length and weight. This is particularly important for children where both are associated with age. In most clinical centres conventional normalization (by mass only) is used whereas there is a stronger biomechanical argument for non-dimensional normalization. This study used data from 82 typically developing children to compare how the two schemes performed over a wide range of temporal-spatial and kinetic parameters by calculating the coefficients of determination with leg length, weight and height. 81% of the conventionally normalized parameters had a coefficient of determination above the threshold for a statistical association (p < 0.05) compared to 23% of those normalized nondimensionally. All the conventionally normalized parameters exceeding this threshold showed a reduced association with non-dimensional normalization. In conclusion, non-dimensional normalization is more effective that conventional normalization in reducing the effects of height, weight and age in a comprehensive range of temporal-spatial and kinetic parameters

The comparison of normative reference data from different gait analysis services

Comparison of normative data between gait analysis services offers the potential to harmonise data collection protocols. This paper presents a method for such a comparison based on an assumption that the root mean square difference from the inter-service mean is a reflection of systematic differences in protocols and that the average standard deviation includes a component attributable to within-centre measurement variability. Substantial normative datasets from two highly respected clinical services were compared. The RMS difference for the difference from the inter-centre mean was less than 1.7° for all kinematic variables apart from hip rotation (2.9°) and foot progression (2.1°), less than 0.1Nm/kg for all joint moments and than 0.21W/kg for all joint powers. The two centres showed very similar normative standard deviations. The data demonstrates a high degree of consistency between data from two highly regarded gait analysis services and establishes a baseline against which other services can assess their performance. An electronic appendix includes data to facilitate this comparison

Exploratory Investigation of Head Stability in Children with Cerebral Palsy and Typically Developing Children during a Targeted Stepping Task

Children with cerebral palsy (CP) exhibit head instability during simple overground walking, which may comprise sensory input and reduce stepping accuracy. Investigations of head stability during more challenging tasks, where fall risk may be increased, are limited. This study explored differences in head stability between ambulatory children with hemiplegic CP (N = 9) and diplegia (N = 9) (GMFCS I and II) and typically developing (TD) children (N = 8) during a targeted stepping task. All children completed five trials stepping into two successive rectangular floor-based targets whilst walking along an 8 m walkway. Three-dimensional motion capture enabled calculation of head stability and foot placement within and before each target. A two-way mixed-design ANOVA compared differences between all groups and target approach. Children with diplegic CP showed greater sagittal, frontal, and resultant head-to-laboratory and head-to-trunk head instability compared to children with hemiplegic CP and TD children. Anteroposterior foot placement error was significantly greater in children with hemiplegic CP (8.5 ± 5.0 cm) compared to TD children (3.8 ± 1.5 cm). Group differences in head instability were not consistent with group differences in foot placement error. To better understand how head instability might affect fall risk in children with CP, more challenging environments should be tested in future

Comparison of Theia3D and the conventional gait model in typically developing children and adults in a clinical gait laboratory

Marker-based motion capture is the clinical standard for gait analysis, requiring precise marker placement on anatomical landmarks. This process is time-consuming and prone to human error. Theia3D, a markerless system using machine learning and neural networks, tracks features from 2D video to produce 3D motion analysis, but has yet to be clinically validated, and its use for children is minimal. This study compared markerless system (Theia3D) joint tracking with currently the most widely-used marker-based model in clinical gait analysis (Conventional Gait Model, CGM1.1) in typically developing children and adults. Twenty-three children and 34 adults underwent gait assessments at Alder Hey Children's Hospital, where data from both systems were collected synchronously. Kinematics, kinetics and segment lengths were calculated from both systems. Model differences were quantified using pairwise root mean square deviations (RMSD) during phases that were statistically significantly different as determined by statistical parametric mapping. Segment length differences produced by each model were assessed by mean difference, standard error of the mean and minimal detectable change. Significant differences were observed across the gait cycle in all but one joint levels and planes, with RMSDs up to 8.5° in the sagittal plane, 5.3° in the frontal plane and 10.2° in the transverse plane. Theia3D produced larger peak knee moments in the sagittal and frontal plane compared to the CGM1.1 model and produced shorter segment lengths. This study shows the potential of the developing Theia3D's software in clinical gait analysis with children and adults but emphasises the need for further investigations across populations

The conventional gait model - success and limitations

The Conventional Gait Model (CGM) is a generic name for a family of closely related and very widely used biomechanical models for gait analysis. After describing its history, the core attributes of the model are described followed by evaluation of its strengths and weaknesses. An analysis of the current and future requirements for practical biomechanical models for clinical and other gait analysis purposes which have been rigorously calibrated suggests that the CGM is better suited for this purpose than any other currently available model. Modifications are required, however, and a number are proposed

Transcriptional Silencing of the Wnt-Antagonist DKK1 by Promoter Methylation Is Associated with Enhanced Wnt Signaling in Advanced Multiple Myeloma

The Wnt/β-catenin pathway plays a crucial role in the pathogenesis of various human cancers. In multiple myeloma (MM), aberrant auto-and/or paracrine activation of canonical Wnt signaling promotes proliferation and dissemination, while overexpression of the Wnt inhibitor Dickkopf1 (DKK1) by MM cells contributes to osteolytic bone disease by inhibiting osteoblast differentiation. Since DKK1 itself is a target of TCF/β-catenin mediated transcription, these findings suggest that DKK1 is part of a negative feedback loop in MM and may act as a tumor suppressor. In line with this hypothesis, we show here that DKK1 expression is low or undetectable in a subset of patients with advanced MM as well as in MM cell lines. This absence of DKK1 is correlated with enhanced Wnt pathway activation, evidenced by nuclear accumulation of β-catenin, which in turn can be antagonized by restoring DKK1 expression. Analysis of the DKK1 promoter revealed CpG island methylation in several MM cell lines as well as in MM cells from patients with advanced MM. Moreover, demethylation of the DKK1 promoter restores DKK1 expression, which results in inhibition of β-catenin/TCF-mediated gene transcription in MM lines. Taken together, our data identify aberrant methylation of the DKK1 promoter as a cause of DKK1 silencing in advanced stage MM, which may play an important role in the progression of MM by unleashing Wnt signaling