Multi-set canonical correlation analysis for 3D abnormal gait behaviour recognition based on virtual sample generation

Small sample dataset and two-dimensional (2D) approach are challenges to vision-based abnormal gait behaviour recognition (AGBR). The lack of three-dimensional (3D) structure of the human body causes 2D based methods to be limited in abnormal gait virtual sample generation (VSG). In this paper, 3D AGBR based on VSG and multi-set canonical correlation analysis (3D-AGRBMCCA) is proposed. First, the unstructured point cloud data of gait are obtained by using a structured light sensor. A 3D parametric body model is then deformed to fit the point cloud data, both in shape and posture. The features of point cloud data are then converted to a high-level structured representation of the body. The parametric body model is used for VSG based on the estimated body pose and shape data. Symmetry virtual samples, pose-perturbation virtual samples and various body-shape virtual samples with multi-views are generated to extend the training samples. The spatial-temporal features of the abnormal gait behaviour from different views, body pose and shape parameters are then extracted by convolutional neural network based Long Short-Term Memory model network. These are projected onto a uniform pattern space using deep learning based multi-set canonical correlation analysis. Experiments on four publicly available datasets show the proposed system performs well under various conditions

Multi-level personalization of neuromusculoskeletal models to estimate physiologically plausible knee joint contact forces in children

Neuromusculoskeletal models are a powerful tool to investigate the internal biomechanics of an individual. However, commonly used neuromusculoskeletal models are generated via linear scaling of generic templates derived from elderly adult anatomies and poorly represent a child, let alone children with a neuromuscular disorder whose musculoskeletal structures and muscle activation patterns are profoundly altered. Model personalization can capture abnormalities and appropriately describe the underlying (altered) biomechanics of an individual. In this work, we explored the effect of six different levels of neuromusculoskeletal model personalization on estimates of muscle forces and knee joint contact forces to tease out the importance of model personalization for normal and abnormal musculoskeletal structures and muscle activation patterns. For six children, with and without cerebral palsy, generic scaled models were developed and progressively personalized by (1) tuning and calibrating musculotendon units' parameters, (2) implementing an electromyogram-assisted approach to synthesize muscle activations, and (3) replacing generic anatomies with image-based bony geometries, and physiologically and physically plausible muscle kinematics. Biomechanical simulations of gait were performed in the OpenSim and CEINMS software on ten overground walking trials per participant. A mixed-ANOVA test, with Bonferroni corrections, was conducted to compare all models' estimates. The model with the highest level of personalization produced the most physiologically plausible estimates. Model personalization is crucial to produce physiologically plausible estimates of internal biomechanical quantities. In particular, personalization of musculoskeletal anatomy and muscle activation patterns had the largest effect overall. Increased research efforts are needed to ease the creation of personalized neuromusculoskeletal models

A multi-scale modelling framework combining musculoskeletal rigid-body simulations with adaptive finite element analyses, to evaluate the impact of femoral geometry on hip joint contact forces and femoral bone growth

Multi-scale simulations, combining muscle and joint contact force (JCF) from musculoskeletal simulations with adaptive mechanobiological finite element analysis, allow to estimate musculoskeletal loading and predict femoral growth in children. Generic linearly scaled musculoskeletal models are commonly used. This approach, however, neglects subject- and age-specific musculoskeletal geometry, e.g. femoral neck-shaft angle (NSA) and anteversion angle (AVA). This study aimed to evaluate the impact of proximal femoral geometry, i.e. altered NSA and AVA, on hip JCF and femoral growth simulations. Musculoskeletal models with NSA ranging from 120° to 150° and AVA ranging from 20° to 50° were created and used to calculate muscle and hip JCF based on the gait analysis data of a typically developing child. A finite element model of a paediatric femur was created from magnetic resonance images. The finite element model was morphed to the geometries of the different musculoskeletal models and used for mechanobiological finite element analysis to predict femoral growth trends. Our findings showed that hip JCF increase with increasing NSA and AVA. Furthermore, the orientation of the hip JCF followed the orientation of the femoral neck axis. Consequently, the osteogenic index, which is a function of cartilage stresses and defines the growth rate, barely changed with altered NSA and AVA. Nevertheless, growth predictions were sensitive to the femoral geometry due to changes in the predicted growth directions. Altered NSA had a bigger impact on the growth results than altered AVA. Growth simulations based on mechanobiological principles were in agreement with reported changes in paediatric populations

Biomechanical risk factors and reduced bone health in lower limb amputees

Bone constantly adapts to its surroundings through the formation and resorption of material, controlled by bone modelling and remodelling. Strains produced by mechanical loading are one factor that drive these processes and thus determine bone health. Lower limb amputees (LLA) adopt an asymmetrical movement pattern to compensate for the loss of a limb, resulting in a change in mechanical loading and subsequently a degradation in bone health. The aetiology of the majority of amputations is vascular diseases, which affect bone health. Therefore, it is not clear whether the asymmetrical loading, or comorbidities cause the degradation in bone health in LLA. Finite element models (FEM) are used to generate strain plots and predict the bone's response to mechanical loading. To understand the relationship between the degradation in bone health and asymmetrical loads in LLAs the asymmetrical loads can be applied to a healthy bone using FEMs, or simulated within a healthy population using restrictive devices. Therefore, the overall aim was to investigate the relationship between asymmetrical loading, as observed in LLA’s, and bone health, through the use of semi-subject specific FEMs and restrictive lower limb devices. Study one established a novel image processing method to convert peripheral quantative computed tomography (pQCT) scan images into binary and segment the tibia. The outer perimeter of the tibia was identified and sectioned to produce landmarks. The outer geometry landmarks were used to morph a base FEM, constructed from open source scan images to create semi-subject tibia FEM. Study two applied subject-specific joint reaction and muscle forces to the semi-subject tibia FEM. The strain plots output from Study two were validated against longitudinal geometrical changes from Study three. Study three, used 3D motion capture, pQCT and dual energy x-ray absorptiometry (DXA) to investigate gait and tibial geometry within a lower limb amputee and able-bodied population across twelve months. The coefficient of variation (CV) for able bodied subjects was less than 10% for ground reaction force (GRF) in level walking and less than 4% for bone total area. Study four, used a rigid foot orthosis and a trans-femoral prosthesis, to restrict able-bodied gait. Results showed participants walked significantly slower (p<0.01) in the restricted conditions, with a longer non-restricted step length (p<0.001). The loading rate and maximum GRF were higher in the non-restricted limb (p<0.05). Larger knee adductor moments were shown in the un-restricted leg in the trans-tibial condition (p<0.05). This thesis presents a novel method of constructing semi-subject specific FEMs from pQCT scans. This can be used to further investigate the link between asymmetrical loading and bone health in LLA's and other populations with asymmetrical gait. The use of restrictive devices allow investigation into LLA's specifically, without the interference of prosthetic variability, or comorbidities

Brain Tumour Classification Using Deep Features from Structural MRI

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