56 research outputs found

    <i>Heatmap</i> showing the Z-scores (standardized measure of the distance to healthy average value) of the 12 most important gait parameters to classify cycles into gait patterns according to random forest models.

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    <p>Cycles are represented in columns and ordered following the dendrogram shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192345#pone.0192345.g001" target="_blank">Fig 1</a>. Gait parameters are shown in rows and ordered according to the relationships between relationships with each other (dendrogram on the left). The Z-scores are represented following the colour legend in the top left corner.</p

    Violin plots of the four most important gait parameters to distinguish between patients with GMFCS I and GMFCS II-III according to random forest model.

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    <p>The vertical axis represents the value of the gait parameters studied. The shape of the violin plot depends on the distribution of the values of the gait parameters in each group. Grey violin plots show data distribution from healthy children, the green ones data distribution from children with HSP and GMFCS I and the red ones distribution from children with HSP and GMFCS II-III. In each violin plot, the white point represents the median value of each group; the vertical black line represents the range.</p

    Distribution of sagittal patterns in left and right cycles and clinical features of each patient.

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    <p>Patients were ordered according to the type of gait patterns they use (left) and clinical features were represented with colour scales (right). Notice that clinical features are partially related to the gait phenotype.</p

    Importance of gait parameters for the random forest model to distinguish between cycles from HSP sagittal Pattern I and healthy controls.

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    <p>It is measured by Breiman-Cutler permutation variable importance (VIMP). <i>Stance time</i> and <i>time to peak knee flexion in stance</i> are the most important parameters to distinguish patients with sagittal Pattern I from healthy controls.</p

    Gait phenotypes in paediatric hereditary spastic paraplegia revealed by dynamic time warping analysis and random forests - Fig 1

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    <p>A) Dendrogram obtained from hierarchical clustering analysis of gait cycles of HSP patients. The vertical axis represents the distance DTW. A vertical line that reaches the base indicates each cycle. Horizontal lines that interconnect the vertical ones indicate DTW distances between the cycles. The higher the horizontal lines joining two cycles, the less similar they are. The lower bar indicates whether the classified cycle is from the right limb (red) or the left (green). Six clusters and an “outlier” (pink cycle) are detected. The majority of cycles are grouped within the red and the blue cluster. B) The <i>heatmap</i> presents Z-scores (standardized comparison to healthy average value) of the spatio-temporal parameters (rows) of each HSP cycle (columns). Green colour indicates a higher spatio-temporal value in the cycle than in healthy children and red, a lower value. The more intense the colour of the square, the further the value of the cycle is from healthy controls. In comparison to healthy controls, red, blue and brown patterns represent less impaired spatio-temporal performance; while orange, green and part of the cycles from the purple pattern show more altered values.</p

    Cumulated kinematic plots of five joints grouped according to seven sagittal patterns yielded by dendrogram in Fig 1.

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    <p>Each column represents a pattern and each row, a joint. The x-axis of each graph corresponds to the percentage of gait cycle. The y-axis represents the joint range in degrees (zero is the neutral position, positive values indicate flexion and negative values, extension). The healthy children’s cycles are depicted in grey lines, their average healthy patterns in black, and the overall healthy average is shown with a thick black line. Patterns I and II (red and blue, respectively) are the most similar to normal. The outlier (pink) corresponds to an “outlier” cycle.</p
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