Vidhya sundhararaj 2115580 Supervisor Prof Mark Taylor.

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Presentation transcript:

Vidhya sundhararaj Supervisor Prof Mark Taylor

 Population based studies are important for implant study, risk assessment for fracture, pre-clinical studies.  Modelling of single femur or limited number of femur excludes inter-patient variability and extrapolation to population makes less sensible. Also creating multiple models is time consuming.  Statistical modelling overcomes this issue of model generation.

To statistically model femur that represents maximum variation in femur population in terms of bone geometry, material property and forces and analysing if force can predict geometry and material property.

1 PCA on Forces 2 PCA on simple geometry 3 PCA on registered geometry 5 PCA with Density 1 Regression on force and simple geometry 2 Regression on force and registered geometry 3 Regression on force and density 4 PCA on surface nodes

 A data reduction method that accounts for most of the variation in the original data. The obtained variables are Called principal components & are uncorrelated to each other.

Time for stance was obtained from musculoskeletal models in OpenSim. Muscolo skeletal models developed by Saulo martelli

 26 muscle forces On femur and hip joint Forces.

9 modes

 Surface matching – deforms the baseline surface to match the given target surface. Volume morphing- creates the internal mesh points based on surface nodes.

6 modes modes

9 modes

 Analysis was performed on force and shape data to know if shape can predict force.  Scatter plots of force and shape

 Regression – a measure of relationship between variable. Has independent variable as predictors and dependent variable as outcome or response variable.  Multiple regression analysis – more than one predictor to predict outcome.  Stepwise regression – shows significant variables that can predict outcome.

X1- Head radius X2- neck major radius X3- neck minor radius y- mean peak forces Fx

Regstat function – performs multiple regression by fitting model to the data. ‘linear‘ - Includes constant and linear terms (default). 'interaction‘-Includes constant, linear, and cross product terms. Mode 1 force represented by shape modes Mode 2 force represented by shape modes

Interaction model Mode 1 of force Mode 2 of force

MODE 1 FORCE REPRESENTED BY SHAPE MODES MODE 2 FORCE REPRESENTED BY SHAPE MODES

TERMS ADDED TERMS REMOVED

FOR FORCE

 Interpretation of force and shape modes  Volume morphing.  Density extraction from CT scans and assigning it to meshes.  PCA and Regression analysis

Questions