DESIGN ITERATIONS AND MATERIAL SELECTION
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After defining the objectives and constraints for our hip implant design, we brainstormed ways in which we could enhance the patient’s bone mass density. This led us to implement the following design modifications:
Consequently, we brainstormed the materials for each of the components that would maximize bone osseointegration and decided on:
Porous Tantalum
Zirconia Toughened Alumina
High Crosslinked Polyethylene
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Figure 1: Initial sketch of hip implant prototype upon careful consideration of the most beneficial changes to the original design.
Figure 2: Initial modeling sketch of the femoral stem to map out the measurements for the final design, highlighting key dimensions.
SOLID MODELLING SUBTEAM
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Taking into account the initial sketch of the hip implant produced during the brainstorming session as well as our patient’s hip morphology, we took the measurements of largest component of our design, the femoral stem (Figure 2).
Using those dimensions, we modelled the hip implant on Autodesk Inventor by creating 2D sketches and using 3D modelling tools, making sure to incorporate the unique components of our design such as the lateral flare and the double liner.
Finally, we constrained all the components of our hip implant together in an assembly and applied different appearances to represent the varied materials used (Figure 3).
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Figure 3: Final assembly of the hip implant with the texture of each material being accurately represented.
Figure 4: Initial flowchart of Python program.
COMPUTING SUBTEAM
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We began by creating a program flow diagram (Figure 4) to outline all major components and functions of our code. This helped us visualize how data would move from the sensor through the stress calculations and into the final graphical output.
We developed a Python function to continually read incoming data from the load cell sensor, which was mounted on a 3D-printed model of the hip implant. This function retrieved the sensor’s measured values and updated variables such as \text{sensor_val} and mths_postop to track how many months post-surgery were being simulated.
After acquiring the sensor data, we implemented separate functions to calculate the axial compressive load acting on the femoral head, as well as the resultant tensile stresses in both the implant stem and the outer femoral diaphysis.
We used Python’s matplotlib library to generate a graphical representation of the data. Our plot displayed both the resultant tensile stress in bone and the ultimate tensile strength as functions of time, measured in years post-surgery.
The code was tested out using a Raspberry Pi to ensure the program could perform the above calculations
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Administrative Responsibilities: Administrator
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Solid Modeling and Assembly of Hip Implant:
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Material Selection:
Figure 5: Updated Gantt chart to represent time allocated to each team deliverable.
Figure 6: Previous design for the inner acetabular lining.
Figure 7: Previous design for the femoral head and stem.