Estimation of discretization errors in contact pressure measurements.

Area of Science:

• Biomechanics
• Biomedical Engineering
• Medical Device Technology

Background:

• Contact pressure measurement in total knee replacements (TKR) often uses discrete sensors like the Tekscan K-Scan.
• Existing methods lack ways to predict discretization errors in contact force, peak pressure, average pressure, and contact area, hindering accuracy assessment.

Purpose of the Study:

• To identify and validate a method for predicting sensor discretization errors in TKR contact pressure measurements.
• To establish a relationship between a novel non-dimensional area variable and measurement inaccuracies.

Main Methods:

• Simulated discrete pressure sensors under Hertzian and uniform pressure distributions with varying element sizes, contact ellipse aspect ratios, and locations.
• Introduced a non-dimensional area variable (perimeter elements to total pressure elements ratio).
• Validated simulations using K-Scan sensor data from four TKR designs.

Main Results:

• A strong power law relationship (r(2)>0.89) was found between worst-case discretization errors and the non-dimensional area variable.
• Simulations predicted errors of 1-4% for contact force/peak pressure and 3-9% for average pressure/contact area in TKR experiments.
• These errors are comparable to those from sensor insertion or pressure-sensitive film truncation.

Conclusions:

• The proposed non-dimensional area variable effectively predicts discretization errors in discrete pressure sensors for TKR.
• The study provides a simple power law regression to estimate measurement accuracy for elliptical contact patches.
• This offers a valuable tool for evaluating the reliability of TKR contact pressure data.