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◆ Journal of Medical Devices2026-06-22· Stability (learning theory)

Analyzing the Sensitivity, Reliability, and Classification Accuracy of Vibration-Based Metrics for Stability Assessment of Percutaneous Osseointegrated Transfemoral Implants

Mostafa Mohamed, Éric Beaudry, Dylan Brenneis, Jacqueline Hebert, Lindsey Westover

原始摘要(英文原文)· Original abstract
Abstract Vibration methods noninvasively assess the stability of percutaneous osseointegrated implants by correlating natural frequencies with the condition of the bone–implant interface (BII). However, these frequencies are also sensitive to implant system geometry, limiting their use as absolute stability metrics across patients. A previously proposed method uses a one-dimensional (1D) finite element (FE) model to estimate BII stiffness (k), reducing the influence of the geometry on stability assessment. This study extends the 1D model to incorporate variability in stem length and diameter, adapter length, and connector presence, and evaluates the accuracy and reliability of BII stiffness estimation (using the model) relative to traditional frequency-based analysis. A tapered element formulation was introduced to better represent components with nonuniform cross sections. Synthetic clinical signals were generated using a three-dimensional (3D) FE model across 48 scenarios involving variations in BII stiffness, geometry, and damping. The 1D model predicted k values of 3.58±0.36 × 106, 2.96±0.25 × 108, and 1.97±0.26 × 109 N/m for the LOW, INTERMEDIATE, and HIGH BII conditions, respectively. Statistical analysis confirmed that k and the first mode frequency (f1) differentiate between BII groups, while the second mode frequency (f2) did not. Unlike k, f1 exhibited a monotonically increasing coefficient of variation with respect to the BII condition, indicating that its reliability decreases for stiffer configurations and that accounting for geometry is a nontrivial scaling matter. Classification accuracy further supported this: 100% for k, 83% for f1, and 17% for f2. Clinically, misclassifications can lead to incorrect diagnosis of BII condition. These results support stiffness prediction via the 1D FE model as a clinically viable tool for implant stability assessment.
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Analyzing the Sensitivity, Reliability, and Classification Accuracy of Vibration-Based Metrics for Stability Assessment of Percutaneous Osseointegrated Transfemoral Implants — 科研速览 Science Skim