Bone Cuts Accuracy of a System for Total Knee Arthroplasty including an Active Robotic Arm
Killian Cosendey, Julien Stanovici, Jaad Mahlouly, Patrick Omoumi, Brigitte M. Jolles, Julien Favre
- 发表年份
- 2021
- 引用次数
- 7
- 访问权限
- 开放获取
摘要
INTRODUCTION: This study aimed to assess the bone cuts accuracy of a system for total knee arthroplasty including an active robotic arm. A second objective was to compare the accuracy among orthopaedic surgeons of different levels of experience. METHODS: Three orthopaedic surgeons cut 10 sawbone knees each. Planned and actual bone cuts were compared using computed tomography. Difference with respect to the planning was expressed as three position and three orientation errors following the anatomical planes. Statistical tests were performed to detect bias and compare surgeons. RESULTS: None of the 30 knees presented an outlier error, meaning an error ≥3 mm or ≥3°. The root-mean-square values of the 12 error types were below 0.8 mm or 0.8°, except for the femoral proximal-distal errors (1.7 mm) and the tibial anterior-posterior errors (1.4 mm). Biases were observed, particularly in femoral proximal-distal and tibial anterior-posterior positions. Median differences between surgeons were all lower than 0.8 mm and 0.5°, with statistically significant differences among surgeons in the femoral proximal-distal errors and the tibial anterior-posterior errors. CONCLUSIONS: The system tested in this study achieved accurate bone cuts independently of the surgeon's level of experience. Biases were observed, suggesting that there might be options to improve the accuracy, particularly in proximal-distal position for the femur and in anterior-posterior position for the tibia.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992