Inicio  /  Applied Sciences  /  Vol: 12 Par: 7 (2022)  /  Artículo
ARTÍCULO
TITULO

Computational Wear Prediction of TKR with Flatback Deformity during Gait

Hye Kyeong Lee    
Sung Min Kim and Hong Seok Lim    

Resumen

Loss of lumbar lordosis in flatback patients leads to changes in the walking mechanism like knee flexion. Such variations in flatback patients are predicted to alter the characteristics of total knee replacement (TKR) contact, so their TKR will show different wear characteristics with a normal gait. However, the relevant study is limited to predicting the wear depth of TKR for normal gait mechanisms or collecting and analyzing kinematic data on flatback gait mechanisms. The objective of this study was to compare wear in TKR of flatback patients with people without flatback syndrome. The main difference between the normal gait mechanism and the flat back gait mechanism is the knee flexion remain section and the tendency to change the vertical force acting on the knee. Thus, in this paper, A finite element-based computational wear simulation for the gait cycle using kinematic data for normal gait and flat gait were performed, and substituting the derived contact pressure and slip distance into the Archard formula, a proven wear model, wear depth was predicted. The FE analysis results show that the wear volume in flatback patients is greater. The results obtained can provide guidance on the TKR design to minimize wear on the knee implant for flatback patients.

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