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• W4381430069 abstract "Medial unloader braces represent a primary noninvasive approach for alleviating knee pain. However, conventional valgus unloader braces, while reducing load on the medial compartment, inadvertently increase load on the lateral compartment through rotation from adduction to abduction. This phenomenon significantly elevates the risk of damage to the lateral compartment. To address this issue, we introduce a novel embedded actuation mechanism that unloads the knee using a pioneering computational procedure. By considering the knee osteoarthritis condition, we propose the calculation of the adduction knee angle and cartilage penetration depth as surrogate parameters for assessing knee pain. Accordingly, the newly developed unloader brace redistributes the load by precisely correcting the abduction angle. Additionally, we determine the maximum required torque for effectively tracking the desired abduction angle. Then, the saturated torque through the robust control method is applied in the presence of interaction force uncertainty between the orthosis and the user. A very small femur rotation change (1.7°) from adduction to abduction in the frontal plane is adequate to significantly reduce the medial contact force (around 886 N). The required robust external abduction torque is determined to be 27.6 Nm. The result shows that the novel procedure and brace prevent excessive overloading of the lateral compartment while it unloads the medial compartment sufficiently. This innovative approach offers significant potential for optimizing unloader brace design and enhancing the management of knee osteoarthritis." @default.
• W4381430069 created "2023-06-21" @default.
• W4381430069 creator A5018625582 @default.
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• W4381430069 date "2023-06-19" @default.
• W4381430069 modified "2023-09-26" @default.
• W4381430069 title "Computational Control Strategy for Reducing Medial Compartment Load in Knee Bracing with Embedded Actuator" @default.
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• W4381430069 doi "https://doi.org/10.3390/act12060256" @default.
• W4381430069 hasPublicationYear "2023" @default.
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