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1. Simulation of total knee arthroplasty in 5° or 7° valgus: A study of gap imbalances and changes in limb and knee alignments from native: SIMULATION OF TOTAL KNEE ARTHROPLASTY IN 5° OR 7° VALGUS

   https://doi.org/10.1002/jor.23492  

   Gu, Yu ; Howell, Stephen M. ; Hull, Maury L. ( September 2017 , Journal of Orthopaedic Research)
2. Using Whole Knee Cartilage Damage Index to Predict Knee Osteoarthritis: A Two-year Longitudinal Study

   https://doi.org/10.1109/bibm.2018.8621530  

   Du, Yaodong ; Shan, Juan ; Almajalid, Rania ; Alon, Tomer ; Zhang, Ming ( December 2018 , IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2018))
3. Closing the Wearable Gap—Part VIII: A Validation Study for a Smart Knee Brace to Capture Knee Joint Kinematics

   https://doi.org/10.3390/biomechanics1010012  

   Turner, Alana J. ; Carroll, Will ; Kodithuwakku Arachchige, Sachini N. ; Saucier, David ; Burch V, Reuben F. ; Ball, John E. ; Smith, Brian K. ; Freeman, Charles E. ; Knight, Adam C. ; Chander, Harish ( June 2021 , Biomechanics)

   Background: Wearable technology is used by clinicians and researchers and play a critical role in biomechanical assessments and rehabilitation. Objective: The purpose of this research is to validate a soft robotic stretch (SRS) sensor embedded in a compression knee brace (smart knee brace) against a motion capture system focusing on knee joint kinematics. Methods: Sixteen participants donned the smart knee brace and completed three separate tasks: non-weight bearing knee flexion/extension, bodyweight air squats, and gait trials. Adjusted R2 for goodness of fit (R2), root mean square error (RMSE), and mean absolute error (MAE) between the SRS sensor and motion capture kinematic data for all three tasks were assessed. Results: For knee flexion/extension: R2 = 0.799, RMSE = 5.470, MAE = 4.560; for bodyweight air squats: R2 = 0.957, RMSE = 8.127, MAE = 6.870; and for gait trials: R2 = 0.565, RMSE = 9.190, MAE = 7.530 were observed. Conclusions: The smart knee brace demonstrated a higher goodness of fit and accuracy during weight-bearing air squats followed by non-weight bearing knee flexion/extension and a lower goodness of fit and accuracy during gait, which can be attributed to the SRS sensor position and orientation, rather than range of motion achieved inmore »each task.« less
4. Knee osteoarthritis severity level classification using whole knee cartilage damage Index and ANN

   https://doi.org/10.1145/3278576.3278585  

   Du, Yaodong ; Shan, Juan ; Almajalid, Rania ; Zhang, Ming ( September 2018 , IEEE Conference on Connected Health: Applications, Systems and Engineering Technologies)
5. Knee Osteoarthritis Severity Level Classification Using Whole Knee Cartilage Damage Index and ANN

   Y. D. Du, J. Shan ( September 2018 , ”, IEEE Conference on Connected Health: Applications, Systems and Engineering Technologies)