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Prediction of Postoperative Outcomes After TKA Using Instrumented Insoles and DNN
Sponsor: Yonsei University
Summary
This multicenter prospective observational study aims to evaluate whether preoperative clinical variables and wearable sensor-derived gait features can predict postoperative improvement after total knee arthroplasty (TKA). Participants will undergo standardized gait assessments using instrumented insoles and complete validated patient-reported outcome measures (PROMs). Prediction models including linear regression, random forest, and deep neural networks will be applied and their performance compared.
Official title: Prediction of Patient-reported Outcome Measure and Performance-based Measure After Total Knee Arthroplasty Using Instrumented Insoles and Deep Neural Networks
Key Details
Gender
All
Age Range
19 Years - Any
Study Type
OBSERVATIONAL
Enrollment
200
Start Date
2021-06-01
Completion Date
2026-12-31
Last Updated
2026-01-26
Healthy Volunteers
No
Interventions
Instrumented Insole Gait Assessment
Participants undergo gait assessment using an instrumented insole system during the Timed Up and Go Test. The device is used solely for data collection and does not provide therapeutic intervention.
Locations (1)
Yongin Severance Hospital
Yongin-si, Gyeonggi-do, South Korea