RecruitingNCT07367789

Prediction of Postoperative Outcomes After TKA Using Instrumented Insoles and DNN

Prediction of Patient-reported Outcome Measure and Performance-based Measure After Total Knee Arthroplasty Using Instrumented Insoles and Deep Neural Networks

Sponsor

Yonsei University

Enrollment

200 participants

Start Date

Jun 1, 2021

Study Type

OBSERVATIONAL

Conditions

Knee Osteoarthritis Total Knee Arthroplasty

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.

Eligibility

Min Age: 19 Years

Inclusion Criteria4

Age ≥ 19 years
Diagnosed with knee osteoarthritis (Kellgren-Lawrence grade 1-4)
Scheduled for primary Total Knee Arthroplasty (TKA) at either study site
Able to walk independently on level ground (Functional Ambulation Categories, FAC ≥ 3)

Exclusion Criteria5

Cancellation of scheduled TKA
History of TKA on the same knee
Neurological or musculoskeletal disorders affecting gait
Pregnancy or possibility of pregnancy
Any condition deemed inappropriate for study participation by the investigator

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Interventions

OTHERInstrumented 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.