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

Status: Recruiting
Location: See location...
Intervention Type: Other
Study Type: Observational
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
Participation Requirements
Sex: All
Minimum Age: 19
Healthy Volunteers: f
View:

• 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)

Locations
Other Locations
Republic of Korea
Yongin Severance Hospital
RECRUITING
Yongin-si
Contact Information
Primary
Na Young Kim, MD, PhD
kny8452@yuhs.ac
+82 010 9127 4482
Backup
Seung Ick Choi
rehab1@yuhs.ac
+82 010 8821 5297
Time Frame
Start Date: 2021-06-01
Estimated Completion Date: 2026-12-31
Participants
Target number of participants: 200
Treatments
TKA Patients
Participants scheduled for primary unilateral total knee arthroplasty at either Yongin Severance Hospital or Gachon University Gil Medical Center. No intervention is assigned; all data are collected as part of observational evaluation.
Sponsors
Leads: Yonsei University

This content was sourced from clinicaltrials.gov