KCT0009062
Completed
未知
Validity and reliability of deep-learning-based 3D markerless motion capture to measure functional movement
Yonsei University Mirae Campus0 sites31 target enrollmentTBD
ConditionsNot Applicable
Overview
- Phase
- 未知
- Intervention
- Not specified
- Conditions
- Not Applicable
- Sponsor
- Yonsei University Mirae Campus
- Enrollment
- 31
- Status
- Completed
- Last Updated
- 2 years ago
Overview
Brief Summary
The Ergo had a high degree of validity compared with the measured values of marker-based motion capture system. The linear regression analysis showed a high to excellent validity and the RMSEs were ranging from 2.33±0.46 ° to 6.25±1.65° in all time series joint angles. The intraclass correlation coefficient showed an excellent validity in all joint peak angles and bland-Altman analysis revealed no significant bias. Furthermore, The Ergo showed high convenience and efficiency results in post-question surveys.
Investigators
Eligibility Criteria
Inclusion Criteria
- •A person who can understand motion instructions and can perform motion without pain for more than 3 seconds
Exclusion Criteria
- •A person with a history of orthopedic surgery and neurological history
Outcomes
Primary Outcomes
Not specified
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