Information about project titled 'Accuracy and Reliability of Model-Based Image-Matching Technique on Ankle Joint Motion Analysis'
Accuracy and Reliability of Model-Based Image-Matching Technique on Ankle Joint Motion Analysis
| Details about the project - category | Details about the project - value |
|---|---|
| Project status: | Published |
| Project manager: | Kam Ming Mok |
| Supervisor(s): | Kai-Ming Chan |
| Coworker(s): | Daniel Fong, Tron Krosshaug, Patrick Yung |
Description
Ankle sprain is one of the most common injuries encountered at sport events (Fong et al., 2007; Fong et al., 2009). Ankle sprain incidents are occasionally recorded unintentionally during television broadcasting. Those video recordings provide valuable information for deducing joint kinematics of specific sport injury, as well as, contributing to the study of injury mechanism. Krosshaug and Bahr (2005) introduced a Model-Based Image-Matching (MBIM) technique for reconstructing human motion from uncalibrated video sequences. Calibrated video setting was not prerequisite in this motion analysis technique. However, only the validation of knee joint movements had been done. Therefore, the validation on ankle joint movement is needed before the application of this technique in investigating ankle kinematics. Bone-pin marker based motion analysis was utilized to reliably calculate the ankle joint kinematics in the present study.
The aim of this study was to validate the MBIM technique on ankle motion measurement with reference to bone-pin marker based motion analysis on a cadaver.
Methods: One cadaveric below-hip specimen was prepared for performing full-range plantarflexion/dorsiflexion, inversion/eversion and relative circular motion between the shank and foot segments. The videos were recorded by four video cameras and analyzed by the MBIM technique and bone-pin marker based motion analysis. The matching procedure was repeated by five times. The results were presented as bivariate correlation coefficients, root mean square (RMS) error and intraclass correlation coefficients (ICCs).