Understanding and preventing anterior cruciate ligament injuries using novel motion analysis systems
Abstract/Contents
- Abstract
- The overall goal of this dissertation is to use novel motion analysis systems to investigate the underlying mechanisms that cause an anterior cruciate ligament (ACL) injury and then to explore movement modification methods that might prevent ACL injuries from occurring. Additionally, novel motion analysis systems can provide new information about ACL injuries and therefore should be used to help analyze these injuries from a different perspective. This thesis provides the results from multiple experimental studies that used two novel motion analysis systems to investigate the underlying causes of ACL injury and potential injury prevention methods. Using a markerless motion capture system, the first investigation determined that increasing the coefficient of friction of the shoe-surface condition will change a subject's movement strategies during a sidestep cutting task in specific ways that may increase the risk of ACL injury. This investigation provides a biomechanical basis for the increased incidence of ACL injuries on high friction surfaces, and suggests that females are more at risk for ACL injury when cutting on high friction surfaces. In terms of novel motion analysis systems, there is a need for simple, cost effective methods to identify athletes at a higher risk for ACL injury during jumping tasks. As such, the second study assessed the capacity of a wearable inertial-based system to evaluate ACL injury risk during jumping tasks. The proposed system measured the knee flexion angle and the trunk lean, and demonstrated good concurrent validity and discriminative performance in terms of the known risk factors for ACL injury. This study also reported the angular velocity of the thigh and shank segments during bilateral and unilateral drop jumps for the first time. Furthermore, this study illustrated that there is an association between the coronal segment angular velocity and knee abduction moment, and that the coronal segment angular velocity can differentiate between subjects at higher risk for ACL injury. Recent studies have shown that the incidence of ACL injury can be decreased through the use of intervention programs. Therefore, the objective for the final study was to determine if an independent inertial-based system can be used to modify jump landing mechanics in order to decrease the risk for ACL injury by providing real-time feedback based on known kinematic and kinetic injury risk factors. This study found that the subjects reduced their risk for ACL injury after training with the system because there were significant increases in the maximum knee flexion angle and the maximum trunk lean. The subjects also reduced their risk for injury by decreasing their thigh coronal angular velocity, which was correlated with a decrease in their knee abduction moment. This study suggests that an inertial-based system could be used for interventional training aimed at reducing the risk for ACL injury.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2011 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Dowling, Ariel Veronica | |
|---|---|---|
| Associated with | Stanford University, Department of Mechanical Engineering | |
| Primary advisor | Andriacchi, Th. P. (Thomas P.) | |
| Thesis advisor | Andriacchi, Th. P. (Thomas P.) | |
| Thesis advisor | Cutkosky, Mark R | |
| Thesis advisor | Giori, Nicholas John | |
| Advisor | Cutkosky, Mark R | |
| Advisor | Giori, Nicholas John |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Ariel Veronica Dowling. |
|---|---|
| Note | Submitted to the Department of Mechanical Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2011. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2011 by Ariel Veronica Dowling
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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