Developing a Musculoskeletal Model of Landing

ECU Author/Contributor (non-ECU co-authors, if there are any, appear on document)

Leela Devi Goel (Creator)

Institution

East Carolina University (ECU )

Web Site: http://www.ecu.edu/lib/

Abstract: Anterior Cruciate Ligament (ACL) injuries are a common sports related injury that results in a loss of play time, are painful, and limit a person’s quality of life while injured. ACL injuries often occur when a person is landing from a jump when the knee is close to full extension. However, it is not well understood why people adapt a landing control mechanism which results in landing with an extended knee. Musculoskeletal modeling is a useful tool to understand and predict how the body will act during a particular motion. By using simulated data, the exact control mechanism the model utilizes and the optimization criterion are known, allowing for a more robust understanding of the neuromuscular control mechanism of a particular motion which is difficult to obtain from experimental data. Additionally, there are few optimization control models for studying landing. Therefore, the purpose of this study is to develop a musculoskeletal model of landing to study the control mechanism of landing. We hypothesize that a model which minimizes acceleration of the head during landing will be the underlying control mechanism. A subject specific optimized landing model was developed using MATLAB. A rigid 4 segment two-dimensional model with six muscle groups was used. The model was optimized to minimize the acceleration of the head, vertical ground reaction force, and ensure an upright end position. The model produced physiologically relevant hip joint kinematics. However, the knee joint kinematics, vertical ground reaction force, and muscle active states were not physiologically reasonable. Future work will be done to improve the objective function of the model, optimization criteria, and use a wobbling mass 4 segment model instead of a rigid model.

Additional Information

Publication

Thesis

Language: English

Date: 2016

Keywords

Landing model, optimization, modeling

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