Presenter's Name(s)

Katlyn HallFollow

Primary Faculty Mentor Name

Niccolo Fiorentino

Project Collaborators

Timothy Tourville, Rebecca Choquette

Status

Undergraduate

Student College

College of Engineering and Mathematical Sciences

Program/Major

Biomedical Engineering

Primary Research Category

Engineering & Physical Sciences

Secondary Research Category

Health Sciences

Presentation Title

Computational Modeling of Knee Joints in Persons 6 Months after ACL Reconstruction

Time

9:10 AM

Location

Jost Foundation Room

Abstract

Anterior cruciate ligament, ACL, injuries are common especially for young athletes. ACL reconstruction, ACLR, is a surgical technique that replaces a damaged ACL. This surgery allows for individuals to regain knee stability; however, the reconstructed knee is at a higher risk of developing functional limitations, muscle weakness and early-onset osteoarthritis. To gain insight into possible causes of joint dysfunction after ACLR, musculoskeletal models were used to analyze motion capture data during normal gait. This study created subject-specific musculoskeletal models and performed computational modeling of the lower limbs during the weight bearing phase of gait.

Problem Statement:

Currently, the cause of functional changes after ACLR surgery is unknown. Computational modeling of the knee using subject-specific musculoskeletal models could give insight to potential causes of knee joint dysfunction.

Methods:

The gait of seven subjects were analyzed six months after their ACLR. Motion capture data were gathered using retroreflective markers, cameras, and ground reaction data. Data were analyzed for two static trials and two dynamic trials for each subject. Motion data were post-processed with Vicon Nexus and MATLAB. Subject-specific models were generated using OpenSim and the static trials. Using OpenSim, inverse kinematics, inverse dynamics, static optimization, and joint reaction simulations were performed on the dynamic trials.

Results:

No statistically significant differences were found between the knee after ACLR and the healthy contralateral knee in the normalized metrics tested: knee angle, knee moment, vastus lateralis activation, vastus lateralis muscle force, and vertical knee reaction force.

Conclusions:

Future work currently involves making refinements to the musculoskeletal models to improve accuracy. Specifically, work is being done to improve the tracking of joint centers during the dynamic trials. Furthermore, additional dynamic trials will be analyzed for each subject and more subjects are being recruited.

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Computational Modeling of Knee Joints in Persons 6 Months after ACL Reconstruction

Anterior cruciate ligament, ACL, injuries are common especially for young athletes. ACL reconstruction, ACLR, is a surgical technique that replaces a damaged ACL. This surgery allows for individuals to regain knee stability; however, the reconstructed knee is at a higher risk of developing functional limitations, muscle weakness and early-onset osteoarthritis. To gain insight into possible causes of joint dysfunction after ACLR, musculoskeletal models were used to analyze motion capture data during normal gait. This study created subject-specific musculoskeletal models and performed computational modeling of the lower limbs during the weight bearing phase of gait.

Problem Statement:

Currently, the cause of functional changes after ACLR surgery is unknown. Computational modeling of the knee using subject-specific musculoskeletal models could give insight to potential causes of knee joint dysfunction.

Methods:

The gait of seven subjects were analyzed six months after their ACLR. Motion capture data were gathered using retroreflective markers, cameras, and ground reaction data. Data were analyzed for two static trials and two dynamic trials for each subject. Motion data were post-processed with Vicon Nexus and MATLAB. Subject-specific models were generated using OpenSim and the static trials. Using OpenSim, inverse kinematics, inverse dynamics, static optimization, and joint reaction simulations were performed on the dynamic trials.

Results:

No statistically significant differences were found between the knee after ACLR and the healthy contralateral knee in the normalized metrics tested: knee angle, knee moment, vastus lateralis activation, vastus lateralis muscle force, and vertical knee reaction force.

Conclusions:

Future work currently involves making refinements to the musculoskeletal models to improve accuracy. Specifically, work is being done to improve the tracking of joint centers during the dynamic trials. Furthermore, additional dynamic trials will be analyzed for each subject and more subjects are being recruited.