2019Unpublished venueRequires access

Musculoskeletal modeling to predict and reduce Antetrior Cruciate Ligament injury during single leg drop jump activity: Synergistic muscle co-activation approach

Oishee Mazumder, Kingshuk Chakravarty, Debatri Chatterjee, Aniruddha Sinha, Murali Poduval

Open publisher page 4 citations

Abstract

This paper presents a `drop jump' modeling to study the effect of synergistic muscle activation on controlling Anterior Cruciate Ligament (ACL) injury. ACL injuries are mostly caused during high impact loading. A full body musculoskeletal model with knee ligaments have been developed in `OpenSim platform' to simulate ACL injury during drop jump activity. The model is used to quantify the effect of change in muscle activation on different kinetic and kinematic parameters, which are associated with ACL injury. A neuromusculoskeletal controller have been designed which selects optimal muscle activation of Quadriceps, Hamstrings, Gastrocnemius and Tibilias anterior muscle group so as to reduce the chance of ACL injury and ankle inversion risk while jumping from elevated platforms. The OpenSim model along with the neuro-muscular controller forms an injury `predict-adapt' system, which can be useful in designing specific training sessions for athletics or for planning personalized rehabilitation therapy.

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What this paper is about

This paper presents a `drop jump' modeling to study the effect of synergistic muscle activation on controlling Anterior Cruciate Ligament (ACL) injury. ACL injuries are mostly caused during high impact loading. A full body musculoskeletal model with knee ligaments have been developed in `OpenSim platform' to simulate ACL injury during drop jump activity. The model is used to quantify the effect of change in muscle activation on different kinetic and kinematic parameters, which are associated with ACL injury. A neuromusculoskeletal controller have been designed which selects optimal muscle activation of Quadriceps, Hamstrings, Gastrocnemius and Tibilias anterior muscle group so as to reduce the chance of ACL injury and ankle inversion risk while jumping from elevated platforms. The OpenSim model along with the neuro-muscular controller forms an injury `predict-adapt' system, which can be useful in designing specific training sessions for athletics or for planning personalized rehabilitation therapy.

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Available abstract

This paper presents a `drop jump' modeling to study the effect of synergistic muscle activation on controlling Anterior Cruciate Ligament (ACL) injury. ACL injuries are mostly caused during high impact loading. A full body musculoskeletal model with knee ligaments have been developed in `OpenSim platform' to simulate ACL injury during drop jump activity. The model is used to quantify the effect of change in muscle activation on different kinetic and kinematic parameters, which are associated with ACL injury. A neuromusculoskeletal controller have been designed which selects optimal muscle activation of Quadriceps, Hamstrings, Gastrocnemius and Tibilias anterior muscle group so as to reduce the chance of ACL injury and ankle inversion risk while jumping from elevated platforms. The OpenSim model along with the neuro-muscular controller forms an injury `predict-adapt' system, which can be useful in designing specific training sessions for athletics or for planning personalized rehabilitation therapy.

Key concepts: Anterior cruciate ligament, ACL injury, Physical medicine and rehabilitation, Ankle, Kinematics, Jump, Computer science, Medicine

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Musculoskeletal modeling to predict and reduce Antetrior Cruciate Ligament injury during single leg drop jump activity: Synergistic muscle co-activation approach — Research Paper | ScholarLens