Monitoring joint mechanics in anterior cruciate ligament reconstruction using depth sensor-driven musculoskeletal modeling and statistical parametric mapping

Abstract

The incidence of anterior cruciate ligament injury and reconstruction (ACLR) may set the stage for the development of early onset osteoarthritis in these patients. Development of accessible quantitative motion capture methodologies for recurrent monitoring of knee joint loading during daily activities following ACLR is necessary. This study aimed to compare lower extremity kinetics between ACLR affected limbs, ACLR unaffected limbs, and dominant limbs of healthy control subjects during over-ground gait and stair ascent using a single depth sensor-driven musculoskeletal modeling approach. No meaningful differences were found between groups during over-ground gait in any kinetic variables. When subjected to a stair ascent task, both ACLR limbs showed greater hip extension and internal rotation moments compared to control subjects at approximately 72–79% stance. This was coincident with greater knee flexion moments in both ALCR limbs compared to control. The absence of differences during over-ground gait but presence of compensatory strategies during stair ascent, suggests task dependent recovery in this cohort who were tested at least 1-year following surgery. Importantly, this was determined using a portable low-cost motion capture method which may be attractive to professionals in sports medicine for recurrent monitoring following ACLR.