Improving ACL Reconstruction Outcomes with NeuroBrace: A Clinical and Economic Framework

Abstract

Nearly  200,000 individuals in the United States  undergo Anterior Cruciate Ligament (ACL) reconstruction annually Still, the standard post-surgery recovery methods  have not  changed in decades. Conventional braces stabilize the joint but do not address arthrogenic muscle inhibition (AMI), which is a  reflex mechanism that lowers the activity of the quadriceps  after injury, resulting in rapid quad atrophy and secondary rupture rates in more than  20% young athletes. Here, we  propose NeuroBrace, which is a closed-loop orthotic pairing surface EMG (sEMG) sensors with targeted neuromuscular electrical stimulation (NMES) to detect and correct activation deficits, while equipping clinicians with objective compliance data. By implementing  conceptual meta-synthesis of published sEMG, NMES, and landing-biomechanics studies , we model how consistent use of the feedback loop could accelerate quad hamstring co-activation symmetry and reduce risk of re-injury, and pair that with a cost model built on Remote Therapeutic Monitoring reimbursement codes to estimate savings from shifting rehab out of the clinic and into an AI guided home protocol.