Development of a Smart Knee Brace for ACL Injury Rehabilitation

Abstract — Anterior Cruciate Ligament (ACL) injury rehabilitation has been transformed by recent developments in wearable and sensor-based technology, which provide creative ways to enhance recovery results. With the use of tools like goniometers and inertial measurement units (IMUs), sensorized knee braces provide constant joint angle and range of motion monitoring, making it possible to precisely monitor the course of recovery. In order to detect aberrant movements or aberrations that can impede rehabilitation, these systems offer real-time input on knee mechanics.Because they are more convenient, less expensive, and improve patient compliance, home-based rehabilitation programs have grown in popularity. With the use of these devices, patients can engage in therapy from the comfort of their own homes while being closely watched over by medical professionals. Research has shown how well these systems work in providing unbiased information on recovery parameters, such as range of motion and joint stability. In order to limit dangerous knee flexion and extension and lower the chance of reinjury, innovative knee braces also have automatic locking systems. In order to make sure that rehabilitation activities correspond with the patient's state of recovery, flexible capacitive sensors have been used to measure knee laxity and offer stability assessments. Additionally, wearable technology combined with ergonomic designs and smart fabrics improves user comfort and permits extended use, which increases the efficacy of therapy.Notwithstanding these developments, issues with sensor calibration, data accuracy, and device ergonomics still exist. By increasing sensor accuracy, creating energy-efficient designs, and utilising machine learning algorithms for predictive analytics, researchers are tackling these problems. The goal of these developments is to provide individualised rehabilitation regimens by developing technologies that dynamically adjust to the patient's recovery curve.