A Multisensor Integration-Based Complementary Tool for Monitoring Recovery Progress of Anterior Cruciate Ligament-Reconstructed Subjects

Abstract

Anterior cruciate ligament (ACL) trauma, being one of the most common musculoskeletal injuries in sports, leads to knee joint instability and causes ambulation impairments. A careful monitoring of the progress of recovery after ACL reconstruction is crucial for minimizing postoperative complications and reinjuries. This research is aimed at designing a complementary tool to assess the recovery status and knee dynamics during the rehabilitation period after ACL reconstruction. The prototype includes wireless body-mounted motion sensors for kinematics measurements, surface electromyography system for muscle activity measurements, a video camera for recording trial activities and custom-developed intelligent system software that provides classification of the progress of the recovery and visual biofeedback during rehabilitation. The subjects’ recovery stages are classified based on combined features from sensors’ data, using an adaptive neuro-fuzzy inference system. The visual biofeedback provides monitoring of different signals simultaneously in order to help in detecting the intra and intersubject variability and correlation between the knee joint dynamics and muscle activities. The promising results of this initial study for assessing the ambulation at various speeds showcase the prospects of using the proposed system as part of existing rehabilitation monitoring procedures to achieve a more effective and timely recovery of ACL-reconstructed subjects.