1 Copyright © 2012 by ASME WIRELESS MULTI-SENSOR INTEGRATION FOR ACL REHABILITATION USING BIOFEEDBACK MECHANISM SMN Arosha Senanayake Department of Computer Science, University of Brunei    Gadong BE1410, Brunei arosha.senanayake@ubd.edu.bn Owais Ahmed Malik Department of Computer Science, University of Brunei    Gadong BE1410, Brunei 11H1202@ubd.edu.bn Pg. Mohammad Iskandar Department of Applied Physics, University of Brunei    Gadong BE1410, Brunei iskandar.petra@ubd.edu.bn ABSTRACT The objective of this study is to propose an integrated motion analysis system for monitoring and assisting the rehabilitation process for athletes based on biofeedback mechanism, particularly for human subjects already undergone Anterior Cruciate Ligament (ACL) injury operations and thus about to start the rehabilitation process. For this purpose, different types of parameters (kinematics and neuromuscular signals) from multi-sensors integration are combined to analyze the motion of affected athletes. Signals acquired from sensors are pre-processed in order to prepare the pattern set for intelligent algorithms to be integrated for possible implementation of effective assistive rehabilitation processing tools for athletes and sports orthopedic surgeons. Based on the characteristics of different signals invoked during the rehabilitation process, two different intelligent approaches (Elman RNN and Fuzzy Logic) have been tested. The newly introduced integrated multi-sensors approach will assist in identifying the clinical stage of the recovery process of athletes after ACL repair and will facilitate clinical decision- making during the rehabilitation process. The use of wearable wireless miniature sensors will provide an un-obstructive assessment of the kinematics and neuromuscular changes occurring after ACL reconstruction in an athlete. INTRODUCTION Human motion analysis is an active research area due to its importance and applications in different fields including pathology identification [1,2], elderly fall prevention[3], rehabilitation of patients[4,5] and sports [6]. In the area of sports medicine, motion analysis has been used for helping in recovery from injuries, designing new products and improving the skills of athletes. Motion analysis can help in designing rehabilitation techniques for athletes suffering from lower limb injuries. One of the most common lower limb injuries that may adversely affect the motion and thus career of an athlete is the knee injury due to Anterior Cruciate Ligament (ACL) rupture. The data on surgical reconstruction in sporting population revealed varying estimated incidence of ACL [7, 8]. There are different causes of ACL injury in sports including sudden stops during running, quick change of direction, pivoting, incorrect landing and direct blow to knee are some of the important causes of ACL sprain or tears. Proceedings of the ASME 2012 International Mechanical Engineering Congress & Exposition IMECE2012 November 9-15, 2012, Houston, Texas, USA IMECE2012-87809