Improved front-view tracking of human skeleton from Kinect data for rehabilitation support in Multiple Sclerosis
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Sosa, German D.
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Institute of Electrical and Electronics Engineers Inc.
Multiple Sclerosis (MS) is an auto-immune, inflammatory disease of the Central Nervous System (CNS), consisting in the progressive demyelinization of axonal fibers. Given its degenerative nature, MS treatment faces complex challenges for both pharmaceutical and therapeutic interventions. Indeed, patients with diagnostic of multiple sclerosis will require continuous rehabilitation for life in order to reduce the progression rate of the disease. However, to assess the actual impact of the particular therapeutic intervention is a difficult process with important implications in the choice of a treatment pathway. Objective measurements (response time, velocity, range of motion -ROM-, etc.) of patient performance could enhance the patient state information available for therapeutic decision making, in a continuous evaluation scenario. This work presents a first step in the design of a low-cost computer-vision based framework (using KinectTM) for the objective measurement of multiple sclerosis patient functional performance1. A real-time front-view detection of human skeleton was implemented to track patient motion and measure the ROM for neck, shoulder, elbow, hip and knee joints. Preliminary measurements on four control subjects (two males, two females) were performed and the system accuracy was evaluated against traditional static diagnostic measurements (goniometer). © 2015 IEEE.
Computer vision , Decision making , Diagnosis , Image processing , Joints (anatomy) , Medical computing , Musculoskeletal system , Signal processing , Central nervous systems , Diagnostic measurements , Inflammatory disease , Multiple sclerosis , Objective measurement , Range of motions , System accuracy , Therapeutic intervention , Patient rehabilitation