Rheumatoid Arthritis (RA) is a disease in which the body has "turned on itself", with its immune system attacking mobility. In RA, an immune mechanism attacks and destroys the joints and limits mobility, in some circumstances to the point of needing replacement of joints. The aim of this research is the development of a less costly, widely accessible, passive sensing technology that provides a quantitative assessment of RA and that monitors the therapeutic effectiveness on joint-debilitating diseases. The proposed solution relies on a quantitative evaluation of human gestures. Such a quantitative assessment supports the comparison between the motion capabilities of a patient and that of a healthy person, using a kinematic model of the human skeleton. Criteria for the classification of severity were established, and tables were generated to classify the levels of severity as a function of the measurements extracted from processed videos of a subject performing predefined movements. This research project, while contributing a new tool to the process of classification of RA level of severity, opens the way for using widely accessible digital imaging for diagnosing and monitoring the evolution of the illness. Replacing MRI or HRUS with a cheaper and more accessible technology would have a major impact on health care services. From the clinical point of view, the proposed techniques based on digital images processing combined with a monitoring approach based on infrared images that was previously developed may provide a utility of care for patients with RA, as well as an alternative and automated approach for early detection of RA and active inflammation at a critical time.

Rheumatoid Arthritis (RA) is a disease in which the body has "turned on itself", with its immune system attacking mobility. In RA, an immune mechanism attacks and destroys the joints and limits mobility, in some circumstances to the point of needing replacement of joints. The aim of this research is the development of a less costly, widely accessible, passive sensing technology that provides a quantitative assessment of RA and that monitors the therapeutic effectiveness on joint-debilitating diseases. The proposed solution relies on a quantitative evaluation of human gestures. Such a quantitative assessment supports the comparison between the motion capabilities of a patient and that of a healthy person, using a kinematic model of the human skeleton. Criteria for the classification of severity were established, and tables were generated to classify the levels of severity as a function of the measurements extracted from processed videos of a subject performing predefined movements. This research project, while contributing a new tool to the process of classification of RA level of severity, opens the way for using widely accessible digital imaging for diagnosing and monitoring the evolution of the illness. Replacing MRI or HRUS with a cheaper and more accessible technology would have a major impact on health care services. From the clinical point of view, the proposed techniques based on digital images processing combined with a monitoring approach based on infrared images that was previously developed may provide a utility of care for patients with RA, as well as an alternative and automated approach for early detection of RA and active inflammation at a critical time.