Osteoarthritis is one of the most common diseases of the knee joint, especially among obese and elderly. However, the diagnosis rely on expensive and invasive methods as X-ray imaging or arthroscopy.
Vibroarthrography (VAG) has been proposed as a non-invasive tool for therapists to evaluate the pathological condition of the knee joint during physical therapy. It has been proposed to use accelerometers to determine if the vibrations of an osteoarthritis knee could be differentiated from a non-pathological knee under in-vivo conditions.
During a dynamic activity, the interaction between the moving articulating surfaces induces vibrations of the bones. In a healthy joint the articulating surfaces are smooth and the vibration is minimal, but as the cartilage degenerates, the articular surfaces become more rough and vibrations increase, and may become audible in extreme cases.
The accelerometers record the change in acceleration resulting from both the movement of the joint as well as from the vibration of the bones and feature extraction methods should be implemented to extract meaningful information from the accelerometer signals to develop pattern recognition algorithms for the classification task.
The inertial sensors could alternatively be coupled to an elastic knee brace to be more practical for elderly use and long term monitoring. This system could be used in the future as a non-invasive assessment tool of the articular cartilage condition. Further research could focus on determining earlier stages of arthritis, before they become symptomatic.
Development of an accelerometer-based system for knee data acquisition and differentiation between normal and pathological knee.
This thesis could drive the study of specific pathological conditions that affect gait and that benefit from physiotherapy. It could also be incorporated as a screening tool for people with arthritic knee joints.
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