Using Motor Imaging and Deep Neural Networks for Knee Osteoarthritis (OA) Diagnosis: A State-of-the-Art Approach

Knee osteoarthritis is a degenerative condition affecting the knee joints. It occurs when the cartilage covering the joint surfaces of the knee progressively wears away, leading to pain, swelling, stiffness, and loss of function in the affected knee. Cartilage, a smooth and tough tissue, is a shock absorber between bones and enables smooth joint movement. With time, factors such as aging, overuse, or prior injuries can contribute to cartilage deterioration, thus increasing the risk of knee osteoarthritis development. Accurately diagnosing knee osteoarthritis (OA) can be time-consuming, given that several other conditions share similar signs and symptoms. This study aims to expedite the diagnosis of knee OA by leveraging motor imagery patterns detected through electroencephalogram (EEG) analysis using deep learning techniques.