Certain investigations on detection and classification of human knee rheumatoid arthritis using machine learning algorithms

Abstract

Arthritis is a chronic inflammation of a joint with pain. It is one of the widely spreading diseases in worldwide. It affects people in all groups of ages but is comparatively high in females than in males. All the bone joint ends are covered with cartilage tissue in the human body that provides smoothness during the movement. Arthritis affects the cartilage tissue and tears the tissue which causes pain and swelling in the joints. It mainly occurs in the knee joint, finger joint, thumb, neck, etc. Initially, it starts with mild joint pain and becomes severe after a few days. The patient may experience pain and discomfort throughout their life. It also results in permanent damage to joints. The most well-known type of Arthritis is Rheumatoid Arthritis (RA) and it occurs in the knee joint. Joint pain is the major symptom of Rheumatoid Arthritis later on it affects the whole joint with severe pain. A few existing methods like X-ray, MRI, CT scan, and infrared imaging are used to detect arthritis. Physicians may suggest non-surgical treatment for RA like weight reduction or doing exercises etc. Even though recommended treatments are available, the disease is not permanently curable if it is identified in later stages. newlineThe existing diagnosis method often uses high radiation for arthritis detection at the same time it gives accurate results. The regular walking pattern is changed due to knee pain and it is reflected in the variations in the foot pressure distribution. To detect knee arthritis in its early stages the pressure distribution by the knee need to be monitored. To monitor the foot pressure some wearable sensor-based, floor sensor, and vision-based research newline newline