Classification of a Pincer Nail Using a Recurrent-based Neural Network

A pincer nail is a disease where a nail becomes deformed. The origin is unclear. Patients with a serious pincer nail cannot walk normally. Serious pincer nails are often treated surgically but tend to recur. Early diagnosis is essential because it allows for complete recovery using a special wire treatment. However, most patients do not seek diagnosis until the pincer nail is advanced. This paper proposes a system to assist doctors in early diagnosis and verifies that the system can distinguish between patients with a pincer nail and healthy persons. The system measures the gravity center fluctuation and uses a neural network to classify the data and defines the feature of a pincer nail patient. The results indicate that that the neural network can classify patients and healthy persons using the gait while walking.