Research Article Open Access

A Review on Parkinson Disease Classifier Using Patient Voice Features

Abstract

Parkinson’s disease (PD) known as chronic and progressive movement disorder, means that symptoms continues and becomes worst over time.PD affects on person’s moves, also affects how they speak and write. After Alzheimer’s disease, around whole world 6.3 million people live with Parkinson’s disease which makes it the second most common neurological disorder. The cause of disease is unknown, and also there is presently no cure and no treatment options such as medication and surgery to manage its syndromes. Approximately 90% of PD patients have suffered speech difficultiesi.e., dysphonia which is impaired speech production and dysarthria is referred as speech articulation difficulties. These mobility deficits are difficult to treat with drugs or neurosurgery. Parkinson disease people must visit clinician to track their progressions regularly. It will become simple process to anticipate harshness of disease with the help of voice recording of patients. This can be achieved by using Hoehn Yahr Score and Parkinson disease Rating Scale (PDRS) Score. Combination of machine learning algorithms are used for classification of voice features according to severities of disease.

Priyanka Holkar, Payal Gatti, Sonali Meher, Pooja Sable