A Literature Review of A Method of Classifying Normal And Parkinson’s Disease Using Machine Learning

This study’s goal is to investigate the variables that, when combined with normal walking and voice recordings, could be utilised to spot atypical gait patterns in Parkinson’s disease patients. The cause of this disease, a neurological condition, remains uncertain. Hypokinetic dysarthria,that affects all surfaces of speech signal production, breathing, phonation, nasality, and prosody, are some of symptom of this disease. We created a vocal problem assessment for identifying unhealthy persons’s Whose dopamine level is lesser then actual using data from a required collection of data. In order to get the required data from the speech sample ,we flatten the signal through figuring out it’s mean value.To differentiate, we employed Support Vector Machines with several kinds of kernels and the Leave-One-Subject-Out validation strategy.