Comparative Study on the Detection of Parkinson's Diseaseusing Machine Learning

Abstract

Parkinson's disease is a progressive disorder that affects the nervous system and the parts of the body controlled by the nerves and the root cause of it is falling rates of dopamine levels in the forebrain. It is a chronic degenerative disease with progressive illness, which means it develops new symptoms over time, actually the average diagnosis time is above two years. The prediction of the Parkinson’s disease is the most challenging problem for the biomedical engineering researches and doctors.Due to the decrease in motor control that is the hallmark of the disease, voice can be used as a means to detect and diagnose PD. With advancements in technology and the prevalence of audio collecting devices in daily lives, reliable models that can translate this audio data into a diagnostic tool for healthcare professionals would potentially provide diagnoses that are cheaper and more accurate. We provide evidence to validate this concept here using a voice dataset collected from people with and without PD.