Diagnosing Methods of Parkinson's Disease: Revolutionary Techniques

Abstract

Parkinson's disease is known by tremor, rigidity, and bradykinesia. Non-motor symptoms also manifest during the disease course or even predate the appearance of motor-symptoms and that can be as troublesome as motor features. At the cellular level, the degeneration of substantia nigra neurons and the low levels of dopamine caused by intracytoplasmic inclusions of Lewy bodies that consist of α-synuclein were recognized as the putative cause of the disease and therefore physical symptoms. PD is a slow-moving illness and detection of that disease is not easy because of delayed symptoms, variation in clinical manifestations, course of progression, and biomarker profiles from person to person. Early diagnosis of PD plays a critical role in effective disease management. Here, the authors aim to give an overview of different methods of diagnosing PD with emphasis on clinical differential diagnosis that differentiate it from other parkinsonian disorders, challenges, and a brief description of new approaches of artificial intelligence technologies as a tool for better prediction of that disease.