Design and Development of Computational Methodologies for Predicting Parkinson's Disease with Artificial Intelligence

Parkinson's disease is a degenerative ailment that affects the central nervous system, hinders movement, and produces tremors and rigidity. Its four stages have an impact on more than 1 million people in India each year. For this persistent illness, there is no known cure. It can only be treated if it is discovered early. Scientists have long theorized that voice impairment is one of the initial signs of Parkinson's disease. Vocal changes in Parkinson's disease patients could be recognized, enabling earlier intervention before physically incapacitating symptoms manifest. With the use of a number of speeches signaling techniques, the proposed work intends to develop a model that examines a person's voice and forecasts their likelihood of developing an illness. Parkinson's disease is a brain disorder where a part of your brain gradually deteriorates, leading to ever-worse symptoms. Numerous symptoms, including stiffness, bradykinesia, difficulties with coordination, and voice irregularities, are brought on by this neurodegeneration. Dysarthria is another symptom of Parkinson's disease. The primary flaws of PD speaking are decrease in intensity, monotony of pitch and loudness, inappropriate silences, and a breathy voice. Clinical signs, such as the description of a variety of movement symptoms and medical observations, are frequently used for treatment of Parkinson's disease (PD). On the other hand, conventional diagnostic techniques may be subjectivity-prone since they rely on the interpretation of motions that may be challenging to identify because they are occasionally imperceptible to human sight.