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Hypomimia is a condition in the early stages of the progression of Parkinsonsdisease that limits the movement of facial muscles, restricting the accuratedepiction of facial expressions. Also known as facial masking, this conditionis an early symptom of Parkinson's disease, a neurodegenerative disorder thataffects movement. To date, no specific test exists to diagnose the disease.Instead, doctors rely on the patient medical history and symptoms to confirmthe onslaught of the disease, delaying treatment. This study aims to develop adiagnostic tool for Parkinsons disease utilizing the Facial Action CodingSystem, a comprehensive system describing all facially discernible movement. Inaddition, this project generates image datasets by simulating faces or actionunit sets for both Parkinsons patients and non-affected individuals throughcoding. Accordingly, the model is trained using supervised learning and neuralnetworks. The model efficiency is compared using Convolutional Neural Networkand Vision Transformer models and later tested with a test program by passing aParkinsons disease-affected image as input. The future goal is to develop aself-determining mobile application (PDiagnosis) by utilizing the model todetermine the probability of Parkinsons progression.

Simulation Study and At Home Diagnostic Tool for Early Detection of Parkinsons Disease