Speaker
Description
Parkinson’s disease (PD) is a chronic, progressive neurodegenerative disease characterized by both motor and non-motor features. The primary objective for us is the early diagnosis of patients using Artificial Intelligence (AI). To accomplish that we developed an Artificial Intelligence Model (model) that diagnoses PD using data collected from the patient’s gait. The data is represented by multiple images that are generated from raw data collected using a physiograph created by our team. For the research scope, we designed a Generative Adversarial Network that is capable of learning and reproducing real biomechanical data representing Parkinsonian patterns of gait, which is able to generate augmented data that will be used further for training our classification models.
Keywords: Neural Networks, Generative Adversarial Network, Convolutional Neural Network, Parkinson’s Disease
