Shoupa: An AI System for Early Diagnosis of Parkinson's Disease
This addresses the problem of inaccessible early PD diagnosis for elderly populations, though it appears incremental as it integrates existing AI technologies with mobile devices.
The paper tackles early diagnosis of Parkinson's Disease by developing an AI system that uses smart mobile devices to evaluate motor and non-motor symptoms in non-clinical settings, aiming to help users detect PD and identify severe symptoms for rehabilitation guidance.
Parkinson's Disease (PD) is a progressive nervous system disorder that has affected more than 5.8 million people, especially the elderly. Due to the complexity of its symptoms and its similarity to other neurological disorders, early detection requires neurologists or PD specialists to be involved, which is not accessible to most old people. Therefore, we integrate smart mobile devices with AI technologies. In this paper, we introduce the framework of our developed PD early detection system which combines different tasks evaluating both motor and non-motor symptoms. With the developed model, we help users detect PD punctually in non-clinical settings and figure out their most severe symptoms. The results are expected to be further used for PD rehabilitation guidance and detection of other neurological disorders.