  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.

Artificial Intelligence