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.

本文介绍了我们开发的智能手机移动设备和 AI 技术相结合的 PD 早期检测系统框架，该系统结合了不同任务，评估了运动和非运动症状，以帮助用户在非临床设置中及时检测 PD，确定其最严重的症状，进而用于 PD 康复指导及其他神经疾病的检测。