Parkinson's disease (PD), as one of the most common neurodegenerative disorders, is primarily characterized by the progressive degeneration and death of dopaminergic neurons in the substantia nigra of the midbrain. The disease presents with complex and diverse clinical manifestations, and faces dual challenges in early diagnosis and the lack of curative treatments. The number of PD patients has been increasing year by year in China, forming a large patient population. The disease not only severely affects patients' quality of life but also greatly increases the societal healthcare burden. Advances in technology have enabled the growing application of digital phenotyping and artificial intelligence (AI) technologies in disease diagnosis and therapy, offering new opportunities for PD management. This article systematically explores the latest progress in the application of digital phenotyping and AI technologies in PD assessment and smart rehabilitation, including speech analysis, quantification of facial expressions, motion signal monitoring, and the integration of AI with treatment. Specific applications encompass speech feature extraction, facial expression assessment, wearable devices, and the development of personalized rehabilitation strategies. The article also identifies current problems and challenges in technology implementation, clinical application, and ethical regulation, with the aim of providing insights for future technology development and long-term PD management.
Xi Chen (Thu,) studied this question.