Parkinson Disease Diagnosis

Parkinson's disease (PD) is the second most common neurodegenerative disease in the world, with a large patient population and high disability rate. The International Society for Movement Disorders-Unified Parkinson's Disease Comprehensive Evaluation Scale (MDS-UPDRS) is an important clinical standard and diagnostic tool for PD diagnosis, disease progression, and curative effect evaluation. Due to the problems such as physician subjectivity, this tool has not been popularized in the diagnosis and treatment of Parkinson's disease. The automatic diagnosis of MDS-UPDRS will significantly reduce the labor cost of doctors and improve the efficiency of clinical diagnosis and treatment. In addition, early intervention and treatment of PD can effectively improve clinical symptoms, improve exercise capacity and social ability of patients, and greatly reduce adverse effects on family and society. However, the early symptoms of PD are vague and heterogeneous, and the early symptoms of different PD patients are different, which is difficult to capture.

Parkinson's disease intelligent diagnosis robot is committed to realizing the quantitative evaluation of MDS-UPDRS and the keen perception of early symptoms of PD, so as to improve the diagnosis rate and treatment evaluation effect of PD. This project expands multi-modal input on the basis of binocular vision, endows the robot with vision, hearing, and touch, so that it can fully perceive the patient's large-scale movements, small-scale movements, expressions, voice and other changes. Through the data-driven machine learning algorithm, the efficiency of the Parkinson's disease diagnosis and treatment process and the objectivity of the evaluation are comprehensively improved, the automation of the diagnosis and treatment process is achieved, and the full-stage intelligent evaluation of PD early screening and diagnosis is realized. This project has important clinical value and significance for the popularization of PD diagnosis and treatment in the whole society.