Interactive Video Acquisition and Learning System for Motor Assessment of Parkinson's Disease
Interactive Video Acquisition and Learning System for Motor Assessment of Parkinson's Disease
Yunyue Wei, Bingquan Zhu, Chen Hou, Chen Zhang, Yanan Sui
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
Demo Track. Pages 5024-5027.
https://doi.org/10.24963/ijcai.2021/718
Diagnosis and treatment for Parkinson's disease rely on the evaluation of motor functions, which is expensive and time consuming when performing at clinics. It is also difficult for patients to record correct movements at home without the guidance from experienced physicians. To help patients with Parkinson’s disease get better evaluation from in-home recorded movement videos, we developed an interactive video acquisition and learning system for clinical motor assessments. The system provides real-time guidance with multi-level body keypoint tracking and analysis to patients, which guarantees correct understanding and performing of clinical tasks. We tested its effectiveness on healthy subjects, and the efficiency and usability on patient groups. Experiments showed that our system enabled high quality video recordings following clinical standards, benefiting both patients and physicians. Our system provides a novel learning-based telemedicine approach for the care of patients with Parkinson’s disease.
Keywords:
Human-Computer Interaction: General
Computer Vision: General
Machine Learning: General