Movement Disorder

Movement disorders research focuses on developing objective and efficient diagnostic tools for conditions like Parkinson's disease and cerebral palsy, improving upon subjective clinical evaluations. Current research employs computer vision and machine learning, leveraging algorithms like convolutional neural networks and graph convolutional networks, to analyze video and sensor data (e.g., from wearables and smartphones) for automated kinematic feature extraction and classification of movement patterns. These advancements aim to improve diagnostic accuracy, accessibility, and efficiency, particularly in resource-limited settings, ultimately leading to better patient care and management of these debilitating conditions.