Post Stroke

Post-stroke rehabilitation focuses on improving functional abilities lost due to stroke, primarily targeting hand and arm motor function. Current research emphasizes developing personalized rehabilitation strategies using machine learning models (e.g., random forests, convolutional neural networks, and recurrent neural networks) to analyze data from various sources, including electronic health records, wearable sensors (accelerometers, smart glasses), and robotic systems. These advancements aim to optimize exercise selection, predict recovery outcomes, and enable remote, cost-effective rehabilitation, ultimately improving patient quality of life and reducing the burden on healthcare systems.