Cloud-Driven Precision Rehabilitation: A Data Analytics Approach for Post-Stroke Recovery Enhancement

The feasibility of combining cloud computing and advanced data analytics into a precision rehabilitation system for post-stroke recovery is presented. The main aim is to create a system that facilitates recovery after a stroke. The system gathers real-time data on the user's activity by using Raspberry Pi-powered smart wearables to collect data from motion sensors. After that, it securely sends the data to an infrastructure that is located in the cloud where it is housed. To analyze and make sense of movement patterns, a sophisticated data processing pipeline hosted in the cloud employs machine learning algorithms. Because of this, it is now feasible to provide customized feedback and advice for workouts. The cloud-driven method makes it simpler to accomplish seamless scalability and raises the system's potential for continuous improvement and real-time analytics. Cloud computing makes both things possible. This cutting-edge device aims to revolutionize post-stroke rehabilitation by providing healthcare professionals with actionable information, fostering more individualized treatment plans, and, ultimately, accelerating the healing process for stroke patients.