Machine Learning-Based Wearable Devices for Smart Healthcare Application With Risk Factor Monitoring

Abstract

The stroke is an important health burden around the world that occurs due to the block of blood supply to the brain. The interruption of blood supply depends on either the sudden blood supply interruption to the brain or a blood vessel leak in tissues. It is tricky to treat stroke-affected patients because the accurate time of stroke is unknown. Internet of things (IoT) is an active field and plays a major role in stroke prediction. Many machines learning (ML) techniques have been used to automate the process and enable many machines to detect the prediction rate of stroke and analyze the risk factor. The ML-based wearable device plays a significant role in making real-time decisions that benefit stroke patients. The parameters such as risk factors associated with stroke and wearable sensors and machine learning techniques for stroke prediction are discussed.