Revolutionizing Patient Care: AI-Driven Wearable Technology for Continuous Remote Health Monitoring

Remote patient monitoring (RPM) refers to the ability of healthcare professionals to be able to monitor the well-being of their patients remotely without having to keep them under continuous in-person observation. Wearable devices that are integrated with Artificial Intelligence are a blessing in disguise when it comes to remote health monitoring. PPG sensors, ECG sensors, accelerometers, pulse oximeter and EDA sensor are some of these AI integrated wearable devices used for continuous remote health monitoring which are discussed in this article. We delved into their specific working mechanism, how the data is collected, stored and transferred and how the use of artificial intelligence algorithms come into all of this. These devices have applications in fields such as cloud computing and big data analytics for health management which are discussed along with key innovations. Certain issues such as data accuracy, data privacy and regulations are also addressed along with future directions which can be pursued that may have the potential to revolutionize the field of remote health monitoring even more than its present advancements. The objective of this paper is to provide a comprehensive understanding of the role of AI-integrated wearable devices in remote patient monitoring (RPM), their mechanism of operation and significance in modern health care.