Authors - Jyotika R. Yadav, Arpit A. Jain Abstract - Internet of Things (IoT) with AI techniques help healthcare industry for patient monitoring and diagnosis. Wearable devices integrated with the Internet of Medical Things (IoMT) have transformed modern healthcare by enabling continuous, real-time monitoring of physiological parameters. The rapid evolution of Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), edge computing, and federated learning has further enhanced the reliability, privacy, and intelligence of such systems. Wearable devices like smart watch or smart sensors help doctors to monitor patient’s daily activities. However, these devices generate huge amount of data on day-to-day basis which makes analysis, monitoring, and diagnosis challenging. Machine Learning or Deep Learning models used for handling such large healthcare data. This survey consolidates and critically reviews recent research works to provide a holistic understanding of the current state-of-the-art in wearable AI-enabled healthcare. A detailed comparative analysis is provided to highlight similarities, differences, strengths, and limitations of existing approaches. Finally, key challenges and future research directions are discussed to guide the development of secure, scalable, and intelligent wearable healthcare solutions.
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