Early Diagnosis of Chronic Diseases Using AI-Enabled Wearable Devices
Abstract
Chronic diseases such as cardiovascular disorders, diabetes, respiratory illnesses, neurological conditions, and sleep disorders require early diagnosis to improve patient outcomes and reduce healthcare costs. Recent advances in Artificial Intelligence (AI), wearable sensors, and the Internet of Medical Things (IoMT) have enabled continuous health monitoring and predictive disease detection. This review examines AI-enabled wearable devices, including smartwatches, fitness bands, smart rings, ECG patches, and continuous glucose monitors, along with the physiological parameters they monitor. Various AI techniques, including machine learning, deep learning, Edge AI, and federated learning, are discussed for disease prediction and risk assessment. The review highlights the effectiveness of wearable AI systems in achieving high diagnostic accuracy, supporting remote patient monitoring, and enabling personalized healthcare. Key challenges related to privacy, security, and regulatory compliance are also analyzed.