The field of wearable technology and AI for health monitoring is rapidly evolving, with a focus on developing innovative solutions for real-time monitoring and prediction of various health conditions. Recent studies have explored the use of machine learning algorithms and small language models for mental health prediction, gait detection, and diabetes screening. These solutions have shown promising results, with high accuracy and efficiency in detecting health conditions and predicting outcomes. The use of wearable devices such as smartwatches and fitness trackers has also enabled the collection of large amounts of physiological and behavioral data, which can be used to develop personalized models for health monitoring. Notable papers in this area include the development of Menta, a small language model for on-device mental health prediction, and SweetDeep, a wearable AI solution for real-time non-invasive diabetes screening. These studies demonstrate the potential of wearable technology and AI to transform the field of health monitoring and improve patient outcomes.