Real-time health tracking garment: MyWear

MyWear, a pioneering wearable T-shirt for proactive health care and high-level patient management. MyWear continuously tracks and forecasts critical physiological parameters, such as stress levels and heart rate variability, and is thus especially useful in the management of cardiovascular diseases, monitoring stress, improving sports performance, and delivering holistic health care. The device has been tested stringently with different machine learning models such as K-Nearest Neighbour (KNN), Support Vector Machine (SVM), Naïve Bayes, Logistic Regression, Decision Tree, and Stochastic Gradient Descent (SGD) to identify abnormal heart rhythms effectively. Remarkably, the SVM model produced a high average accuracy of 98% in identifying possible health problems. In the future, MyWear will be integrated with mobile apps seamlessly to allow real-time data visualization and analysis. This convergence not only improves patient outcomes with real-time feedback but also promotes increased user activation towards health management. Through the convergence of sophisticated wearable technology and machine learning, MyWear is a major leap towards customized health monitoring, enabling users to manage their health and wellbeing independently while supporting timely intervention on emerging health risks.