Physical activity prediction using fitness data: Challenges and issues

In the new healthcare transformations, individuals are encourage to maintain healthy life based on their food diet and physical activity routine avoid risk of serious disease. One recent technologies support self health monitoring is wearable device that allow individual play active role own healthcare. However, there still questions in terms accuracy data for recommending due enormous fitness generated by devices. this study, we conducted a literature review machine learning techniques predict suitable activities personal context data. We categorize structure research evidence has been publish area predicting using found 10 different models Behavior Change Technique (BCT) selected two which Fogg Model (FBM) Trans-theoretical (TTM) proposed conceptual framework consists data, combination TTM FBM context. This study will provide insights software development personalization managing health.