Mental Fitness Tracker Using Regression Models

Mental health plays an important role in human health affecting many aspects of life. However, evaluating and improving mental well-being is not an easy task because it involves many complex and unique elements. In this work, we employ artificial intelligence (AI) technology to propose a novel approach to track and enhance mental health. Our solution, called Mental Fitness Tracker, is a web-based application that tracks and analyzes user behavior, emotions, and mental health indicators using a range of data sources, such as social media, wearable technologies, online questionnaires, and natural language processing. In light of the data analysis, the program provides users with individualized recommendations, guidance, and actions to enhance their mental health.