Personal Workout Plans

At Athlerse, our goal is to not only help users reach their fitness goals but to do so in a manner that is efficient, enjoyable, and sustainable. And the use of AI will help us build personalized workout plans to facilitate this.

User data collection, processing and analysis is essential for any data-driven decisions. This includes basic information such as age, weight, height, and gender, as well as more specific fitness details such as current activity level, past workout history, personal preferences, and specified fitness goals. The Athlerse app integrates with a variety of wearable devices for real-time tracking of physiological data like heart rate, sleep patterns, and activity levels.

This extensive user data forms the basis for our AI models, which use machine learning algorithms to analyze the data and develop personalized workout plans. Our models will employ a hybrid of supervised learning to leverage the vast data collected and reinforcement learning for continual improvement over time. The AI learns from every user interaction, refining the workout plans as it gains more insights about the user's progress, responsiveness, and preferences. The workout plan is not static but rather dynamic and adaptable. It adjusts to users' feedback, progress, and changes in their lifestyle or goals. For instance, if the AI notices that a user consistently struggles to complete a particular exercise or meets their step goal more easily than anticipated, it can modify the plan to better suit their abilities and needs.