Smart AI Workout Analysis

AI-powered workout analysis aims to identify areas of improvement and the scaling of workout difficulty based on each user's performance and progression.

To implement this, the app continuously collects and analyzes user workout data, such as completed exercises, performance metrics, user feedback, and physiological data from wearable devices. The AI model then processes this data, making use of advanced machine learning techniques to identify patterns, trends, and correlations. Unsupervised learning will be at great use here helping to outline irregularities or non-standard correlations in data unnoticeable to the human eye.

For example, the AI might discover that a user's performance tends to decline after a certain intensity threshold is reached, indicating a potential area for improvement. Similarly, it may identify that a user performs better in certain exercises but struggles in others, suggesting where emphasis should be placed in subsequent workout plans.

The AI models will also be capable of scaling the difficulty of the workout plans in a gradual and controlled manner. As the user progresses and their fitness level improves, the AI will intelligently increase the complexity and intensity of the workouts, ensuring continual growth and challenge. This dynamic adjustment is not only based on performance but also considers factors such as user feedback, recovery times, and changes in lifestyle or health status.