Abstract
Generic workout plans often fail to meet individual needs, leading to sub-optimal outcomes and an increased risk of injury. The Personalized Workout Generator offers a solution by utilizing `learning to create customized fitness routines based on the user’s specific goals, physical condition, and progress. The system begins by allowing users to select their fitness objectives, such as weight loss, yoga, weight training, or body-weight exercises. It then collects data on the user's fitness level, preferences, and other relevant factors, which is used to generate a tailored workout plan. The system continuously tracks the user’s progress and updates the workout plan based on completed sessions, adherence, and changes in fitness metrics, ensuring the plan remains challenging and aligned with the user’s evolving needs. Additionally, user feedback is incorporated to refine the plan further. This dynamic, adaptive approach offers a safe and effective solution for users of all fitness levels, enhancing motivation, reducing the risk of injury, and helping individuals achieve their fitness goals more efficiently. Key Words: Personalized Workout, Machine Learning, Fitness Plan, User Progress Tracking, Adaptive Fitness System, Injury Prevention, Workout Customization
Published Version
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