AI Exercise Program Generation Using User Energy Scores
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current exercise machines lack the ability to dynamically adjust and personalize exercise programs based on user energy scores and feedback, leading to inefficient bone growth and muscle strengthening, particularly for older or less mobile individuals or those recovering from injuries.
Innovation Solution
An AI-driven system that generates exercise programs by associating user energy consumption metrics with MET values, dynamically adjusts exercises based on user feedback, and assigns users to specific programs based on their energy scores, using load cells and sensors to provide real-time feedback on force exertion and compliance with exercise plans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If exercise programs are statically designed without dynamic adjustment, then device complexity is reduced, but adaptability to user energy levels and rehabilitation needs deteriorates
Solution Approach 1:
The exercise program transitions from a static, pre-defined structure to a dynamic system that automatically adjusts exercise parameters (intensity, duration, type) based on real-time user energy score measurements and feedback, enabling the program to adapt to changing user conditions without manual intervention
Solution Approach 2:
The system implements a closed-loop feedback mechanism where user energy scores are continuously measured during exercise, compared against target values, and used to automatically adjust subsequent exercise parameters, creating a self-regulating program that adapts to user capabilities
2Manufacturing precision
If generic exercise programs are used for all users, then ease of operation is improved, but manufacturing precision of exercise dosage deteriorates
Solution Approach 1:
The system precisely controls exercise dosage by dynamically adjusting key parameters (intensity, duration, exercise type) based on measured user energy scores, ensuring each user receives a customized exercise prescription that precisely targets their rehabilitation or fitness goals rather than using fixed generic programs
3Loss of information
If manual monitoring of user progress is used, then device complexity is reduced, but loss of information about user energy consumption deteriorates
Solution Approach 1:
The system automatically performs data collection, analysis, and program adjustment without requiring manual monitoring by trainers or users. The artificial intelligence engine autonomously processes energy score data, identifies trends, and modifies exercise programs, eliminating information loss while maintaining operational simplicity
Data Source
AI summary
Systems, methods, and computer-readable mediums for generating, by an artificial intelligence engine, an exercise program comprising a first user energy score, wherein the method comprises generating, by the artificial intelligence engine, the exercise program including an exercise plan including a plurality of exercises. Each respective exercise is associated with user energy consumption metrics based at least on a metabolic equivalent of task (MET) value, and based on the user energy consumption metrics, the first user energy score is associated with the exercise program. The method includes receiving data pertaining to a plurality of users. The data includes physical activity goals the plurality of users desires to achieve. The method includes determining second user energy scores for the physical activity goals, and based on the first and second user energy scores, assigning, by the artificial intelligence engine, at least a subset of the plurality of users to the exercise program.