Exercise Selection System Using User Feedback
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Solution Overview
Problem
Existing methods for selecting physical exercises do not adequately consider user objectives or feelings, leading to discomfort and inefficiency in exercise performance, as they primarily focus on improving weak muscle parameters without accounting for user goals or emotional responses.
Innovation Solution
A system that uses a movement sensor, such as an accelerometer or gyroscope, to classify exercises based on user objectives and physical qualities, incorporating user feedback to select exercises that align with their goals and preferences, shifting from a 'top-down' to a 'bottom-up' approach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Strength
If exercises are automatically selected based solely on improving weakest muscle parameters, then muscular performance is improved, but user comfort and alignment with user goals deteriorate
Solution Approach 1:
The system incorporates user feedback loops where users report their comfort levels and goal alignment during exercise execution. This feedback is used to dynamically adjust exercise selection, ensuring both muscular improvement and user comfort are maintained. The feedback mechanism transforms the system from a purely objective-based selector to a user-centered adaptive system.
Solution Approach 2:
The exercise selection system transitions from a static, goal-based selection to a dynamic process that continuously adapts based on real-time user feedback. The system dynamically adjusts exercise parameters, intensity, and type to balance muscular performance improvement with user comfort and goal alignment, making the selection process flexible and responsive to user needs.
2Stability of the object's composition
If a top-down model is used where coaches impose exercises on users, then training structure is provided, but user autonomy and personalization deteriorate
Solution Approach 1:
The system enables users to actively participate in their own exercise selection process by providing tools for self-assessment, goal setting, and feedback submission. Users can input their own comfort levels and preferences, which the system then uses to personalize exercise recommendations. This self-service approach empowers users while maintaining structured training guidance.
Solution Approach 2:
The system inverts the traditional top-down coach-to-athlete exercise selection model by placing user feedback and preferences at the center of the decision-making process. Instead of coaches unilaterally determining exercises, the system uses user-reported comfort and goals as primary inputs for exercise selection, fundamentally reversing the direction of personalization.
3Productivity
If exercises are selected without considering user feedback, then selection speed is maintained, but exercise effectiveness and user satisfaction deteriorate
Solution Approach 1:
The system performs preliminary assessments of user goals, comfort levels, and preferences before exercise selection begins. By gathering this feedback information in advance and using it to pre-filter and pre-rank exercise options, the system maintains fast selection speeds while ensuring exercises are tailored to user needs. The preliminary feedback collection enables rapid, personalized exercise recommendation without compromising effectiveness.
Data Source
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AI summary
The present invention relates to a method for automatically selecting exercises to be offered to a user (7) wearing a mobile device (5) comprising a processor (23), the user (7) also wearing a motion sensor, for example an accelerometer (3) configured to communicate with the mobile device (5). The method comprises the following steps: - classifying a predefined collection of exercises in a database; - automatic selection by the mobile device (5) and/or by the accelerometer (3), this selection taking into account at least one piece of feedback from the user. The feedback indicates the user's (7) sensation during the performance of an exercise.