Self-Calibrating Exercise Machine Load Thresholds via Bone Geometry
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Solution Overview
Problem
Conventional exercise machines do not tailor target load thresholds to individual users, leading to inefficient workouts and a failure to dynamically adjust as bone geometry changes over time, which can result in insufficient osteogenesis and muscle growth.
Innovation Solution
A system and method that determine a user's bone geometry and strain needed to trigger osteogenesis, calculating personalized target load thresholds based on individualized and empirical data, which are then displayed on a user interface during exercise, allowing for self-calibration and adjustment as bone geometry changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional exercise machines use fixed target load thresholds, then device complexity is reduced, but adaptability to individual users and dynamic adjustment to bone geometry changes deteriorates
Solution Approach 1:
The system performs preliminary actions by determining bone geometry and calculating personalized target load thresholds before the user begins exercising. This allows the exercise machine to be pre-configured with customized parameters specific to each user's bone structure, enabling adaptive exercise protocols without requiring complex real-time adjustments during exercise execution.
Solution Approach 2:
The system creates a digital model or representation of the user's bone geometry through scanning or measurement, then uses this copied data to calculate appropriate load thresholds. This copying approach allows the system to adapt to individual users by working with their specific anatomical data without requiring complex physical modifications to the exercise machine itself.
2Productivity
If conventional exercise machines use fixed target load thresholds, then ease of operation is improved, but effectiveness in triggering osteogenesis deteriorates
Solution Approach 1:
The system performs self-calibration by automatically determining bone geometry and calculating personalized target load thresholds without requiring manual intervention or complex user input. The exercise machine autonomously adapts to each user's specific needs, maintaining ease of operation while significantly improving the effectiveness of osteogenesis training through scientifically optimized load parameters.
3Adaptability or versatility
If personalized target load thresholds are calculated based on bone geometry, then adaptability to individual users is improved, but measurement precision requirements increase
Solution Approach 1:
The system applies partial measurement by focusing on specific bone geometry parameters that are most critical for determining target load thresholds, rather than requiring complete and ultra-precise measurements of all bone characteristics. This approach achieves sufficient personalization accuracy for effective osteogenesis training without demanding excessively high measurement precision that would complicate the system.
Data Source
AI summary
A system and method for intelligent self-calibration of target load thresholds for users of exercise machines is disclosed herein. In one embodiment, a method includes determining, by one or more processing devices, a bone geometry of a bone in a portion of a body of a user, where said portion is going to be exercised by the user performing an exercise on an exercise machine. The method also includes determining, using the bone geometry, a strain on the bone in the portion of the body of the user such that the strain triggers osteogenesis, determining a target load threshold to be added by the user to the exercise machine during the exercise to achieve the strain that triggers osteogenesis, and, while the user performs the exercise on the exercise machine, causing the target load threshold to be represented on a user interface of a computing device.