AI Exercise Guide Using Muscle Percentiles for Target Weight Setting
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Solution Overview
Problem
Users face difficulty in determining the appropriate target weight for exercise equipment based on their physical characteristics and exercise purpose, making it challenging to effectively utilize weightlifting equipment.
Innovation Solution
An AI exercise guide device that estimates muscle strength based on user data, detects a percentile value among preset adult muscle strength values, and adjusts the target weight of exercise equipment accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually determine target weight based on their own judgment, then they can use the exercise equipment, but they cannot confirm whether they are using it appropriately according to their physical characteristics and exercise performance
Solution Approach 1:
The system automatically determines the target weight by processing user input data (gender, age, weight, height, BMI, body fat percentage, exercise purpose) through algorithms, eliminating the need for users to manually calculate or judge appropriate weights. The exercise equipment self-adjusts based on detected muscle strength percentile values.
Solution Approach 2:
The patent replaces manual judgment and physical trial-and-error with an automated digital system that uses algorithms and data processing to determine target weights. The system substitutes human decision-making with computational analysis of user characteristics.
2Adaptability or versatility
If the exercise equipment provides fixed weight options, then the structure is simple, but it is difficult to adapt to different user physical characteristics and exercise purposes
Solution Approach 1:
The system dynamically adjusts the target weight based on real-time analysis of user characteristics and detected muscle strength. The weight recommendation is not fixed but adapts to each user's specific physical condition, exercise purpose, and performance level through automated processing.
Solution Approach 2:
The patent changes multiple parameters (gender, age, weight, height, BMI, body fat percentage, exercise purpose) to determine the appropriate target weight. The system adjusts the weight parameter based on combinations of these user-specific parameters rather than using fixed weight categories.
3Measurement precision
If the system automatically sets target weight based on multiple user parameters, then the accuracy improves, but the data processing complexity increases
Solution Approach 1:
The patent segments the data processing into distinct functional modules: a muscle strength estimation unit that calculates estimated muscle strength values from user data, a detection unit that identifies percentile values, and a target weight determination unit that sets appropriate weights. This modular approach manages complexity while maintaining precision.
Solution Approach 2:
The system introduces an intermediary processing layer that transforms raw user data into meaningful target weight recommendations. The detection unit acts as an intermediary that converts estimated muscle strength values into percentile rankings, which then guide target weight selection.
Data Source
AI summary
As a preferred embodiment of the present disclosure, an AI exercise guide device includes a muscle strength estimation unit for estimating an estimated muscle strength value of a user's specific muscle strength based on user data, a detection unit for detecting a percentile value to which the estimated muscle strength value belongs among preset adult muscle strength percentile values, and a PMW estimation unit for estimating a PMW of exercise equipment the user intends to use based on the detected percentile value.