Pedal Exerciser Settings Based on Daily Living Ability
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Solution Overview
Problem
Existing exercise equipment, such as pedal exercisers, lack the ability to provide personalized and effective training settings based on a user's daily living activities and physical capabilities, leading to inefficient muscle training.
Innovation Solution
A processing system and method that calculates recommended settings for pedal exercisers by analyzing user data, including daily living activities and physical information, to ensure the load placed on muscles does not exceed an individual's capabilities, adjusting parameters like rotational speed, load resistance, and geometric arrangements to optimize training.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed training settings are used on pedal exercisers, then device simplicity is maintained, but training effectiveness and user adaptability deteriorate
Solution Approach 1:
The system automatically calculates recommended training settings by processing user data (age, weight, height, medical conditions) through algorithms that determine safe and effective load parameters, eliminating the need for manual professional assessment while enabling personalized training programs
Solution Approach 2:
The system performs preliminary calculation of safe load limits and recommended training parameters before the user begins exercise, using pre-stored user profile data and medical information to establish personalized training boundaries in advance
2Reliability
If professional assessment is required for each user, then training safety is improved, but ease of operation deteriorates
Solution Approach 1:
The pedal exerciser system autonomously assesses user safety requirements by processing input data (age, weight, medical conditions) through embedded algorithms that determine safe load parameters, replacing the need for manual professional assessment while maintaining safety standards
Solution Approach 2:
The system continuously monitors training parameters and provides feedback on whether current exercise intensity remains within safe limits based on the user's profile, automatically adjusting recommendations to maintain safety without requiring ongoing professional supervision
3Productivity
If generic training programs are used, then device simplicity is maintained, but productivity deteriorates
Solution Approach 1:
The system pre-calculates optimal training parameters including load resistance, speed ranges, and duration recommendations based on user data before training begins, enabling users to start effective personalized programs immediately without requiring complex real-time adjustments during exercise
Data Source
AI summary
A processing system includes a processor. The processor is configured to: acquire user data including information on an activity of daily living a user is able to perform; calculate a recommended setting of training equipment that places a load on a muscle of the user, based on the user data; and output the recommended setting.