Personalized Fitness Course Generation via Physiological Sensing
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Solution Overview
Problem
Existing fitness applications lack personalization based on individual physical conditions, failing to tailor workout plans effectively for users' specific fitness levels, experiences, and preferences.
Innovation Solution
A system and method that connects electronic devices to a backend database to generate personalized fitness courses by sensing physiological parameters, such as heart rate and muscle recovery rates, and adjusts workout plans based on user input and preferences, including muscle groups, exercise intensity, and rest times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If fitness applications run on a single device with stand-alone operation, then the application can record individual fitness history, but it cannot personalize fitness classes based on the individual's physical condition
Solution Approach 1:
The patent introduces a backend database server as an intermediary between the mobile device and the fitness course generation system. The mobile device collects physiological data (heart rate, recovery rate, tiredness level) and transmits it to the server, which then generates personalized fitness courses based on this data. This intermediary architecture enables personalized fitness planning without requiring complex processing capabilities in the mobile device itself.
2Adaptability or versatility
If the electronic device is connected to the database in the server to generate big data, then remote servers can generate fitness classes based on big data, but it requires network connection and increases system complexity
Solution Approach 1:
The system performs preliminary data collection and analysis by storing physiological parameters and fitness history in the backend database before generating fitness courses. The server maintains a database of big data from multiple users, which is processed in advance to create personalized fitness plans. This preliminary action allows the system to quickly generate customized courses when needed without requiring complex real-time processing during exercise sessions.
3Measurement precision
If sensing modules are arranged to sense physiological parameters, then the system can provide fitness exercise course suggestions, but it increases hardware requirements and cost
Solution Approach 1:
The patent employs a multi-functional sensing module that can detect multiple physiological parameters (heart rate, recovery rate, tiredness level) using a single integrated device. This universal sensing approach eliminates the need for separate sensors for each parameter, reducing hardware complexity and cost while maintaining comprehensive physiological monitoring capabilities for personalized fitness course generation.
Data Source
AI summary
A system for planning a fitness exercise course includes a corresponding module establishing a corresponding relationship between a training target and each of a plurality of fitness exercise items, wherein the training target includes a specific muscle, a muscle group and a whole body muscle; a sensing module sensing a physiological state of a body builder; and a determining module, according to the corresponding relationship, in response to the physiological state, selecting one of the plurality of fitness exercise items and a combination of fitness exercise items to complete the training target.