Athletic Training Optimization via Heart Rate and GPS Data Processing
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Solution Overview
Problem
Athletes face challenges in determining their current fitness level for optimal training, as existing methods like lactate threshold testing are expensive and impractical for frequent use, and relying solely on race times can be stressful and inaccurate, disrupting training rhythms.
Innovation Solution
A system and method for monitoring and updating an athlete's fitness level using heart rate and navigation data from baseline and training activities, allowing for personalized and frequent adjustments to training paces without the need for frequent lactate threshold tests or races, by processing data to identify fitness level changes and prompting users to maintain target heart rates or paces during specific runs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If lactate threshold testing is used to determine fitness level, then measurement precision is improved, but loss of time and ease of operation deteriorate due to expense and impracticality for frequent use
Solution Approach 1:
The system enables athletes to self-monitor their fitness level continuously through automated processing of heart rate and navigation data from routine training activities, eliminating the need for external laboratory testing services. The processor automatically identifies fitness level changes by comparing current data against historical baselines, allowing athletes to obtain fitness assessments independently and frequently without requiring professional testing facilities.
Solution Approach 2:
The patent replaces the mechanical/physical lactate threshold testing system with an electronic data processing system that uses heart rate monitors and GPS devices. Instead of collecting physiological samples and performing laboratory analyses, the system electronically captures, stores, and processes training data to derive fitness level information, substituting complex laboratory mechanics with simple electronic sensing and computation.
2Measurement precision
If lactate threshold testing is used, then measurement precision is improved, but ease of operation worsens due to cost and complexity
Solution Approach 1:
The system enables athletes to self-monitor their fitness level continuously through automated processing of heart rate and navigation data from routine training activities, eliminating the need for external laboratory testing services. The processor automatically identifies fitness level changes by comparing current data against historical baselines, allowing athletes to obtain fitness assessments independently and frequently without requiring professional testing facilities.
Solution Approach 2:
The patent employs inexpensive, widely available consumer electronics (heart rate monitors, GPS devices, smartphones) rather than expensive specialized laboratory equipment. These common devices capture sufficient data for fitness assessment, making the system accessible and easy to operate for typical athletes without requiring investment in costly testing infrastructure.
3Ease of operation
If race times are used to determine fitness level, then ease of operation is improved, but measurement precision and reliability deteriorate due to stress and disruption to training
Solution Approach 1:
The system continuously collects and processes training data during regular athletic activities rather than requiring discrete race events. Heart rate and navigation data are gathered throughout ongoing training sessions, providing a continuous stream of information for fitness assessment. This continuous monitoring approach maintains training rhythm while accumulating sufficient data for accurate fitness level determination.
Solution Approach 2:
The system provides real-time feedback to athletes about their training intensity and fitness level changes. By continuously analyzing heart rate data against pace data and historical baselines, the system generates feedback that helps athletes understand their current fitness state and adjust training accordingly, replacing the delayed feedback from race results with immediate, actionable information.
Data Source
AI summary
Methods and apparatuses for athletic training optimization are disclosed. In one example, a fitness level change is identified. In one example, a current training intensity is updated to reflect an updated user fitness level.


