Electronic Training System for Sports Feedback
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Solution Overview
Problem
Conventional sports performance monitoring systems suffer from information overload, making it difficult for athletes to discern relevant feedback and improve their performance, as they often lack synchronization with coaching methodologies and provide disconnected recommendations.
Innovation Solution
An electronic training system that integrates user feedback with AI-based evaluation, using a network environment with server and local AI systems, stimulus devices, and sensors to provide comprehensive, user-friendly feedback by annotating tracked data and adjusting stimuli based on responses, thus focusing on specific areas for improvement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional monitoring systems provide comprehensive recommendations, then more information is available to athletes, but information overload occurs making it difficult to discern relevant feedback
Solution Approach 1:
The system segments the comprehensive monitoring information into distinct categories (technical performance, tactical performance, physical condition, psychological state) and presents them separately through annotated tracked data and prioritized feedback, allowing athletes to process information in manageable segments rather than overwhelming comprehensive data streams
2Adaptability or versatility
If conventional systems provide disconnected recommendations, then multiple data sources are utilized, but synchronization with coaching methodologies is lost
Solution Approach 1:
The system implements feedback loops where AI-based evaluation continuously monitors athlete performance and provides recommendations that are synchronized with coaching methodologies. The system adjusts stimuli based on athlete responses and incorporates user feedback to maintain alignment between technological recommendations and coaching strategies, ensuring stable integration rather than disconnected advice
Solution Approach 2:
The system merges AI-based automated evaluation with human coaching methodologies into a unified feedback framework. By combining multiple data sources (sensors, video analysis, physiological monitors) and integrating them with coaching expertise through the AI system, it creates synchronized recommendations that maintain both technological versatility and methodological coherence
3Adaptability or versatility
If human observation is used to evaluate sports performance, then contextual understanding is achieved, but biases and measurement inaccuracies occur
Solution Approach 1:
The system replaces human observation and judgment with AI-based automated evaluation using sensors, video analysis, and computational algorithms. This substitution eliminates human biases and measurement inaccuracies while maintaining contextual understanding through advanced data processing that analyzes multiple performance dimensions simultaneously, achieving both precision and adaptability
Data Source
AI summary
An electronic training system includes external response sensors that detect and measure changes on the user's body, internal response sensors that measure internal changes within the user's body, a stimulus device, and control circuitry. The control circuitry tracks data from the response sensors and stimulus device to evaluate and provide feedback on the user's sports performance, receives input regarding the user's current and target sports performance states, retrieves relevant stimuli from a sports knowledge database, determines a set of test stimuli specific to the user, and controls the stimulus device to provide these stimuli. The circuitry further establishes associative relationship between each stimulus-response pair and the second set of responses, determines a plurality of causes of similarity and variability based on the established associative relationship, and calibrates the stimulus parameters based on the user's responses, current performance state and target performance state.