Motion Tracking Sensors with AI Form Feedback
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Solution Overview
Problem
Existing systems for monitoring motion data in athletics training require expensive equipment and professional trainers, and often fail to provide feedback on form or technique, which is crucial for preventing injuries and improving performance.
Innovation Solution
A cost-effective, user-friendly system utilizing sensors to track motion count, speed, power, form, heart rate, distance, and calories burned, with an accompanying app that provides real-time feedback and analysis to improve athletic performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expensive equipment and professional trainers are used to monitor motion data, then measurement precision and reliability are improved, but device complexity and cost increase
Solution Approach 1:
The system enables users to independently monitor and analyze their own motion data using automated sensors and AI analysis, eliminating the need for professional trainers to interpret data. The app automatically provides feedback on form, technique, and performance metrics, allowing users to self-diagnose and self-correct their movements.
Solution Approach 2:
The patent replaces complex mechanical monitoring systems with sensor-based detection and software analysis. Instead of using expensive specialized equipment, the system uses accelerometers, gyroscopes, and other motion sensors combined with AI algorithms to achieve accurate motion analysis and form feedback.
2Loss of information
If professional trainers interpret motion data, then feedback quality on form and technique is improved, but ease of operation and accessibility worsen
Solution Approach 1:
The system implements automated feedback loops where sensors continuously monitor motion data, AI algorithms analyze form and technique in real-time, and the app provides immediate corrective feedback to users. This continuous feedback mechanism replaces the need for professional trainers while maintaining high-quality form analysis through automated detection of motion patterns and deviations.
Solution Approach 2:
The patent introduces an AI-based software intermediary that acts as a bridge between raw sensor data and user understanding. The app translates complex motion data into actionable feedback on form and technique, making professional-level analysis accessible to ordinary users without requiring them to hire trainers or understand complex data.
3Loss of information
If comprehensive sensors track multiple health and motion parameters, then information completeness is improved, but device complexity and data processing requirements increase
Solution Approach 1:
The system uses multi-functional sensors that can detect multiple types of data simultaneously. For example, accelerometers and gyroscopes serve both motion tracking and form analysis functions, while heart rate monitors provide both health metrics and workout intensity data. This multi-functionality reduces the need for separate specialized sensors for each parameter.
Solution Approach 2:
The patent combines multiple sensor types and data streams into a unified analysis platform. Instead of treating motion data, health data, and form data as separate systems, the integration merges all sensor inputs into a single comprehensive analysis framework that processes multiple parameters simultaneously and provides holistic feedback.
Data Source
AI summary
A computer-implemented method executed using a first computer includes receiving motion data from a set of one or more sensors, initializing one or more motion variables corresponding to a particular motion, analyzing the first motion data to identify one or more instances of the particular motion and to determine one or more motion values corresponding to the one or more motion variables, and generating and transmitting display instructions which, when rendered using a second computer, cause the second computer to display at least one of the one or more motion values. The one or more motion variables include one or more of repetition count, speed, power, and form.